Microstructure and Properties of Plasma Sprayed and Sol-gel Modified Hydroxyapatite
Coatings
By
Md. Fahad Hasan
A thesis submitted in total fulfilment of the requirements of the degree of
Doctor of Philosophy in the Faculty of Engineering and Industrial Sciences
All rights reserved. This thesis may not be reproduced in whole or in part, by photocopy or
other means, without the permission of the author.
Md. Fahad Hasan, 2014 Swinburne University of Technology
Hawthorn, Melbourne, VIC 3122
Abstract
ii | P a g e Author: Md. Fahad Hasan
Abstract
Hydroxyapatite (HA, Ca10(PO4)6(OH)2) has a calcium phosphate phase that exhibits a
similar chemical structure to that of bone and teeth. For the deposition of HA coatings,
plasma spray is the accepted technique that has been approved by the Food and Drug
Administration (FDA). However, plasma spray is a complex deposition method, involving a
myriad of process parameters, types of equipment, and powder characteristics that have a
direct effect on the coating properties. The conventional trial and error optimization
process is expensive and time consuming. Thus, there is a need to develop strong
scientific correlations among the prime thermal spray parameters that permit the
manufacture of quality coatings. In this research, prime plasma spray process parameters
have been optimised with respect to several important coating properties.
Plasma spray HA coatings have a vast range of applications in the area of biomedical
engineering. For these applications, the coating quality is of prime importance and
indentation test method is a suitable technique to determine the coating quality. Plasma
spray coatings exhibit complex microstructures that consist of flat plate–like lamellae,
cracks, pores, unmelted particles, weak interfaces between splats, and oxides: features
that all contribute to highly heterogeneous and anisotropic behaviour. The effects of
applied load, measurement direction, and indent location on the microhardness are
investigated in this thesis using Vickers and Knoop indentation methods.
It is found that top surface microhardness is higher than the cross-section
microhardness. It is seen that measuring the effect of lower applied loads (50 and 100 gf)
and higher applied loads (300 and 500 gf) shows two distinct trends concerning
microhardness, indent roughness, and Weibull modulus of microhardness throughout the
dense areas of the coating thickness during Vickers indentation. The microhardness,
elastic modulus, Weibull modulus of microhardness, and Weibull modulus of elastic
modulus reach their maximum at central position (175 µm) on the cross-section of the
coatings on application of the Knoop indentation technique. Also, dependence of the
Knoop microhardness values on the indentation angle follows Pythagoras’ theorem.
Abstract
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Author: Md. Fahad Hasan
Plasma spraying of HA offers superior osteoconductivity. However, plasma spray
coatings contain cracks, pores and residual stress that reduce the durability, mechanical
properties and also can cause partial or complete delamination of the coatings. In this
research, sol-gel HA coatings are applied on the plasma sprayed HA coatings to improve
the coating properties.
It is found that the porosity, microhardness, and surface roughness are improved after
sol-gel treatment on the plasma spray HA coatings. Also, phase structure and crystallinity
show some improvement. The Ca/P ratio exhibits a higher value on the sol-gel modified
thermal spray coatings for both top surface and cross-section compared to the typical
thermal spray coatings.
Acknowledgements
iv | P a g e Author: Md. Fahad Hasan
Acknowledgements I wish to express my deep sense of gratitude from the core of my heart to my
supervisor Prof. Christopher C. Berndt for his invaluable guidance, motivation, instructions,
untiring efforts, encouragement, and meticulous attention that launches my research and
development skill as well as the ability to conduct research independently. It was only
possible to reach at this stage, only for Prof. Berndt continuous feedback and input.
I would also like to thank Dr. James Wang for being supportive and cooperative
throughout this whole research. Thanks to Associate Professor Paul Stoddart for his
advice during characterizing sample using Raman spectroscopy system. I must thank the
senior technical officers Mr. Andrew Moore and Mr. Brian Dempster for their technical help
throughout the progress of my project. I must acknowledge Dr. Deming Zhu for his advice
during characterizing sample using Raman spectroscopy and 3D profiler system. I would
also like to thank every member of Laser and Thermal Spray Technology (L-TST) Group at
Swinburne for their support and help.
I also acknowledge international experts in thermal spray technology during their
visits to Swinburne University of Technology. Thanks to Prof. Sanjay Sampath from Stony
Brook University, USA; Dr. Shrikant Josh i f r om ARCI , India; and Prof. Ghislain
Montavon from LERMPS, France.
Special thanks to Dr. Sylvia Mackie and Ruth Fluhr for their proof-reading help.
I am also grateful to my family (Father, mother, brother, sister, brother-in-law) for their
prayers, supports, and encouragements during my study. Thanks again; especially to my
father and mother.
Author’s Declaration
v | P a g e Author: Md. Fahad Hasan
Author’s Declaration I hereby declare that this thesis presented for the degree of Doctor of Philosophy to the
Faculty of Engineering and Industrial Sciences, Swinburne University of Technology. The
candidate also declares that this thesis is solely candidate’s own work and contains no
material that has been accepted for the award of any other degree or diploma, except
where due references is made in the text. This work has been carried out under the
supervision of Prof. Christopher C. Berndt at Swinburne University of Technology,
Melbourne, Australia.
Md. Fahad Hasan
Table of Contents
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Table of Contents
1. Introduction ................................................................................................................. 1
1.1. Objectives of the research project ........................................................................... 3
1.2. Structure of thesis ................................................................................................... 3
2. Literature review ......................................................................................................... 5
2.1. Hydroxyapatite ........................................................................................................ 5
Structure and phase diagram.......................................................................... 6 2.1.1.
Comparison of HA and bone .......................................................................... 8 2.1.2.
Dissolution behaviour ..................................................................................... 9 2.1.3.
Thermal behaviour ........................................................................................ 10 2.1.4.
Hydroxyapatite powder ................................................................................. 12 2.1.5.
Deposition of HA coatings ............................................................................ 13 2.1.6.
2.2. Thermal spray process .......................................................................................... 15
Plasma spray process .................................................................................. 16 2.2.1.
High velocity oxygen fuel (HVOF) spray process.......................................... 22 2.2.2.
Microstructure of the HA coatings ................................................................. 23 2.2.3.
2.3. Sol-gel process ..................................................................................................... 28
Advantages of sol-gel coatings ..................................................................... 29 2.3.1.
Sol-gel chemistry .......................................................................................... 29 2.3.2.
Sol-gel coating techniques ............................................................................ 30 2.3.3.
Sol-gel HA coatings ...................................................................................... 32 2.3.4.
2.4. Optimization of HA coatings .................................................................................. 32
Design of experiments (DOE) ....................................................................... 33 2.4.1.
Importance of design of experiments ............................................................ 36 2.4.2.
Factorial and fractional factorial experiments ............................................... 36 2.4.3.
Taguchi orthogonal arrays ............................................................................ 38 2.4.4.
Response surface methodology ................................................................... 39 2.4.5.
DOE for plasma sprayed HA coatings .......................................................... 41 2.4.6.
2.5. Indentation techniques .......................................................................................... 43
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Brinell hardness test ..................................................................................... 44 2.5.1.
Meyer hardness test ..................................................................................... 45 2.5.2.
Rockwell hardness test ................................................................................. 45 2.5.3.
Vickers hardness test ................................................................................... 47 2.5.4.
Knoop hardness test ..................................................................................... 48 2.5.5.
Leeb hardness test ....................................................................................... 49 2.5.6.
Microhardness study on thermal spray coatings ........................................... 50 2.5.7.
Errors in microhardness testing for thermal spray coatings .......................... 55 2.5.8.
2.6. Summary ............................................................................................................... 55
3. Experimental equipment, procedure, and materials characterization ................. 58
3.1. Plasma spray system ............................................................................................ 58
3.2. Feedstock morphology .......................................................................................... 62
3.3. Preparation of substrate and coating cross-sections ............................................. 62
Substrate ...................................................................................................... 62 3.3.1.
Grit blasting and substrate cleaning procedure ............................................ 62 3.3.2.
Coating mounting, grinding and polishing ..................................................... 62 3.3.3.
3.4. Characterization of HA coatings ............................................................................ 65
Scanning electron microscopy (SEM) & energy dispersive X-ray 3.4.1.
spectroscopy (EDS) ...................................................................................... 65
X-Ray diffraction (XRD) ................................................................................ 66 3.4.2.
Raman spectroscopy .................................................................................... 68 3.4.3.
Profilometer .................................................................................................. 68 3.4.4.
3.5. Analysis of coatings .............................................................................................. 69
Porosity measurements ................................................................................ 69 3.5.1.
Microhardness and elastic modulus measurements ..................................... 70 3.5.2.
Deposition efficiency measurements ............................................................ 71 3.5.3.
Crystallinity measurements ........................................................................... 71 3.5.4.
Surface roughness measurements ............................................................... 72 3.5.5.
4. Relationship between process parameters according to literature survey ......... 74
4.1. Introduction ........................................................................................................... 74
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4.2. Methodology.......................................................................................................... 74
4.3. Results & discussions ........................................................................................... 75
Relationship between power and stand-off distance..................................... 75 4.3.1.
Relationship between power and powder feed rate ...................................... 75 4.3.2.
Relationship between power and powder particle size ................................. 77 4.3.3.
Relationship between powder feed rate and powder particle size ................ 78 4.3.4.
4.4. Summary ............................................................................................................... 78
5. Taguchi design of experimental study on HA coatings ........................................ 79
5.1. Introduction ........................................................................................................... 79
5.2. Methodology.......................................................................................................... 80
5.3. Results & discussions ........................................................................................... 83
Porosity ......................................................................................................... 83 5.3.1.
Microhardness .............................................................................................. 85 5.3.2.
Deposition efficiency ..................................................................................... 85 5.3.3.
Crystallinity ................................................................................................... 87 5.3.4.
Surface roughness ........................................................................................ 88 5.3.5.
Numerical optimization of coating properties ................................................ 89 5.3.6.
5.4. Summary ............................................................................................................... 91
6. Effect of power and stand-off distance on the HA coatings ................................. 93
6.1. Introduction ........................................................................................................... 93
6.2. Methodology.......................................................................................................... 93
6.3. Results & discussions ........................................................................................... 94
Morphology and microstructure of the coatings ............................................ 94 6.3.1.
Porosity and deposition efficiency ................................................................. 96 6.3.2.
Physical properties: microhardness and roughness ..................................... 98 6.3.3.
Phase structure and crystaliinity ................................................................... 99 6.3.4.
6.4. Summary ............................................................................................................. 101
7. Microhardness study using indentation techniques ........................................... 103
7.1. Introduction ......................................................................................................... 103
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7.2. Methodology........................................................................................................ 103
7.3. Microhardness study using Vickers indentation .................................................. 104
Effects of applied load on the microhardness and indenter tip roughness .. 106 7.3.1.
Effects of indenter location on the microhardness and indenter tip 7.3.2.
roughness ................................................................................................... 110
Effects of testing direction ........................................................................... 110 7.3.3.
Rule of mixture............................................................................................ 111 7.3.4.
Weibull modulus analysis ........................................................................... 113 7.3.5.
7.4. Microhardness study using Knoop indentation .................................................... 116
Effects of indentation angle on the microhardness and elastic modulus ..... 118 7.4.1.
Effects of testing direction on the microhardness and elastic modulus ....... 120 7.4.2.
Effects of indent location on the microhardness and elastic modulus ......... 122 7.4.3.
Weibull modulus analysis for microhardness and elastic modulus ............. 123 7.4.4.
Depth of indentation .................................................................................... 126 7.4.5.
Frequency distribution ................................................................................ 128 7.4.6.
Student’s t-test ............................................................................................ 130 7.4.7.
Effects of indentation on the microstructure ................................................ 132 7.4.8.
7.5. Summary ............................................................................................................. 132
8. Sol-gel modified thermal spray coatings .............................................................. 136
8.1. Introduction ......................................................................................................... 136
8.2. Methodology........................................................................................................ 137
8.3. Effects of sol-gel coatings on microstructure improvement ................................. 138
8.4. Coating properties ............................................................................................... 142
Porosity ....................................................................................................... 142 8.4.1.
Microhardness ............................................................................................ 143 8.4.2.
Surface roughness ...................................................................................... 144 8.4.3.
Weibull modulus analysis for coating properties ......................................... 144 8.4.4.
8.5. Phase structure and crystallinity .......................................................................... 146
8.6. Ca/P ratio ............................................................................................................ 149
8.7. Summary ............................................................................................................. 152
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9. Conclusions, major contributions, and future work ............................................ 154
9.1. Conclusions......................................................................................................... 154
Process parameter and DOE study ............................................................ 154 9.1.1.
Micromechanical study ............................................................................... 155 9.1.2.
Study of the sol-gel modified thermal spray coatings .................................. 156 9.1.3.
9.2. Future work ......................................................................................................... 157
References ..................................................................................................................... 158
Appendix ........................................................................................................................ 186
List of Figures
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List of Figures Figure 2-1 Hexagonal hydroxyapatite crystal structure. Red = calcium, Light blue =
phosphorous, Yellow = oxygen ................................................................... 7
Figure 2-2 Phase diagram of the system CaO-P2O5 at high temperature (a) with no
water present (b) at a partial water pressure of 500 mmHg. ....................... 8
Figure 2-3 States of matter. ......................................................................................... 16
Figure 2-4 Plasma spray system.................................................................................. 17
Figure 2-5 High velocity oxygen fuel (HVOF) apparatus .............................................. 22
Figure 2-6 Typical thermal spray coatings with common features. .............................. 23
Figure 2-7 Typical structure of plasma sprayed hydroxyapatite coating (a) top
surface, and (b) cross-section .................................................................... 24
Figure 2-8 Grains within a HA coating splat. ................................................................ 24
Figure 2-9 Typical HA splat on metal surface with one big and several smaller
pores........................................................................................................... 25
Figure 2-10 Coating-development-model. ...................................................................... 26
Figure 2-11 Splat-development-model dependent on plasma flame temperature. ........ 27
Figure 2-12 Possible phase development in half melted HA powder particle. ............... 27
Figure 2-13 Sol-gel process ........................................................................................... 28
Figure 2-14 Stages of the dip coating process (a) dipping of the substrate into
coating layer formation, (b) wet layer formation by withdrawing the
substrate, and (c) gelation of the layer by solvent evaporation. .................. 31
Figure 2-15 Stages of the spin coating process (a) placing small amount of solution
on the substrate, (b) rotating the substrate at high speed, and (c) drying
the film ........................................................................................................ 32
Figure 2-16 General model of a process/system ........................................................... 34
Figure 2-17 Coatings build up. ....................................................................................... 35
Figure 2-18 Steps of design of experiment .................................................................... 35
Figure 2-19 Central composite design with cube points, star points and centre points .. 40
Figure 2-20 Brinell hardness testing. ............................................................................. 44
Figure 2-21 Rockwell working principle .......................................................................... 46
List of Figures
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Figure 2-22 Vickers hardness testing ............................................................................. 47
Figure 2-23 Knoop hardness testing .............................................................................. 49
Figure 2-24 HVOF titania coatings (a) top surface, and (b) cross-section. .................... 51
Figure 2-25 Comparison of Weibull plots of (a) conventional PSZ coatings, and (b)
nanostructured PSZ coatings ..................................................................... 53
Figure 2-26 Cause-effect diagram of microhardness measurement for thermal spray
coatings. ..................................................................................................... 56
Figure 3-1 Plasma spray booth. ................................................................................... 58
Figure 3-2 Plasma spray torch SG 100. ....................................................................... 59
Figure 3-3 Control system. ........................................................................................... 60
Figure 3-4 Powder feeder unit. .................................................................................... 61
Figure 3-5 Gas supply system. .................................................................................... 61
Figure 3-6 HA powder (a) morphology, and (b) particle size distribution. .................... 63
Figure 3-7 Automatic Struers cutter. ............................................................................ 64
Figure 3-8 Metallographic preparation (a) grinding (P240-P1200), (b) coarse
polishing (15 and 5 µm), and (c) smooth polishing (1 µm). ......................... 65
Figure 3-9 Scanning electron microscopy (SEM). ........................................................ 66
Figure 3-10 X-ray diffractometry (XRD). ........................................................................ 67
Figure 3-11 Raman spectroscopy system. ..................................................................... 68
Figure 3-12 Two dimensional profilometer. .................................................................... 69
Figure 3-13 Three dimensional profilometer. ................................................................. 69
Figure 3-14 The Ra parameter. ...................................................................................... 73
Figure 4-1 Relationship between power and stand-off distance (a) with all data, (b)
with average data, and (c) with good data. ................................................. 76
Figure 4-2 Relationship between power and powder feed rate. ................................... 76
Figure 4-3 Relationship between power and powder particle size. .............................. 77
Figure 4-4 Relationship between powder feed rate and powder particle size. ............. 78
Figure 5-1 Plasma spray process parameters graph from literature survey a) power
vs. stand-off distance, and b) power vs. powder feed rate.......................... 81
Figure 5-2 Plasma spray process with factors and responses for Taguchi L9
design. ........................................................................................................ 82
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Figure 5-3 Main effects plot generated by Minitab software. ........................................ 84
Figure 5-4 Main effects plot generated by Minitab software. ........................................ 85
Figure 5-5 Main effects plot generated by Minitab software. ........................................ 87
Figure 5-6 Main effects plot generated by Minitab software. ........................................ 88
Figure 5-7 Main effects plot generated by Minitab software. ........................................ 89
Figure 6-1 SEM surface morphology a) sample 1: (20 kW, 8 cm), b) sample 4:
(30kW, 11 cm), and c) sample 7: (40 kW, 16 cm). ...................................... 95
Figure 6-2 Cross-section of the coatings a) sample 1: (20 kW, 8 cm), b) sample 4:
(30 kW, 11 cm), and c) sample 7: (40 kW, 16 cm). ..................................... 96
Figure 6-3 Influence of spraying parameters on the porosity of hydroxyapatite
coatings (a) porosity, (b) deposition efficiency, (c) microhardness, and
(d) surface roughness. ................................................................................ 97
Figure 6-4 Influence of process parameters on the a) crystallinity, b) XRD pattern
for i) sample 1: (20 kW, 8 cm), ii) sample 4: (30 kW, 11 cm), and iii)
sample 7: (40 kW, 16 cm) of hydroxyapatite coatings. .............................. 100
Figure 7-1 Schematic of Vickers indentation at different indent location within a
typical thermal spray coating microstructure. .............................................. 105
Figure 7-2 SEM micrographs of plasma sprayed hydroxyapatite coating (a) top
surface, and (b) cross-section. ................................................................... 106
Figure 7-3 Effects of applied load on the microhardness of the coating top section
a) dense area, and b) porous area. ............................................................ 107
Figure 7-4 Effects of applied load and distance from the substrate-coating interface
of the coating on the microhardness a) dense area, and b) porous area
(indent location is presented in Fig. 7-1; 100 and 300 gf data are
presented on the x-axis position of 77, 177, and 277 µm for clear
visualisation). .............................................................................................. 108
Figure 7-5 Effects of applied load on the surface roughness of indenter horizontal
tip. ............................................................................................................... 109
Figure 7-6 Effects of applied load and distance from the substrate-coating interface
of coating on the indent roughness (indent location is presented in Fig.
List of Figures
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Author: Md. Fahad Hasan
7-1; 100 and 300 gf data are presented on the x-axis position of 77,
177, and 277 µm for clear visualisation). .................................................... 109
Figure 7-7 Combined microhardness on the top surface using rule of mixture for
75% dense and 25% porous area, 50% dense and 50% porous area,
25% dense and 75% porous area microhardness. ..................................... 112
Figure 7-8 Microhardness on the cross-section calculated using rule of mixture for
a) 75% dense and 25% porous area, b) 50% dense and 50% porous
area, and c) 25% dense and 75% porous area microhardness (100 and
300 gf data are presented on the x-axis position of 77, 177, and 277 µm
for clear visualisation). ................................................................................ 113
Figure 7-9 Weibull modulus of microhardness on the top surface a) dense area,
and b) porous area. .................................................................................... 114
Figure 7-10 Weibull modulus of microhardness on the cross-section a) dense area,
and b) porous area (indent location is presented in Fig. 7-1)...................... 115
Figure 7-11 Schematic of Knoop indentation at different indent location within typical
thermal spray coatings microstructure. ....................................................... 117
Figure 7-12 Distributions of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic
modulus (adjusted data) with change of indentation angle with the
substrate-coating interface (indentation angle is presented in Fig. 7-11;
100 and 300 gf data are presented on the x-axis position at 2⁰, 47⁰,92⁰
for clear visualisation). ................................................................................ 118
Figure 7-13 Distributions of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic
modulus (adjusted data) with change of testing directions and applied
loads. .......................................................................................................... 120
Figure 7-14 Distributions of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic
modulus (adjusted data) at different locations on the cross-section
(indent location is presented in Fig. 7-11; 100 and 300 gf data are
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Author: Md. Fahad Hasan
presented on the x-axis position of 77, 177, and 277 µm for clear
visualisation). .............................................................................................. 121
Figure 7-15 Weibull modulus of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic
modulus (adjusted data) with different indentation angles (indentation
angle is presented in Fig. 7-11). ................................................................. 124
Figure 7-16 Weibull modulus of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic
modulus (adjusted data) with change of testing directions. ........................ 125
Figure 7-17 Weibull modulus of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic
modulus (adjusted data) on the cross-section (indent location is
presented in Fig. 7-11)................................................................................ 126
Figure 7-18 Depth of indentation variation with change of indentation angles
(indentation angle is presented in Fig. 7-11). .............................................. 127
Figure 7-19 Depth of indentation variation with change of testing directions. ................ 127
Figure 7-20 Depth of indentation variation with change of indent locations on the
cross-section (indent location is presented in Fig. 7-11). ............................ 128
Figure 7-21 Frequency distribution of microhardness on the cross-section at the
centre (175 µm) of the coatings. ................................................................. 129
Figure 7-22 Frequency distribution of microhardness on the top surface. ..................... 129
Figure 7-23 Indentation on the cross-section of the coatings at the centre position
(175 µm) with an applied load of 100 gf (a, b) without splat movement,
and (c, d, e, f) with splat movement (‘HK’ indicates Knoop
microhardness value and ‘a’ indicates major diagonal length of Knoop
indentation). ................................................................................................ 132
Figure 8-1 Sol-gel modified thermal spray coatings with active top layer. .................... 136
Figure 8-2 Typical thermal spray coatings top surface. ................................................ 139
Figure 8-3 Sol-gel modified thermal spray coating top surface morphology after 3
days from the sol-gel treatment day. .......................................................... 139
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Figure 8-4 Sol-gel modified thermal spray coating top surface after 7 days from the
sol-gel treatment day. ................................................................................. 140
Figure 8-5 Typical thermal spray coating cross-section. .............................................. 141
Figure 8-6 Sol-gel modified thermal spray coating cross-section. ................................ 141
Figure 8-7 Sol-gel modified thermal spray coating cross-section after using gold
coatings by PVD technique on the top surface of the sample. .................... 142
Figure 8-8 Porosity variation for typical thermal spray coatings and sol-gel modified
thermal spray coatings throughout the coating’s thickness......................... 143
Figure 8-9 Microhardness variation for typical thermal spray coatings and sol-gel
modified thermal spray coatings throughout the coatings thickness with
load of (a) 50 gf, (b) 100 gf, and (3) 300 gf (sol-gel modified coatings
microhardness data are presented on the x-axis position of 77, 177, and
277 µm for clear visualisation). ................................................................... 144
Figure 8-10 Comparison of Weibull modulus of microhardness on the cross-section
of typical thermal spray coatings and sol-gel modified thermal spray
coatings with applied loads of (a) 50 gf, (b) 100 gf, and (c) 300 gf. ............ 145
Figure 8-11 Comparison of Weibull modulus of porosity for typical thermal spray
coatings and sol-gel modified thermal spray coatings. ............................... 146
Figure 8-12 Comparison of XRD spectra for typical thermal spray coatings and sol-
gel modified thermal spray coatings. .......................................................... 147
Figure 8-13 Raman spectra comparison for typical thermal spray coatings and sol-
gel modified thermal spray coatings within a Raman frequency of (a)
200-2000 cm-1 (PO4 band), and (b) 3000-5000 cm-1 (OHˉ band). ............... 148
Figure 8-14 Comparison of Ca/P ratio on the top surface and cross-section. ................ 149
Figure 8-15 Ca/P ratio variations throughout the coating thickness. .............................. 150
List of Tables
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List of Tables Table 2-1 Chemical composition of hydroxyapatite. ................................................... 7
Table 2-2 Comparison of bone and hydroxyapatite ceramics ..................................... 9
Table 2-3 Mechanical properties of HA and bone ....................................................... 9
Table 2-4 Thermal effects of HA . ............................................................................... 12
Table 2-5 Comparison of different methods to deposit HA coatings ........................... 14
Table 2-6 Primary and secondary parameters ............................................................ 18
Table 2-7 A 3 factor, 2 level factorial experiments ...................................................... 37
Table 2-8 A 5 factor, 2 level fractional factorial experiments. ..................................... 38
Table 2-9 Summary of DOE studies done on plasma sprayed HA coatings. .............. 42
Table 3-1 Parameters used for SEM analysis of HA coatings and HA powder. .......... 66
Table 3-2 Parameters used for XRD analysis of HA coatings and HA powder. .......... 67
Table 5-1 Plasma spray process parameters predicted from literature study. ............ 82
Table 5-2 Process parameters used in Taguchi L9 design. ........................................ 82
Table 5-3 Coating properties. ..................................................................................... 83
Table 5-4 ANOVA table for coatings porosity. ............................................................ 84
Table 5-5 ANOVA table for coatings microhardness. ................................................. 86
Table 5-6 ANOVA table for coatings deposition efficiency. ......................................... 87
Table 5-7 ANOVA table for coatings crystallinity. ....................................................... 89
Table 5-8 ANOVA table for coatings surface roughness. ........................................... 90
Table 5-9 HA optimisation criteria. .............................................................................. 90
Table 5-10 Comparison of results between actual and estimated performance of
coating properties. ...................................................................................... 91
Table 6-1 Plasma spray process parameters. ............................................................ 94
Table 6-2 Chemical composition of the coatings for samples. .................................... 101
Table 7-1 Plasma spray parameters. .......................................................................... 104
Table 7-2 Comparison of microhardness data with Pythagoras’ theorem. .................. 119
Table 7-3 Student’s t-test for the microhardness on the top surface with original
(n=20) and adjusted data (n=16). ............................................................... 130
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Table 7-4 Student’s t-test for the microhardness on the cross-section with original
(n=20) and adjusted (n=16) data. ............................................................... 131
Table 8-1 Plasma spray parameters. .......................................................................... 138
Table 8-2 Full width at half maximum (FWHM) comparison for typical thermal
spray coatings and sol-gel modified thermal spray coatings with PO4
band and OHˉ band. ................................................................................... 147
Table 8-3 Comparison of chemical composition on the top surface and cross-
section of typical thermal spray and sol-gel modified thermal spray
coatings. ..................................................................................................... 150
Table 8-4 Comparison of chemical composition throughout the thickness for
typical thermal spray coatings and sol-gel modified thermal spray
coatings. ..................................................................................................... 151
Table 8-5 Chemical composition of the sol-gel coatings. ............................................ 152
List of Terms and Abbreviations
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List of Terms and Abbreviations Al2O3 Alumina
ANOVA Analysis of variance
APS Air plasma spray
ASTM American standard for testing and materials
Ba Barium
BSI British standards institution
CaO Calcium oxide
Cl Chloride
CO3 Carbonate
C2P Monetite
CCD Central composite design
DD Draft documents
DE Deposition efficiency
DOE Design of experiment
EDS Energy dispersive X-ray spectroscopy
ENV European pre-standard
F Fluoride
FDA Food and drug administration
FWHM Full width at half maximum
HA Hydroxyapatite
HPO4 Acid phosphate
HVOF High velocity oxygen fuel
ImageJ Image processing and analysis in Java
ISO International organisation for standardization
List of Terms and Abbreviations
xx | P a g e
Author: Md. Fahad Hasan
K Potassium
Mg Magnesium
Na Sodium
NiAl Cermet
NIH National Institutes of Health
NIST National Institute of Standards and Technology
OHA Oxyhydroxyapatite
Pb Lead
PLC Programmable logic controller
PSZ Partially stabilized zirconia
PVD Physical vapour deposition
SEM Scanning electron microscopy
SOD Stand-off distance
SLPM Standard litres per minute
Sr Strontium
TCP Tricalcium phosphate
TTCP Tetracalcium phosphate
VPS Vacuum plasma spray
XRD X-ray diffraction
YSZ Yttria-stabilised zirconia
Chapter 1 Introduction
1 | P a g e Author: Md. Fahad Hasan
1. Introduction
Biomaterials are critical components in artificial organs, and they are used as
scaffolds in tissue engineering to replace a part or a function of the body in a safe,
reliable, economic and physiologically acceptable manner. The goal of using
biomaterials is to improve human health by restoring the function of natural living
tissues and organs in the body. Therefore, it is necessary to understand the
properties, functions, and structures of biological materials. The success of a
biomaterial used in an implant depends on the properties and biocompatibility of the
implant, the health condition of the recipient, and the competence of the surgeon
who monitors its progress.
Biomaterials are a worldwide multi-billion dollar industry and it is increasing day
by day. Biomaterials have helped to improve, support, and sustain the lives of over
20 million patients over the last decade and the number of patients has increased by
10% per year. The market for organ replacement and prostheses exceeds $300
billion US dollars per year and represents between 7-8% of total worldwide
healthcare spending. The market for organ replacement and prostheses exceeds
$300 billion US dollars per year and represents between 7-8% of total worldwide
healthcare spending. In the United States alone, the cost of therapies enabled by
organ replacement technology exceeds 1% of the gross national product [1]. These
large expenses highlight the importance of biomaterial development. As a
consequence, research in this area is essential to improve materials and reduce
costs.
This area of materials science is shaped by medical needs, material
characterisation and design, basic research, advanced technological development,
patient expectation, ethical considerations, industrial involvement, and federal
regulation [2]. Such multidisciplinary research requires expertise and techniques
used in a wide variety of subjects such as materials science, chemistry, molecular
and cell biology, mathematics, engineering, biomechanics, computer modelling,
manufacturing, medicine, and genetics. Biomaterial devices are available for joint
and limb replacements; artificial arteries and skin; contact lenses; and dentures: all
of which aim to replace damaged or diseased tissues. However, prostheses may
Chapter 1 Introduction
2 | P a g e Author: Md. Fahad Hasan
also be used for enhancement of the body, of which the most well-known is the
breast implant.
The applications of biomaterials are expanding daily. Biomaterials are widely
used in orthopaedic applications, repair of skeletal tissues, hip, knee, ankle,
shoulder, and elbow joint replacement. This current study is focussed on such
orthopaedic applications.
Metallic devices for orthopaedic applications have been very successful, and
hundreds of thousands of them are implanted annually and applied to removable
devices, such as those for stabilisation of fractures. The use of metals as
biomaterials has been increasing in demand throughout the history of joint
replacement. Only metals and some composite materials possess the mechanical
strength required to withstand the high loads imposed in uniaxial directions in load
bearing joints. Metals and alloys differ in comparison to bone in terms of their
properties and their biological response. Disadvantages in selecting metals include
harmful ion release [3] and a lower quality of biological response than other types of
materials. Thus, to provide protection, a biocompatible coating on metals is
preferred. Hydroxyapatite (HA), Ca10(PO4)6(OH)2, is well accepted as a bioactive and
biocompatible coating closely resembling the mineral phase in bone, and able to
form a strong implant-bone interfacial bond to improve prosthesis fixation [4, 5].
Several methods and techniques [6-15] have been introduced to coat
hydroxyapatite on metal. Among several deposition techniques, thermal spray, in
particular plasma spraying, is the most commonly used method for the application of
HA coatings, and it is also the only Food and Drug Administration (FDA) approved
method. However, plasma spray has as many as 50 variable process parameters
that make it challenging to understand process-structure-property relationships and
to optimise parameters.
Other challenges include understanding the micromechanical properties of
thermal spray HA coatings. It is necessary to understand microhardness and elastic
modulus distributions throughout the coatings to properly understand thermal spray
HA coatings.
Chapter 1 Introduction
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Thermal spray HA coatings contain pores and cracks that may have a detrimental
effect on micromechanical properties, resulting in partial or complete delamination of
the coatings. However, pores and cracks are beneficial for initial bone growth. Thus,
a novel approach is needed to fulfil these two conflicting requirements.
1.1. Objectives of the research project
The main objectives of this research project are presented below:
a) The first goal of this research was to understand and optimise plasma
spray process parameters for hydroxyapatite coatings in order to obtain
optimum coating properties. The investigation also includes the effects of
process parameters on the coating properties and microstructure.
b) The second goal was to analyse and understand thermal spray
micromechanical properties (microhardness, elastic modulus) using the
Vickers and Knoop indentation technique with respect to the change of
applied load, indent location, and indentation angle. Then, statistical
analysis was carried out to understand the microhardness and elastic
modulus data.
c) The third goal of this research was to modify the plasma spray coatings
using the sol-gel technique to improve the properties of the coatings.
1.2. Structure of thesis
The thesis is divided into nine chapters.
Chapter 1 was the introduction of this thesis which described the importance of
this work, and goal of this research project.
Chapter 2 contains an extensive literature review. The review encompasses an
overview of the properties of HA, thermal spray process, sol-gel process, design of
experiment (DOE), and indentation techniques.
The experimental procedure and equipment are presented in Chapter 3. A
detailed description of plasma spray equipment and feedstock description are
included. Also, the characterization and analysis of coatings using different
equipment are described.
Chapter 1 Introduction
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Chapter 4 provides information related to the relationship between plasma spray
process parameters. The process parameters collected from the available published
literature are employed to establish the relationships.
Chapter 5 includes a description of the optimisation of HA coatings using Taguchi
DOE technique. Three factors and five responses were considered for the DOE
design. The process parameters are optimized in this chapter with respect to
optimum coating properties.
Chapter 6 emphasises the effect of power and stand-off distance on the HA
coating properties and microstructure. Power and stand-off distance are coupled and
the effect of these coupled factors on both the properties of the coatings and the
microstructures are investigated.
Microhardness and elastic modulus study results are presented in Chapter 7.
Vickers microhardness results and Knoop microhardness results with respect to
applied load, indent location, testing direction, and indent angle are discussed in this
chapter. Statistical analysis results are also presented in this chapter.
Chapter 8 discusses comparison of typical thermal spray coatings and sol-gel
modified thermal spray coatings. Typical thermal spray coatings are modified using
sol-gel coatings to improve the coating properties.
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2. Literature review
2.1. Hydroxyapatite
In the current era of nanotechnology, hydroxyapatite (HA) coatings have a great
importance in the biological and biomedical coating fields. Since hydroxyapatite
coatings fulfil the requirement of choice of a material, i.e., proper specification, an
accurate characterization, length of the time to function, and safe for humans. HA
can be applied to bioinactive implants to make their surface bioactive, and enable
faster healing and recovery [16].
Hydroxyapatite is a hydrated calcium phosphate mineral. In 1788, Proust and
Klaprota were the first researchers who recognised the similarity between calcium
phosphate bioceramics and the mineral component of bone [17]. The development
of many commercial and non-commercial calcium phosphate materials, including
ceramic HA, non-ceramic HA, β-TCP, coralline HA, and biphasic calcium phosphates
was based on this similarity. In 1920, Albee was the first scientist who successfully
repaired a bony defect with a calcium phosphate reagent, identified as triple calcium
phosphate compound [18].
The production of ceramic materials for use in dental and medical applications
was developed by Levitt and Monroe in the late sixties and early seventies [19]. The
research was continued in the mid-seventies and scientists worked simultaneously,
but independently on the development and commercialization of hydroxyapatite in
the USA, Europe, and Japan [19].
Calcium phosphate ceramics have been used for dental implants, orthopaedics,
maxillofacial surgery, periodontal treatment, alveolar ridge augmentation, and
otolaryngology for about thirty years [20]. They are used as a coating material
Materials from this section (Section 2.1, 2.2, 2.4) have been accepted in the
following book as a book chapter:
Berndt, C.C.; Hasan, Md. Fahad; Tietz, U.; Schmitz, K.-P.; Book Chapter title: A
review of hydroxyapatite coatings manufactured by thermal spray, Book title:
Advances in calcium phosphate biomaterials, Series title: Springer Series in
Biomaterials Science & Engineering, Editor: Ben‐Nissan, B., Vols. 2, pp 267-329,
2014.
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6 | P a g e Author: Md. Fahad Hasan
applied onto a tougher substrate because of their inherent brittleness in the case of
load bearing applications. HA coatings and HA composite coatings are used
commercially for hip and knee replacements [21].
Structure and phase diagram 2.1.1.
Werner [17] was the first scientist who, in 1786, named hydroxyapatite as a
mineral. The name was derived from the Greek word ‘to deceive’ [17]. The chemical
formula of HA is Ca10(PO4)6(OH)2 and it has a Ca/P ratio of 1.67 [22]. Beevers and
Mclntyre first reported the structure of HA and it was later refined by Kay et al. [19].
HA is the most abundant naturally occurring phosphate on earth. It provides a
major source of phosphorus to the global phosphorus cycle. Sometimes, it is also
referred to as hydroxylapatite [23, 24], calcium hydroxyapatite or apatite and it has a
similar composition to bone. It is a brittle ceramic with a calculated density of 3.22
g/cm3. Synthetic HA is considered to be a stoichiometric material, whereas biological
apatites are generally considered non-stoichiometric due to vacancies or
substitutions that can commonly occur. HA is monoclinic with lattice parameters of
a = 9.4214 Å, b = 2a, c = 6.8814 Å, γ = 120° and a lattice volume of 528.8 Å3. Figure
2-1 shows the crystal structure of HA. The unit cell contains Ca, PO4, and OHˉ ions
closely packed together to represent the apatite structure.
HA, like all apatites, has a hexagonal system with the space group P63/m; thus
defining it as a material family [19, 25]. The acceptance of a hexagonal P63 structure
is limited because this structure gives a poor least squares fit to XRD diffraction. To
achieve better fit to diffraction patterns, two monoclinic models have been
suggested, P21/b [26] and P21 [27] and also more energetically favourable models
of the structure of HA. Their chemical composition and Ca/P ratio are summarised in
Table 2-1.
The hydroxyapatite phase changes to various other phases upon heat treatment.
A phase diagram presents the various phases of a substance under a particular
condition. A phase diagram for hydroxyapatite is important because it can describe
the formation of different phases with respect to temperature. Figure 2-2 shows the
phase diagram of hydroxyapatite (a) with no water present and (b) at a partial water
pressure of 500 mmHg.
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Figure 2-1 Hexagonal hydroxyapatite crystal structure [28]. Red = calcium, Light blue
= phosphorous, Yellow = oxygen
Table 2-1 Chemical composition of hydroxyapatite [29, 30].
Symbol Chemical formula Chemical definition Ca/P
MCP Ca(H2PO4)2 Monocalcium Phosphate hydrate 0.50
DCPA CaHPO4 Dicalcium Phosphate Anhydrous 1.00
DCPD CaHPO.2H2O Dicalcium Phosphate Dihydrate 1.00
OCP Ca8H2(PO4)6.5H2O Octocalcium Phosphate 1.33
α-TCP α-Ca3(PO4)2 α-Tricalcium Phosphate 1.50
Β-TCP β- Ca3(PO4)2 β-Tricalcium Phosphate 1.50
TTCP Ca4(PO4)2O Tetracalcium phosphate 2.00
OHA Ca10(PO4)6(OH)2-2xOx Oxyhydroxyapatite 1.67
OA Ca10(PO4)6O Oxyapatite 1.67
HA Ca10(PO4)6(OH)2 Hydroxyapatite 1.67
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Figure 2-2 Phase diagram of the system CaO-P2O5 at high temperature (a) with no
water present (b) at a partial water pressure of 500 mmHg [22, 31].
From Fig. 2-2 (a) it can be seen that hydroxyapatite is not stable under these
conditions. It can decompose into other calcium phosphates such as tetracalcium
phosphate (TTCP), tricalcium phosphate (TCP), monetite (C2P) and mixtures of
calcium oxide (CaO) and C4P. Figure 2-2 (b) shows that HA is stable up to 1,550 ºC.
HA powder is influenced by the partial pressure of water in the surrounding
atmosphere and the stoichiometry changes when it is heated. Fang et al. [32]
reported the effect of stoichiometry on the thermal stability of HA from experiments
where the Ca/P ratios of HA powder samples remained within 1.52 to 1.68 when
heated to 1,100 ºC.
Comparison of HA and bone 2.1.2.
HA, due to its apatite structure, contains many impurities that allow substitutions
of other ions. For example, if there is a deficiency in either calcium or carbonate
species, then sodium (Na+), magnesium (Mg2+), acid phosphate (HPO4), potassium
(K+), carbonate (CO32-), fluoride (F-), and chloride (Cl-) ions may be substituted as
minor elements. The trace elements of strontium (Sr2+), barium (Ba2+), and lead
(Pb2+) may also be observed. Synthetic HA and the main constituents of bone are
compared in Table 2-2.
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Table 2-2 Comparison of bone and hydroxyapatite ceramics [33].
Constituents (wt.%) Bone HA Ca 24.5 39.6 P 11.5 18.5
Ca/P ratio 1.65 1.67 Na 0.7 Trace K 0.03 Trace
Mg 0.55 Trace CO3
2- 5.8 -
There are different methods available to deposit calcium phosphate, and the
mechanical properties of calcium phosphate vary depending on their deposition
technique. HA powder differs in grain size and in composition because of the
difference in preparation methods of the HA scaffold materials. Small grain sizes
lead to greater fracture toughness. Table 2-3 shows the comparison of mechanical
properties of cortical bone, cancellous bone, and HA scaffolds.
Table 2-3 Mechanical properties of HA and bone [34, 35].
Properties Cortical bone Cancellous bone HA scaffolds Compressive strength (MPa) 130-180 4-12 350-450
Tensile strength (MPa) 50-151 1-5 38-48 Young’s modulus (GPa) 12-18 0.1-0.5 7-110
Dissolution behaviour 2.1.3.
Hydroxyapatite is stable in body fluids. However, the dissolution rates of other
phases formed due to high temperature of the plasma spray may be variable. The
dissolution of a material is dictated by its free energy corresponding to a lower
solubility product. The new phases appearing in the HA coating are tri-calcium phase
[Ca3(PO4)2, TCP; i.e., α-TCP and/or β-TCP], tetra-calcium phosphate (Ca4P2O9; i.e.,
TTCP), calcium oxide (CaO), oxyhydroxyapatite (OHA) and oxyapatite (OA). The
dissolution order is as follows [19, 36]:
CaO >> TCP>ACP>TTCP >OHA/OA >> HA
Among all these phases, CaO has no biocompatibility and dissolves significantly
faster than TCP, so it is necessary to avoid this detrimental phase. The dissolution of
HA coating increases with an increase in porosity and surface area, and a decrease
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in particle size and crystallinity. The dissolution decreases as the crystallinity of the
coating increases. Sun et al. [37] reported that coatings sprayed at lower power
(27.5 kW) demonstrated a pattern of crystalline HA; whereas coatings sprayed at
higher power (42 kW) exhibited a pattern of bone apatite.
The dissolution of unstable phases in the coating led to an undesirable reduction
of the mechanical strength. However, these dissolved phases have been shown to
enhance bone tissue growth, as reported by Ducheyne et al. [38] and Porter et al.
[39]. Ducheyne et al. [38] compared the performance of three calcium phosphate
coatings (polylactic acid /calcium deficient HA, calcium deficient HA and
oxyhydroxyapatite/α-TCP/β-TCP) with an uncoated implant in vivo. The calcium
phosphate coated implants allowed a greater degree of bone growth than the
uncoated implant.
Thermal behaviour 2.1.4.
The plasma spray process involves melting of particles by a plasma flame at high
temperature (up to 16,600 ºC) that causes thermal decomposition and changes the
balance of phases of each particle [40]. Since plasma sprayed HA coatings form with
a significantly different crystal structure, phase composition, and morphology than
the original starting powder; the changes occurring within the plasma flame need to
be understood to ensure that the coating produced has the required composition.
There are various processes involved in the thermal decomposition of HA. The
heating of HA leads to three processes in particular [22]:
• Evaporation of water
• Dehydroxylation and
• Decomposition
Evaporation of water
The hydroxyapatite structure has the capacity to absorb water. This water can be
present both on the surface of the powder and trapped within pores [41]. The
absorbed water begins to evaporate when heated and lattice water starts to
evaporate on further heating [42].
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Dehydroxylation
The dehydroxylation reaction has been reported by several authors [42, 43], and
is as follows:
Ca10(PO4)6(OH)2 → Ca10(PO4)6(OH)2-2xOxVx + xH2O (1)
(Hydroxyapatite) → (Oxyhydroxyapatite)
Ca10(PO4)6(OH)2-2xOxVx → Ca10(PO4)6OxVx + (1-x)H2O (2)
(Oxyhydroxyapatite) → (Oxyapatite)
where V represents vacancy and x < 1
In the first step, there is a formation of a hydroxyl ion deficient product, known as
oxyhydroxyapatite (OHA). OHA has a large number of vacancies in its structure, a
bivalent oxygen ion and a vacancy substitute for two monovalent OHˉ ions of HA
[42]. In the second step, dehydroxylation leads to the formation of oxyapatite. In the
presence of water, oxyhydroxyapatite and oxyapatite readily transform back to
hydroxyapatite [36].
Decomposition
Hydroxyapatite decomposes into another phase at high temperature. There is
agreement between researchers about the processes that occur during the thermal
decomposition of HA. HA retains its crystal structure up to a critical point. When the
critical point is exceeded, complete and irreversible decomposition occurs. During
decomposition, HA converts into other calcium phosphate phases such as β-tri-
calcium phosphate (β-TCP) and tetra-calcium phosphate (TTCP). Firstly, oxyapatite
transforms into tricalcium phosphate and tetracalium phosphate. In the next step,
tricalcium phosphate and tetracalcium phosphate convert into calcium oxide [42, 44,
45].
Ca10(PO4)6Oxٱx → 2Ca3(PO4)2 (β) + Ca4(PO4)2O (3)
(oxyapatite) → (tricalcium phosphate) + (tetracalcium phosphate)
Ca3(PO4)2 → 3CaO + P2O5 (4)
(tricalcium phosphate) → (calcium oxide) + (phosphorus pentoxide)
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Ca4(PO4)2O → 4CaO + P2O5 (5)
(tetracalcium phosphate) → (calcium oxide) + (phosphorus pentoxide)
It is difficult to predict the exact temperatures at which reactions occur. The
reactions do not occur instantly, but over a range of temperatures, depending on a
number of factors related to the environment and the composition of the HA. Table 2-
4 shows the temperature range in which reactions occur as HA is heated from room
temperature to 1,730 ºC.
Table 2-4 Thermal effects of HA [22].
Temperature (ºC) Reaction(s)
25-200 Evaporation of absorbed water 200-600 Evaporation of lattice water 600-800 Decarbonation
800-900 Dehydroxylation of HA forming partially or completely dehydroxylated oxyhydroxyapatite
1,050-1,400 HA decomposes to form β-TCP and TTCP <1,120 β-TCP is stable
1,120-1,470 β-TCP is converted to α-TCP 1,550 Melting temperature of HA 1,630 Melting temperature of TTCP, leaving behind CaO 1,730 Melting of TCP
Hydroxyapatite powder 2.1.5.
HA feedstock is the foundation for the thermal spray coating process. The ASTM
standard F1609 [46], which is comparable with other standards from FDA or ISO,
provides limitations for feedstock concerning crystallinity, particle form and in vivo
and in vitro behaviour. Therefore, several common parameters for the feedstock
have become accepted. Usually, a fully crystalline pure HA powder is the basis,
which is generally manufactured using phosphate-containing and calcium-ion-
containing ingredients. After mixing both components, calcination leads to the HA
feedstock [47].
The ASTM Standard Specification (ASTM F1185-03 [48]) states that surgical
implants require a minimum of 95% of HA content, established by a quantitative X-
ray diffraction (XRD) analysis, while the concentration of trace elements should be
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limited; e.g., arsenic 3 ppm, cadmium 5 ppm, mercury 5 ppm, and lead 30 ppm. The
HA phase is required by the International Organisation for Standardization (ISO
13778-1: 2000, Implants for surgery, Hydroxyapatite – Part 1: Ceramic
hydroxyapatite) [49] to exhibit a crystallinity of at least 45%. The maximum allowable
total limit of all heavy metals is 50 ppm. The Ca/P ratio for HA used for surgical
implants must be between 1.65 and 1.82 [48].
The quality of coating depends on the shape of HA powders for plasma spray
deposition. The particles are melted or partly melted in the plasma flame; thus the
morphology of the powder particles relate directly to the heating rate. Irregularly
shaped particles exhibit a higher degree of particle heating within the plasma flame
due to their greater surface area to volume ratio than spherical particles. Spherical
particles have better flow properties than angular particles and can be more reliably
transported to the plasma flame.
Powder with a narrow range of particle sizes will result in more consistent
coatings. The particles must also be capable of withstanding the spray environment.
For example, Cheang et al. [50] observed that weakly agglomerated HA powders
fragment within the plasma stream giving a new distribution of smaller particles that
influences the coating microstructure.
Deposition of HA coatings 2.1.6.
Several techniques are available to deposit HA coatings, such as thermal spray[6,
7], physical vapour deposition [8], electrophoretic deposition [9, 10, 51], biomimetry
[12, 52], sol-gel methods [13, 53, 54], and pulsed laser deposition [15]. The
comparisons of all the techniques are drawn in Table 2-5.
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Table 2-5 Comparison of different methods to deposit HA coatings [16, 47].
Technique Thickness (µm) Advantages Disadvantages
Thermal spray 30-200
• High deposition rate;
• Low cost;
• Line-of-sight technique;
• High temperature;
• Rapid cooling produces amorphous coating;
Physical vapour deposition
0.5-3.0
• Uniform thickness;
• Dense coating;
• Line-of-sight technique;
• Time consuming;
• Produces amorphous coating;
Electrophoretic deposition
0.1-2.0
• Uniform thickness;
• High deposition rate;
• Can coat complex shapes;
• High sintering temperature;
• Difficult to produce crack free coatings;
Biomimetry <30 • Bone-like apatite
formation;
• Can coat complex substrates;
• Time consuming;
• Requires replacement and constant conditions;
Sol-gel 50-500 • Inexpensive;
• Can coat complex shapes;
• Homogenous coatings;
• High sintering temperature;
• Thermal expansion mismatch;
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The selection of a particular process depends on several factors, such as:
• Process cost.
• Process energy.
• Requirement and availability of the apparatus.
• Limitation imposed by the substrate.
• Mechanical compatibility of the coatings with the substrate.
• Adhesion of the deposited material with the substrate.
• Requirement of the deposition rate.
• Purity of the target material.
Among all the available deposition techniques, thermal spray, in particular plasma
spray, has been approved by the Food and Drug Administration (FDA) for the
deposition of hydroxyapatite coatings [55]. The sol-gel coating method is also used
for depositing HA coatings since it is economical and provides homogenous
coatings.
2.2. Thermal spray process
Thermal spray basically employs high temperature and velocity to melt the
powder or wire as a feedstock and deposit the surface of one material on another.
Thermal spray methods can be divided into two types: (i) chemical energy of the
combustion gases that power the flame spray torch, and (ii) electric currents
providing energy for plasma generators. Thermal spray can be further classified as:
(i) Flame spray, (ii) Plasma spray, (iii) High velocity oxygen fuel (HVOF) spray, (iv)
Electric arc spray, and (v) Cold spray. Among these, plasma and HVOF spray are
widely used for spraying HA coatings.
The plasma spray method offers the possibility of preparing large scale coatings
that exhibit excellent adhesion to substrates with complex shapes [47, 56]. Plasma
spraying has the ability to produce specialised coatings with functional properties
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that are beneficial to the field of biomedical engineering, such as biocompatibility,
fixation, corrosion, and wear resistance [57-59].
Plasma spray process 2.2.1.
Plasma spray is regarded as the most versatile of all the thermal spray
processes; i.e., flame spraying, arc spraying and HVOF. The plasma spraying
process uses the latent heat of two ionised inert gases to create the heat source.
The most common gases used to create plasma are argon, as the primary, and
hydrogen or helium as the secondary gases. However, the gas usage depends on
the type of material to be sprayed and the method of application.
A plasma is a complex process environment and phenomenon. When the gases
are heated to a particular temperature, the atoms collide with each other due to the
excitation and knock their electrons off in the process to form a plasma flame.
Plasmas are used in many processing techniques; for example, for the modification
and activation of surfaces. There is currently much research being carried out to
understand and control plasma. Figure 2-3 shows the different states of matter.
Figure 2-3 States of matter [60].
Figure 2-4 shows a typical torch and plasma spray coating process. The
advantages of plasma spray have been widely recognised in many industries. The
unique features that characterise plasma spray processing are listed below:
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The process
• is simple and flexible.
• can control coating parameters by the appropriate setting of process
parameters.
• produces uniform coating.
• can melt any metals, ceramics or composites.
• has a high deposition rate.
The plasma spray system consists of an electronically controlled power supply, a
Programmable Logic Controller (PLC)-based operator control station, a gas mass
flow system, a closed-loop water chilling system, a powder feeder, and a plasma
torch [61]. A primary inert gas, such as argon, is injected between two water-cooled
electrodes (the anode and cathode) in the gun, where it is ionised to form a plasma
jet when ignited. Any powders injected into the plasma flame will melt and
subsequently be deposited onto the substrate to form a coating [62]. The particle
velocities of plasma spraying are higher than flame and arc spraying, and therefore,
it produces denser coatings and less rough surfaces.
Figure 2-4 Plasma spray system [63].
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Since the implant material is not heated during the process, plasma spraying is
termed as a ‘cold’ method, which has the advantage of avoiding metallurgical
change or damage to the implant metal [64]. Furthermore, plasma spraying produces
coatings with good density and strength, and minimized contamination by other
elements during the manufacturing process [64].
Plasma Spray Process Parameters
The properties of plasma spray coatings are affected by as many as 50 process
parameters [65]. These parameters relate to various parts of the spray process. The
major parts are the powder, the powder injector, the plasma torch, the plasma flame
itself and the substrate. Among these processing parameters, there are some that
can be controlled directly, called ‘primary parameters’, and others called ‘secondary
parameters’ which cannot be controlled directly and depend on the primary
parameters. The most important primary and secondary parameters are listed in
Table 2-6.
Table 2-6 Primary and secondary parameters [22].
Primary parameters Secondary parameters
Powder particle morphology Plasma flame temperature Powder particle composition Plasma flame velocity
Powder injection angle Dwell time in plasma flame Plasma forming gas Particle velocity
Plasma forming gas flow rate Particle melting Current Substrate temperature Power Particle quench rate
Carrier gas Residual stress development Carrier gas flow rate Coating thickness Stand-off distance Substrate material
Substrate surface properties Substrate pre-heating
Traverse velocity
In order to produce the desired coatings, it is necessary to understand the
process parameters because these affect the resultant coatings. The main
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parameters of the plasma spray process are: power, plasma forming gas, carrier
gas, powder feed rate, stand-off distance, and torch traverse velocity.
Power
Plasma power has major effects on the coatings. To obtain the appropriate
coating, the power of the plasma spray process needs to be appropriate so that it
can melt the powder properly. Power is equal to current multiplied by voltage and so
current is proportional to power. The typical current values used for spraying HA
coatings are in the range of 350 A to 1,000 A.
Cizek et al. [66] and Guessama et al. [67] studied the effect of power on the
temperature of the plasma flame velocity of the particle. They reported that a high
current or power level caused an increase in particle temperature and velocity. Cizek
et al. [66] found that high power levels result in an increased flame temperature that
causes a greater degree of particle melting. Increasing the power level was also
found to cause an increase in the velocity of the plasma flame.
A net power increase of 10 kW was observed to cause an increase of 80 ºC in
particle temperature and an increase of 60 ms-1 in particle velocity. Increased power
lead to a decrease in the purity and crystallinity of HA coatings, as demonstrated by
Tsui et al. [68] and Sun et al. [69]. The findings of Yang et al. [70] contradicted these
findings [68, 69] where crystallinity increased with increasing current. Tsui et al. [68]
reported that the porosity level and extent of microcracking decreased with an
increase in power. Quek et al. [71] demonstrated that dense, less porous coatings
evolved when high currents were employed.
Plasma forming gas
The plasma forming gas has a major role in the coating properties. The major
component of the gas mixture is known as ‘primary gas’ and the minor component is
known as ‘secondary gas’. There are four main gases used in plasma spray
processes: argon, helium, hydrogen, and nitrogen. The choice of the plasma gas
depends on many factors, such as the design features of the torch, in particular the
electrode materials [72].
However, argon is used as the primary gas because it is cheap, easily ionised
and has inert properties. Argon, when used in the plasma flame increases the
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velocity from 600 ms-1 to 2,200 ms-1 as reported by Fauchais et al. [73]. Helium is
used only in special cases because it is an expensive gas, but it produces a high
temperature plasma flame, density and enthalpy. Nitrogen and hydrogen are
diatomic gases that result in a plasma jet with higher thermal conductivity than
monatomic argon and helium plasma gases. Leung et al. [74] reported that the size
and shape of the jet and the momentum that the carrier gas imparts on the powder
particles vary depending on the gases used.
Plasma gas flow rate and power to the plasma torch must be balanced or
optimised to obtain a stable plasma flame. Gas flow rate has a direct effect on
particle velocity, since increasing the gas flow rate during spraying leads to an
increase in particle velocity, as reported by Guessasma et al. [67]. The latter [67]
also demonstrated that increasing the gas flow rate from 30 to 50 standard litres per
minute (slpm) resulted in an increase in the average particle velocity from 186 to
269ms-1 and also a slight increase in particle temperature from 2,516±131 ºC to
2,526±203 ºC. These results differ from the Cizek et al. [66] who reported no
significant change in particle temperature with an increase in gas flow rate.
Carrier gas
The carrier gas carries the powder into the plasma torch and the powder leaving
the torch should pass through the centre of the plasma jet as much as possible
because this is the hottest part of the plasma. When selecting the powder carrier
gas, it is necessary to consider the chemical reactivity of the powder; an inert gas will
prevent chemical changes in the powder particles.
The velocity of the powder carrier gas is also important, particularly when the
powder injector is radial to the plasma flame. A very low flow rate fails to convey the
powder effectively to the plasma jet and a high flow rate may cause the powders to
escape from the hottest region of the jet. In a radial injected plasma torch, the
powder particles are forced into the plasma flame perpendicular to the direction of
the flame. This guides most particles to attain their maximum velocity by being
passed through the hottest part of the plasma that is in the centre of the jet. The
ideal carrier gas flow rate would inject particles into the plasma jet at a momentum
similar to that of the plasma jet.
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Different carrier gases have different particle flow into the plasma jet. Argon is
most commonly used as the carrier gas [75]. Leung et al. [74] found that nitrogen
has a gas momentum value that is 37% greater than that of argon, and for helium
the value was 10% less for the flow rates used compared to argon. The nitrogen
carrier gas achieved the highest radial distance between the trajectory centre of the
particles and the torch axis because it had the highest momentum. Mawdsley et al.
[76] demonstrated that carrier gas flow rate influences the thickness of plasma
sprayed coatings; i.e., high carrier gas flow rates increase coating thickness.
Powder feed rate
To reach the powder in a plasma flame, there is a need for a powder flow rate.
The powder feed rate has two main effects. Firstly, the powder feed rate affects the
coating thickness. If the flow rate increases, that ultimately increases the quantity of
particles and increases the coating thickness. However, a very high flow rate may
give rise to an incomplete melting, resulting in a high amount of porosity in the
coatings. Incomplete melting increases the amount of the unmelted powders that
may bounce off from the substrate surface and keep the deposition efficiency (DE)
low. Secondly, the feed rate affects the temperature of the plasma flame. When the
feed rate increases, it introduces a greater number of particles into the flame, which
reduces flame temperature [22]. According to Cizek et al. [66], the effect of the
powder feed rate on the velocity and temperature of the plasma flame is small.
Stand-off distance (SOD)
The distance between the torch and the substrate is called the ‘spray distance’ or
‘stand-off distance’ (SOD). SOD affects the velocity of the particle and the length of
time that the particles are exposed to the heating effect of the plasma flame; thus
affecting the degree of particle melting that occurs. A longer SOD may cause a
reduction in the velocity of the droplets during spraying due to the frictional forces
from air molecules. A shorter SOD suggests that the substrate experiences more of
the heating effects of the plasma flame. Thus, SOD affects the substrate
temperature [22]. Kweh et al. [77] demonstrated that coating properties deteriorate
with increasing spray distance.
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Sun et al. [69] studied the effects of varying stand-off distance from 80 mm to
160mm and reported that longer spray distances were observed to cause increased
particle melting, lower porosity and a greater number of microcracks. Lu et al. [78]
investigated spray distances of 80-200 mm. They suggested that, at longer spray
distances, the particles begin to cool and resolidify; thereby allowing a coating with
increased crystallinity to be formed. Cizek et al. [66] measured the change in
temperature and velocities as the spray distance increased from 50 to 150 mm. A
decrease in particle temperature of 220 ºC and a decrease in velocity of 90 ms-1
were found over this range.
Traverse velocity
The velocity at which the plasma torch travels is called ‘torch traverse velocity’.
Traverse velocity has an effect on cooling, thickness, recrystallization and residual
stress development [22]. Traverse speeds used for spraying vary greatly; values
ranging from 75 mm/s 750 mm/s [71, 79] have been reported.
High velocity oxygen fuel (HVOF) spray process 2.2.2.
For HA processing, high velocity oxygen fuel (HVOF) spray has been investigated
[80, 81]. This works on the principle of using kinetic and thermal energy for
accelerating powder particles at a nearly supersonic speed with a low flame
temperature of almost 3,000 ºC before their impact onto the substrate [82]. Figure 2-
5 shows a schematic of a typical HVOF gun design.
Figure 2-5 High velocity oxygen fuel (HVOF) apparatus [83].
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This process uses only powder as feedstock, instead of wire or rod. The
feedstock powder is injected into a water cooled high pressure combustion chamber
that has a long barrel (160-200 mm) [84]. HVOF systems have internal combustion
that combust a mixture of fuel (gas or liquid) and oxygen. The fuel gas can be
propane, propylene, acetylene or hydrogen. The gas temperature depends on the
ratio of fuel and oxygen gas flow rate and the choice of fuel gas. The combustion
products are forwarded through a nozzle where they attain supersonic speeds that
can be observed as ‘shock diamonds’ at the exit of the barrel. Powder is fed into the
hot and expanding gas where it is heated and accelerated towards the substrate.
Coatings produced with the HVOF process exhibit dense coatings, excellent
bonding, minimal metallurgical changes, and minimal temperature effects [85].
Microstructure of the HA coatings 2.2.3.
The microstructure of a thermal spray coating depends on the spray parameters
and feedstock particle quality [86]. Coatings are created by several layers of
overlapping splats that are formed from fully or partially molten feedstock particles. A
typical thermal spray microstructure consists of pores, cracks, unmelted particles,
voids, oxides, impurities, intra splat cracks, and horizontal cracks as shown in Fig. 2-
6. The structure of HA coatings deposited by the plasma spray method are shown in
Fig. 2-7.
Figure 2-6 Typical thermal spray coatings with common features [87].
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Figure 2-7 Typical structure of plasma sprayed hydroxyapatite coating (a) top
surface, and (b) cross-section [88, 89].
Splats are the basic building block of thermal spray coatings. The flat, round
shaped splats are approximately 50–60 µm in diameter and 5 µm thick [90]. The
splats consist of grains, which are smaller at the fringe and larger in the centre (up to
5 µm) [90]. Figure 2-8 demonstrates the nano-grained structure of a HA splat. A disc
shaped HA splat with pores is shown in Fig. 2-9.
Figure 2-8 Grains within a HA coating splat [90].
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Figure 2-9 Typical HA splat on metal surface with one big and several smaller
pores[90].
Porosity that forms between splats may be correlated directly to the crystalline HA
phase; i.e., the porosity of HA coatings increases with a larger amount of crystalline
HA phase [91]. This phase differentiation arises because the crystalline HA splats
are less viscous, and therefore flatten less and are slow to cool. Hence, voids
between these splats are not filled by viscous material, which may be differentiated
from the case of an amorphous phase [91]. Furthermore, it was found that the
increase in the less viscous amorphous phase decreases the surface roughness and
hence the coating is more smooth. A larger amount of amorphous phase, therefore,
is responsible for decreasing the coating porosity.
Several authors [92-94] have developed models that describe the manner in
which a single splat may consist of diverse phases. Sun et al. [92] developed a
model concerning the coating formation and the recrystallization of the amorphous
phase, Figure 2-10. This model suggests that during the solidification of the splat
some regions of the amorphous and stoichiometric phase (in between core and
shell) recrystallize due to longer cooling times on the coating surface. Furthermore,
this model considers that subsequent droplets influence the previous layers. That is,
heat from the plasma flame and from the overlapping new droplets melt the outer
sections of the prior-formed splats. This process may lead to recrystallization since
the new splats decrease the cooling rate of the already-deposited splats. Secondly,
while the first-formed splats recrystallize, new OHˉ groups have time to infiltrate
these regions and generate a crystalline phase out of a former amorphous phase.
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Figure 2-10 Coating-development-model [92].
Gross et al. [93] developed a model that indicates that splat phases depend on
the plasma flame temperature, Figure 2-11, since this parameter regulates the
viscosity of the splats and the degree of dehydroxylation. Following this model,
crystalline, not dehydroxylated, hydroxyapatite can be found in the core of droplets
and splats. The amorphous, highly dehydroxylated and fast cooling phase develops
at the metal surface; while oxyapatite, which cools down more slowly, is located near
the outer splat surface. Higher temperatures lead to tri-calcium and tetra-calcium
phosphates, as well as to calcium oxide. Calcium oxide is not desirable due to its
bio-incompatible properties.
Possible phase development inside a lamellae was developed by Deram et al.
[94], Figure 2-12. There are six possible calcium containing compounds known in the
calcium-phosphate system: hydroxyapatite, tri-calcium phosphate, tetra-calcium
phosphate, calcium oxide, calcium pyrophosphate and oxyapatite.
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Figure 2-11 Splat-development-model dependent on plasma flame temperature [93].
Figure 2-12 Possible phase development in half melted HA powder particle [94].
Not every compound appears in HA coatings, since these are controlled by the
spray process and its parameters. The amorphous and the crystalline phases of HA
are dominant, with alpha and/or beta phases of tri-calcium phosphate and tetra-
calcium phosphate often also present. The amorphous HA phase may develop
instead of a crystalline phase due to the rapid solidification conditions during the
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splat quenching process, where cooling rates of 1x106 degrees per second may
exist. Thus, the HA does not have adequate time to crystallize [95, 96].
2.3. Sol-gel process
The sol-gel process is a wet chemical process employed in the manufacture of
ceramic and glass materials. The sol-gel technique allows preparation of ceramic or
glass materials in a wide variety of forms: ultra-fine or spherical shaped powders,
thin film coatings, ceramic fibres, micro porous inorganic membranes, and monolithic
or extremely porous aerogels [97-99]. An overview of the sol-gel process is
illustrated in Fig. 2-13.
A ‘sol’ is a stable suspension of colloidal solid particles or polymers in a liquid;
and ‘gel’ is a porous, three-dimensional, continuous solid network surrounding a
continuous liquid phase [97, 100, 101]. Hence, sol differs from a solution, as a
solution is a single-phase system, whereas a sol is a two-phase, solid-liquid system.
The colloidal solid particles have a size range of approximately 1-1000 nm. The
gravitational forces on these particles are negligible and interactions are dominated
by short-range forces such as van der Waals and surface charges [97].
Figure 2-13 Sol-gel process [102].
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Advantages of sol-gel coatings 2.3.1.
Sol-gel is a unique process that can produce powders, platelets, coatings, fibers
and monoliths of the same composition by varying chemistry, viscosity and other
factors of a given solution. The sol-gel process allows the manufacture of thin
coatings (<10 µm) [103]. The advantages of sol-gel coatings are [101, 104, 105]:
• Low process temperature.
• Low cost.
• Ability to control the composition on molecular scale.
• Homogeneous coatings.
• Possibility to synthesize composition materials.
• High purity products.
• Ability to coat complex shapes.
• Ability to use various chemical routes.
• Shrinkage up to a certain number of coatings.
• Rapid drying of coatings without cracking
Sol-gel chemistry 2.3.2.
The sol-gel process involves the controlled hydrolysis of dissolved metal organic
precursors followed by a polycondensation reaction, resulting in the formation of a
three dimensional network of particles [106, 107]. The hydrolysis takes place using a
small amount of water. In the hydrolysis reaction, the alkoxide groups are replaced
stepwise by hydroxyl groups (OH):
Polycondensation reactions occur simultaneously with the hydrolysis [106].
(6)
(7)
M OR + HOH M OH + ROH
M OH+ M OH M O M + HOH
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Sol-gel coating techniques 2.3.3.
There are two main types of sol-gel coating techniques [101, 106].
• Dip coating and
• Spin coating
Dip Coating
The dip coating is an inexpensive and rapid method for producing thin
homogenous coatings. The dip-coating technique can be described as a film
deposition process. In this technique, the substrate to be coated is immersed in a
liquid and then withdrawn at a well-defined speed under controlled temperature and
atmospheric conditions [101, 106]. The schematics of the dip coating process are
shown in Fig. 2-14.
The dip coating thickness depends on the solid content, the withdrawal speed,
and the viscosity of the liquid [106, 108]. If the withdrawal speed is chosen such that
the sheer rates keep the system in the Newtonian regime, then the coating thickness
can be calculated by the Landau-Levich equation [109]:
2/3
1/6 1/2LV
0.94 ( v)h = ( g)η
γ ρ (9)
where, h = coating thickness η = viscosity v = substrate speed
LVγ = liquid vapour surface tension ρ = density g = gravity
(8)
M OH + M OR M O M + ROH
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Figure 2-14 Stages of the dip coating process (a) dipping of the substrate into
coating layer formation, (b) wet layer formation by withdrawing the substrate, and (c)
gelation of the layer by solvent evaporation [110].
Spin coating
Spin coating has been used for several decades for the application of thin films.
Spin coating is a process suited to flat shapes, such as disks, plates and lenses. In
this technique, a small amount of solution needs to be placed onto the centre of the
substrate and then the substrate is spun at high speed (typically around 3000 rpm) in
order to spread the fluid by centrifugal force. The rotation is continued while the fluid
spins off the edges of the substrate, until the desired thickness of the coating is
achieved. A separate drying step is added after the high speed spin to dry the
coating without substantially thinning it. The thickness of the coating depends on the
nature of the fluid and the parameters chosen for the spin process. The coating
thickness varies between several hundreds of nanometres to ten micrometres. The
schematics of the spin coating process are shown in Fig. 2-15.
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Figure 2-15 Stages of the spin coating process (a) placing small amount of solution
on the substrate, (b) rotating the substrate at high speed, and (c) drying the film[111].
Sol-gel HA coatings 2.3.4.
Sol-gel processing is widely used for depositing HA due to its low cost and
convenient technique. Weng et al. [112] prepared sol-gel HA coatings on an alumina
substrate and reported that the coating obtained at 500 ºC showed good crystallinity,
adhesive strength, and dense morphology. Hsieh et al. [113] deposited HA coatings
onto a Ti-6Al-4V substrate using sol-gel processing with rapid heating. A porous
structure was reported on the outermost coating surface, with a pore size of 10-
20µm. This structure, which is beneficial for the in-growth of living cells, arose due to
the fast decomposition during rapid heating.
Dense HA coatings were deposited onto a stainless steel substrate using sol-gel
processing upon heat treatment of 375-500 ºC by Liu et al. [114]. Zhang et al. [115]
prepared uniform HA coatings on NiTi alloy via dip coating using a sol-gel procedure.
They reported that sol-gel HA coatings formed on the surface of a porous NiTi alloy
substrate, as well as inside the pores.
2.4. Optimization of HA coatings
The plasma spray process has many variable parameters and it is important to
optimise parameters to obtain quality coatings. Plasma spray process parameters
may be optimised in a trial and error method, which is time consuming and inefficient
use of resources. However, for superior coatings, it is necessary to understand the
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scientific phenomena involved in the plasma spray process. Design of experiment
(DOE) methods are a suitable technique that provides a maximum amount of
information with the minimum number of experiments. The benefits of statistical
design of experiments have been demonstrated by researchers in studies of plasma
sprayed coatings for various materials such as zirconia [116], titanium nitride [117],
alumina [76] and alumina-titania [118]. Recently, statistical design of experiments
has been employed used by Dyshlovenko et al. [119, 120], Cizek et al. [66] and
Tanay et al. [22] for plasma sprayed hydroxyapatite coatings.
Design of experiments (DOE) 2.4.1.
The statistical experiment approach is usually called ‘design of experiment’
(DOE). The DOE method was introduced by Sir R. A. Fisher in the early 1920’s[121].
Fisher developed a method to carry out agricultural experiments in which the effects
of properties, such as fertiliser, sunshine, and rain on a crop were determined.
Further improvements in the DOE technique were brought about by Dr. Genechi
Taguchi in the 1940’s [121]. A number of special orthogonal arrays were introduced
that made the implementation of DOE easier. The DOE method has been applied
across a wide range of disciplines since the 1920’s [22].
In the DOE technique, the parameters to be changed in the experiment are
termed ‘factors’ or ‘variables’ [122]. The different possibilities for a factor are called
the ‘levels’. Levels can be either qualitative or quantitative. The measured output
from the experiment is termed the ‘response’. Once the experiment has been run,
the effect of each factor can be evaluated by comparing the average response
change with the factor changed. Responses can then be represented as a
polynomial regression equation of the following form:
0 j j ij i j ijk i j ky b b X b X X b X X X= + + +∑ ∑ ∑ (10)
where i, j and k vary from 1 to the number of variables; coefficient 0b is the mean
of the responses of all the experiment; the jb coefficient represents the effect of the
variable jX and ijb and ijkb are the coefficients of regression that represent the
effects of the interactions of variable i jX X and i j kX X X respectively [22].
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In performing a designed experiment, there is a need for input process or
machine variables to observe corresponding changes in the output process. The
information gained from such experiments can be used to improve the performance
of products. Figure 2-16 shows the general model of a process/system.
Figure 2-16 General model of a process/system [123].
In every process there are some variables or factors that can be controlled easily,
and some that are hard to control during normal production or standard conditions. In
Fig. 2-16 outputs are performance characteristics that are measured to assess the
process/product performance. During an experiment controllable variables can be
varied easily and such variables have key roles to play in the process
characterization. Uncontrollable variables, with small effects on process
characterization, are difficult to control during an experiment. It is important to
determine optimal settings of controllable variables to minimize the effect of
uncontrollable variables [123].
Factors, levels and responses represent three aspects of design analysed by a
design of experiment, as shown in Fig. 2-17. Factors (such as power, powder feed
rate, stand-off distance) can be either controllable or uncontrollable variables. Levels
include the settings of parameters. In this case, coatings are potentially influenced by
the factors and their respective levels. Experiments are often designed in such a way
as to avoid optimizing the process for one response at the expense of another.
Based on this, the design of experiment technique can be shown as a flowchart as
shown in Fig. 2-18.
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Figure 2-17 Coatings build up.
Figure 2-18 Steps of design of experiment [124].
A number of different DOE methods have been developed, including factorial
experiments and fractional factorial experiments, response surface methodology
techniques, such as the central composite design and the Box-Behnken design, and
Taguchi orthogonal arrays. The method selected for a particular experiment depends
on considerations such as the objectives of the experiment, the number of factors
being investigated and the resources available. The potential application of DOE in
manufacturing processes includes [120]:
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• Improved process yield, stability and capability.
• Improved process net profits and return on investment.
• Reduced process variability and improved product performance.
• Reduced process design and development time that will ultimately reduce
the manufacturing costs.
• Development of a relationship between key process inputs and output(s).
Industrial experiments involve a sequence of activities [123], such as:
• Hypothesis: An assumption of responses and factors that motivates the
experiment.
• Experiment: Identification required number of tests to investigate the
hypothesis. Carrying out a number of identification tests to investigate the
hypothesis.
• Analysis: Understanding the nature of data and performing statistical
analysis of the data collected.
• Interpretation: Understanding the results of the experimental analysis.
• Conclusion: Determining, whether or not the originally set hypothesis is true
or false.
Importance of design of experiments 2.4.2.
A conventional way to optimise a process is to change one factor at a time and
check the response. This process consumes time and needs many experiments.
Thus, there is a need for a process that can evaluate the effect of each factor on the
resultant response with only a few experiments. Design of experiment fulfils this
requirement. It can give much more information from a small number of experiments.
Factorial and fractional factorial experiments 2.4.3.
In a full factorial experiment, factors and levels are first identified and then all
possible combinations of the levels of the factors are investigated. There can be a
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wide range of factors, but limited factors are preferable, because a large number of
factors increases the number of experiments to be conducted which is undesirable.
Two-level full factorial experiments are the most common. In this type of experiment,
factors are set at a low level (coded -1) and a high level (coded +1). A two level
experiment with k factors is called a 2k experiment. For example, a 23 experiment is
used to study three factors at two levels and consists of 8 experiments. The design
for a 23 experiment is shown in Table 2-7.
Table 2-7 A 3 factor, 2 level factorial experiments [123].
Run X1 X2 X3
1 -1 -1 -1
2 1 -1 -1
3 -1 1 -1
4 1 1 -1
5 -1 -1 1
6 1 -1 1
7 -1 1 1
8 1 1 1
When carrying out experiments, there are some factors that have very little effect
on the results and these types of factors need to be excluded from the experiment.
Also, some factors may exist that are not of primary interest but still affect the
results; these factors need to be eliminated. The effect of these factors can be
eliminated from the overall results by organising the experiment into blocks. The
effects of uncontrolled factors and unblocked factors can be eliminated by running
the experiments in random order.
Centre points are also usually added to factorial designs. These points are the
centre value between the high (+1) and low (-1) values selected for each factor and
are coded 0. The purpose of centre points is to allow process stability to be
determined. Generally, between 3 and 6 centre points are added to an experiment
design [22].
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Full factorial experiments are very efficient for a small number of factors. For a
large number of factors, a fractional factorial is more efficient than a full series
because it reduces the number of experiments. The reduction of experiments can be
achieved by confounding the effects of some of the factors. However, due to the high
order, interactions between factors cannot be estimated. This type of experiment is
used to obtain information on the main effects as well as on low-order interactions
and is also often used for screening designs [22, 123].
Fractional factorial design involves fewer experiments than the full 2k run of
experiments. A fraction of the number of runs is required for such an experiment;
such as 1/2, 1/4, 1/6, 1/8 etc. The general term used for a fractional factorial design
is 2k-m, a 1/2 fractional factorial experiment is termed a 2k-1 experiment, and a ¼ is a
2k-2. A 25-2, i.e., 1/4 fractional factorial matrix is given in Table 2-8.
Table 2-8 A 5 factor, 2 level fractional factorial experiments [22, 123].
Taguchi orthogonal arrays 2.4.4.
Orthogonal arrays are used to study combinations of factors in the presence of
noise factors. Signal to noise (S/N) ratios are calculated and used to make decisions
about optimal parameter settings for each combination. Orthogonal arrays are
helpful to minimize the number of runs needed for the experiment. Orthogonal arrays
are optimized based on the signal to noise ratio. Signal to noise ratio is a metric term
used to determine the magnitude of true output after making some adjustment for
uncontrollable variation [125]. The S/N ratio is the ratio of energy that is transformed
into the intended output to transform it into the unintended output.
Run X1 X2 X3 X4= X1X2 X5 = X1X3 1 -1 -1 -1 1 1 2 1 -1 -1 -1 -1 3 -1 1 -1 -1 1 4 1 1 -1 1 -1 5 -1 -1 1 1 -1 6 1 -1 1 -1 1 7 -1 1 1 -1 -1 8 1 1 1 1 1
Confounding
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Power of SignalS Ratio = N Power of Noise (11)
There are 3 types of signal to noise ratio used in orthogonal arrays.
(a) Type 1. Smaller the better: the response is continuous and positive. The most
desired value is zero [126].
n2i
i=1
1S = -10log( y )N n∑ (12)
where iy is represented by a set of characteristic of 1y , 2y , 3y ,……… ny .
(b) Type 2. Nominal the best: the response is continuous and it has a non-extreme
target response [126].
2yS 10log( )N V
= (13)
where y is the average of a set of characteristics 1y , 2y , 3y ,……… ny and V is the
variance of data.
(c) Type 3. Larger the better: this is the case for a continuous response, where the
response needs to be maximum [126].
n
2i 1 i
1 1S 10log( )N n y=
= − ∑ (14)
where iy is represented by a set of characteristics of 1y , 2y , 3y ,……… ny .
Response surface methodology 2.4.5.
Response surface methodology is a statistical technique used for developing,
optimizing and improving complex processes. It is a useful technique to minimize or
maximise a response in a certain region. The two most popular response surface
methodologies are a central composite design and the Box-Behnken design.
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Central composite design (CCD):
A central composite design (CCD) is a technique for factorial or fractional factorial
design. Figure 2-19 shows the central composite design.
Figure 2-19 Central composite design with cube points, star points and centre
points[22].
A CCD design consists of three types of experiments [22]:
• Cube samples: these are the experiments that cross lower and upper
levels of the design variables. They are the ‘factorial’ or ‘fractional’ part of the
design.
• Centre samples: these are the replicates of the experiment that cross
the mid-levels of all design variables. They are usually used to determine the
experimental error of the design.
• Star (or axial) samples: these are used to make the design region
spherical and are located at the midpoints of the ‘faces’ of the factorial part of
the design that are specific to CCD designs.
The design matrix of a central composite design can be shown as follows [22]:
BA = C
D
(15)
B is either a 2k factorial or 2k-m fractional factorial experiment, where k is the
number of factors and m is the number of factors that are confounded. C is a matrix
with 2k rows, where all of the factors are set to 0, except one factor, which is placed
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41 | P a g e Author: Md. Fahad Hasan
at the star point or axial point. The distance from the centre of the design space to
the star point is ±α. The value of α depends on the type of centre composite design
being used and also on the number of factors under investigation. The value of α can
be calculated as follows [22]:
14α = (2K) (16)
DOE for plasma sprayed HA coatings 2.4.6.
Heimann et al. [36] studied the DOE method for optimum surface roughness,
porosity, and tensile adhesion strength. Dyshlovenko et al. [119] used the DOE
technique to examine the plasma spray preoaration of HA, and, later, a laser post
spray treatment process.
In another study, Dyshlovenko et al. [120] used a factorial design to investigate
the relationship between plasma spray parameters and the microstructure of HA
coatings. In their study, three responses were examined: (i) the fraction of HA, (ii) the
fraction of decomposition phases, and (iii) the amorphous content of the coatings.
Dyshlovenko et al. [119, 120] used the DOE technique for a small number of factors.
Levingstone et al. [22] used response surface methodology to study the effect of five
plasma spray process parameters (current, gas flow rate, carrier gas flow rate,
powder feed rate, and stand-off distance) to optimise the coatings with respect to
responses such as crystallinity, purity, surface roughness, and porosity. Table 2-9
shows previous DOE studies that concern in plasma sprayed hydroxyapatite
coatings.
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Table 2-9 Summary of DOE studies done on plasma sprayed HA coatings.
Author Type of DOE Description Factors Responses
Cizek [66] Taguchi
• 6 factors;
• 3 levels;
• 2 responses;
• 18 experiments;
• Power input;
• Primary gas flow rate;
• Secondary gas flow rate;
• Carrier gas flow rate;
• Powder feed rate;
• Stand-off distance;
• Temperature;
• Velocity;
Dyshlovenko [120]
24 factorial design of
experiment
• 4 factors;
• 2 levels;
• 3 responses;
• 16 experiments;
• Ar content of main gas flow;
• H2 content of gas flow;
• Power;
• Spray distance;
• Fraction of HA phase;
• Fraction decomposition phase;
• Fraction amorphous phase;
Dyshlovenko [119]
24 factorial design of
experiment
• 4 factors;
• 2 levels;
• 3 responses;
• 16 experiments;
• Electric power;
• Ar content of main gas flow;
• Carrier gas flow;
• Laser power density;
• %HA;
• %α-TCP;
• %TTCP;
• Depth of Laser melt zone;
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2.5. Indentation techniques
Indentation techniques are used to determine hardness. Hardness is defined as
the ratio of applied force to contact surface area or alternatively it is defined as the
resistance to indentation. Hardness is a characteristic of materials, not a
fundamental physical property. A smaller indentation indicates that the material is
hard. A hardness value is obtained by measuring the area of indentation or depth of
indentation. Researchers have proposed some modified microhardness techniques
but the principle of the technique has remained the same.
There are three main approaches for measuring hardness: scratch, rebound or
dynamic, and indentation techniques. Among all these techniques, indentation is the
most widely used method for measuring microhardness. In this technique, an
indenter is pressed into the desired sample surface to be tested with a desired load
and a microhardness measurement is made based on the size of indent area or
depth of indent area. Typically, the indenter is made of hard steel, tungsten carbide,
Levingstone [22]
Response surface
methodology
• 5 factors;
• 2 levels;
• 5 responses;
• 31 experiments;
• Current;
• Gas flow rate;
• Powder feed rate;
• Stand-off distance;
• Carrier gas flow rate;
• Crystallinity;
• Porosity;
• Roughness;
• Thickness;
• Purity;
Heimann [36]
Response surface
methodology
• 5 factors;
• 2 levels;
• 4 responses;
• 28 experiments;
• Power;
• Primary gas flow rate;
• Secondary gas flow rate;
• Carrier gas flow rate;
• Spray distance;
• Thickness;
• Adhesion strength;
• Porosity;
• Roughness;
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or diamond in the shape of a sphere, cone or pyramid. The Brinell, Meyer, Rockwell,
Vickers and Knoop hardness tests are examples of the indentation method.
Brinell hardness test 2.5.1.
In 1900, Dr. Johan August Brinell, a Swedish engineer, invented the Brinell
hardness test, which is the oldest hardness technique. It is commonly used for
materials that have too coarse a structure or too rough a surface; e.g., castings and
forgings. It is mostly used on large parts. Brinell hardness results are measured by
the permanent width of indentation created by the carbide or tool steel indenter with
a specific load and time period onto a test specimen. An indentation is typically made
with a Brinell hardness testing machine and then the indentation diameter is
measured using an optical microscope. The measurement is converted to a Brinell
value using the following formula [127]:
2 2
2PBH = πD(D- D -d )
(17)
where D is the ball diameter in mm, d is the impression diameter in mm, P is the
load in kgf, and BH is the Brinell hardness number. Figure 2-20 shows the Brinell
hardness testing technique.
Figure 2-20 Brinell hardness testing [127].
The Brinell test typically uses a load of 3000 kgf and a ball with diameter of
10mm. Test loads can vary in the range of 500 kgf to 1 kgf. Ball diameter can vary in
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the range of 10 mm to 1 mm. For a soft material such as aluminium, the test is
performed with a 500 kgf load or 1500 kgf and a 10 mm ball is used to avoid
excessive indentation [128]. Lower loads and ball diameters are normally used for
convenience in ‘combination’ testers. Brinell tests are defined in ASTM E10 [129]
and ISO 6506-1 [130] standards. The test standard suggests a dwell time of 10-15 s.
The specimen should be about 4 times wider than the diameter of the impression.
Also, the thickness of the specimen should be at least 15 times the depth of the
indentation for softer metals and 10 times the depth of the indentation for hard
metals [131].
A Brinell hardness number is expressed as ‘75 BH 10/3000/15’, which indicates
that a Brinell hardness of 75 was obtained with a 10 mm diameter ball using a 3000
kgf applied load for a period of 15 seconds. Brinell hardness tests are less influenced
by surface scratches and roughness. The main source of error in Brinell testing is the
measurement of indentation. The results may vary under perfect conditions due to
operator errors and inconsistencies [127].
Meyer hardness test 2.5.2.
In 1908, Meyer proposed that hardness should be expressed in terms of mean
pressure between the surface of the indenter and the indentation [132]. His proposal
can be explained as the load divided by the projected area of the indentation.
Meyer Hardness can be expressed using the following formula [132]:
2
4PMH = πd
(18)
where d is the diameter of resultant indentation in mm, and P is the applied load
in kgf.
The sensitivity of the Meyer hardness test is less compared to the Brinell
hardness test. Meyer hardness follows a more fundamental measure of indentation
hardness but its uses in practical fields are rare.
Rockwell hardness test 2.5.3.
The Rockwell hardness test was invented by Stanley P. Rockwell in 1919. It is the
most popular method for a hardness test since it overcomes the limitations of
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previous methods. In this method, indentations are made on the test material with a
diamond cone or hardened steel ball indenter. Figure 2-21 shows the working
principle of the Rockwell hardness test.
A preliminary minor load (F0), usually 10 kgf, is applied to all the test material
using an indenter. This load represents the reference or zero position. An additional
load, named the ‘major load’ (F1), is applied with the ‘preload’ or ‘minor load’ (F0), to
reach the total required test load (F). These loads are held for a certain dwell time to
allow for elastic recovery. Then, the additional major load is removed but the preload
is still retained. Then, the Rockwell hardness (HR) number is calculated using the
equation below [133]:
HR = E-e (19)
where e is the indentation depth created by the minor load and E is indentation
depth created by the major load.
Figure 2-21 Rockwell working principle [133].
Rockwell hardness has no units and is normally expressed in 30 different scales
(A, B, C, D etc). The most widely used scales are B and C scales for testing brass,
steel and other metals. Rockwell hardness is expressed as ‘60 HRB’ which indicates
that the specimen has a hardness reading of 60 on the B scale. The hardness of
hard plastics (nylon, polycarbonate, polystyrene, and acetal) is most commonly
measured using the Rockwell hardness test [134]. The following standards are
defined by the Rockwell hardness test: ASTM D785 plastics [135], ASTM E18 metals
[136], and ISO 6508-1 metals [137].
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Vickers hardness test 2.5.4.
In 1925, the Vickers test was developed in England by Vickers Ltd [138]. It is also
known as the Diamond Pyramid Hardness Test. This method is the most commonly
used technique. In this method, tested materials are indented using a diamond
indenter in the form of a right pyramid with a square base and an angle of 136º angle
between opposite faces, Figure 2-22.
It covers force ranges of micro load (10 gf to 1000 gf) and macro load (1 kgf to
100kgf) using the same indenter shape for both of these ranges. It is useful for
testing many materials as long as the samples are prepared carefully. It is useful for
a variety of applications, such as: testing small parts or small areas, measuring the
surface of a part, testing thin materials such as foils, measuring individual
microstructures, measuring the depth of case hardening by sectioning a part, and
making a series of indentations to describe a change of hardness.
Figure 2-22 Vickers hardness testing [139].
The Vickers testing method is similar to the Brinell test. It uses a penetrator that is
square in shape, but tipped in one corner, so that it has the appearance of a playing
card ‘diamond’ rather than using the ‘Brinell’ steel ball-type indenter and calculating
the hemispherical area of impression in the Brinell hardness test. The indenter was
suggested by Smith et al. [140].
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Sample preparation is important for this test to provide a small sample that can fit
into the tester. The sample tested surface needs to be smooth since the
measurement system is optically based. The indentation should be large enough to
maximize the measurement resolution. Error percentages decrease with an increase
in indentation sizes. In this test, vertical and horizontal axes are measured after
indentation. Then, this measurement is converted to a Vickers hardness number,
using the following formula [141, 142]:
2
PVH = 1.8544 d
(20)
where d is the arithmetic mean of two diagonals d1 and d2 in mm, P is the applied
force in kgf, and VHN is the Vickers hardness number.
The Vickers test is a non-destructive technique; however, the test is slow. The
Vickers test methods are defined in the following standards: ASTM E384 (micro
force ranges: 10 g to 1 kg) [143], ASTM E92 (macro force ranges: 1 kg to 100 kg)
[144] and ISO 6507-1 (micro and macro ranges) [138, 145].
Knoop hardness test 2.5.5.
The Knoop hardness test was developed by the National Bureau of Standards
(NIST) in 1939. The test load varies from 10 g to 1000 g. It is mostly used for
sections, small parts, and case depth work. Figure 2-23 shows Knoop hardness
testing with a pyramid-shaped indenter, which is more elongated than the indenter
used on the Vickers test. The long side faces are set at a 172º30ˊ angle to one
another. The short side faces are set at a 130º angle to one another. In this test, only
the long axis is measured, rather than measuring the vertical and horizontal axes, as
in the Vickers test. Then, this measurement is converted to a Knoop hardness
number using the following formula [146, 147]:
2
PKH = 1.4229 L
(21)
where L is the measured length of the long diagonal of the indentation in mm, and
P is the applied load in kgf.
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For a given material and load, the Knoop indenter may penetrate approximately
half as much, and the diagonal dimension may be 3 times higher as that achieved by
the Vickers indenter [148].
A high magnification is required in the Knoop test to dictate and measure the
Knoop indents on a highly polished surface. Samples are normally mounted and
polished to achieve this surface. Therefore, the Knoop test can be considered as a
destructive test. The Knoop test allows the hardness testing of brittle materials such
as ceramics and glass. The test values are mostly load independent over 100 gf.
The hardness testing can take 30 seconds. This test method is well defined in ASTM
E384 [143] and ASTM D1474 (hardness of organic coatings) standards [149, 150].
Figure 2-23 Knoop hardness testing [149].
Leeb hardness test 2.5.6.
The Leeb is the modern electronic version of the Scleroscope. It is also known as
an Equotip. A carbide ball hammer with a spring is used in this test. The velocity of
the hammer is measured by an electronic sensor. The hammer travels towards and
away from the surface of the sample. The Leeb value can be expressed as
follows[151]:
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Hammer rebound velocityImpact velocity 1000Leeb value = × (22)
The Leeb hardness values are in the range of 0 to 1000 and can be converted to
other hardness scales such as Rockwell and Vickers numbers. A wide range of
materials can be tested using this hardness test. However, the tested parts must
have a good finish and a minimum weight of 5 kg. It is portable and can be used at
different angles as long as they are perpendicular to the test surface. The Leeb test
methods are well defined by ASTM A956 standard [152].
Microhardness study on thermal spray coatings 2.5.7.
Thermal spray coatings are widely used in various industrial sectors, such as in
agricultural implements; automotive; aerospace; primary metals; mining; chemicals
and plastics; paper; oil and gas production; and biomedical applications [153-155].
For these applications, the quality of the coatings is of prime importance. Also
microhardness techniques are the key and most suitable technique to determine the
quality of coatings for a certain application [156]. Microhardness is the major
qualitative technique used for characterizing thermal spray coatings. It has also been
used for optimizing spray parameters [157-159]. It has provided a convenient means
for clients to compare the coatings sprayed with different techniques. It is also useful
for quick estimations for the strength of coatings [160].
Lin et al. [142] reported microhardness variations in thermal spray coatings with
respect to applied load and measurement direction, using Vickers indentation to
understand and delineate the hardness and its relationship with the microstructure of
the coatings. They reported a bimodal distribution for small loads in coatings of
metal-metal mixtures. Their studies indicated that the large load reflected small
average microhardness and large Weibull modulus.
Lima et al. [161] analysed the distribution of hardness for HVOF sprayed titania
coatings using Vickers indentation. They reported near-isotropic behaviour for a
plasma sprayed titania coating, and that the origin of this near isotropy could be due
to the characteristics of the HVOF process. Their investigations also summarised a
high Weibull modulus for titania coatings compared to other coatings, due to the
following factors: narrow particle size distribution selection, the HVOF process,
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uniform particle temperature, non-lamellar uniform microstructure, and a near single-
phase coating.
Their results indicated that top surface microhardness is higher compared to the
cross-section. These differences arise since thermal spray coatings are formed by a
successive overlapping of splats, and the resulting complex microstructure is
expected to have different features when examined in top surface and cross-section
orientations. The recommendation of engineering literature on thermal spray
coatings is that the hardness values measured on the cross-section should not be
compared with the top surface values, due to the anisotropic characteristics of the
coatings [61].
Figure 2-24 shows the homogeneous structure of the top surface and cross-
section of HVOF titania coatings. Buchman et al. [162] investigated the
microstructure of HVOF and air plasma spray (APS) titania coatings and concluded
that the top surface and cross-section of HVOF coatings exhibited a homogeneous
microstructure, whereas APS titania coatings revealed a heterogeneous
microstructure.
Figure 2-24 HVOF titania coatings (a) top surface, and (b) cross-section [162].
Microhardness variation of alumina coatings with the change of indent location,
measurement direction, and applied loads were studied and analysed statistically by
Yin et al. [163]. They examined the hardness distribution with change of indent
location throughout the coating cross-section under an applied load of 50 gf. Their
results showed that microhardness data varied within the coatings and the measured
microhardness data set follows Weibull distributions. Microhardness values were
higher on the cross-section than the top surface. The decrease of microhardness
value with the increase of applied load was explained in terms of the Kick’s law and
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the Meyer’s index k of 1.93. The Weibull modulus value indicates that microhardness
data are less variable on the cross-section of a coating at higher load.
To assess the engineering reliability of a coating system, statistical analysis is a
very popular technique. Valente et al. [156] used statistical analysis (Student’s t-test,
Fisher’s test, Gaussian distributions, Weibull distributions, and Meyer’s theory) to
assess the heterogeneity of thermal sprayed ceramic (WC-12%Co) and metallic (Ti-
6Al-4V, CoNiCrAlY) coatings under three different loads (100, 300, and 500 gf). They
reported that ceramic coatings show load-hardness dependence due to their brittle
nature; whereas metallic coatings show a bimodal distribution at small loads. Lin et
al. [164] also used statistical analysis (Gaussian and Weibull distributions) to
characterize thermal spray coatings of NiCoCrAlY bond coat and cerium-stabilised
zirconia.
Vickers hardness distribution on WC-12%Co thermal spray coatings was
analysed by Factor et al. [165]. They analysed the microhardness data using
Gaussian and Weibull statistical models. They concluded that Weibull statistics are
more generally appropriate than Gaussian distributions for the heterogeneous
thermal spray coatings. They concluded that a true population average is required
for the microhardness data, since microhardness data show wide scatter that are
difficult to assess on the basis of the mean microhardness value. Therefore, they
suggested a Student’s t-test and analysis of variance (ANOVA) test for the
comparison of microhardness data sets.
In another study, Factor et al. [166] examined the between-operator
reproducibility of microhardness statistics using Vickers indentation. They used eight
different personnel to check the between-operator reproducibility. They summarised
microhardness readings performed by different operators by means of ANOVA
analysis and concluded that there is a consistent, statistically significant variation. To
overcome operator caused repeatability, they suggested the methods listed below:
• Measuring hardness under increased load.
• Addition of correction factor.
• Measurement based on automated system image analysis.
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• Use of near-field microscopy, confocal microscopy and atomic force
microscopy.
• Measurement using scanning electron microscopy (SEM) with high
magnification.
• Use of Knoop indentation under increased load.
• Ultrasonic microhardness testing.
• Scanning microhardness (depth analysis).
• Other technique such as superficial Rockwell A indentation, Hardel’s large
spherical probe-minimal penetration indentation procedure, instrumented
scratch testing.
The Knoop indentation technique is used widely to investigate microhardness as
well as the elastic modulus of thermal spray coatings. Lima et al. [167] examined the
Knoop microhardness distributions for nanostructured partially stabilized zirconia
(PSZ) coatings, and analysed the distributions using Weibull statistics. The
microhardness data of the nanostructured PSZ coating presents bimodal
distributions in Weibull plots, whereas conventional PSZ coatings exhibit mono-
modal distributions, as shown in Fig. 2-25.
Figure 2-25 Comparison of Weibull plots of (a) conventional PSZ coatings, and (b)
nanostructured PSZ coatings [167].
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Bimodal distributions for nanostructured PSZ coatings indicates two phases that
could be molten and non-molten. These two phases arise due to the nucleation rates
and rapid cooling rates of molten thermal spray particles [168, 169]. Microhardness
data were measured on the molten region and non-molten region. The predicted
microhardness shows good agreement with the measured microhardness. The
microhardness was predicted from the following rule of mixtures formula:
1 1 2 2Predicted Microhardness = H f + H f (23)
where f1 and f2 are the percentages (fractions) of the non-molten and molten
region in the overall coating microstructure; and H1 and H2 are the microhardness
values of the non-molten and molten regions.
Knoop microhardness and elastic modulus were examined by Li et al. [170] for
plasma sprayed Cr3C2-NiCr coatings. The effects of the coating process, indenter
loads, and measurement directions were considered for investigation; and statistical
analyses were carried out to describe the results. Their results indicated that Knoop
microhardness values were lower when the major diagonal of the indenter was
parallel to the interlamellar boundary of the coatings, compared to the vertical
position of the major diagonal. Their elastic modulus data were much more scattered
compared to the microhardness data since the elastic modulus measurement
contained systematic errors.
Elastic modulus was also examined by Leigh et al. [147] using Knoop indentation
for a variety of thermal spray coatings such as (i) alumina (Al2O3), (ii) yttria-stabilised
zirconia (YSZ), and (iii) metallic, intermatilcs, and cermet (NiAl) coatings. They
reported that the elastic modulus of thermal spray deposits was in the range of 12-
78% of the comparable bulk materials and revealed the anisotropic character of
thermal spray deposits. The APS-processed deposits exhibited much lower elastic
modulus values than the vacuum plasma spray (VPS)-processed deposits, due to
the lower porosity, a lower oxidation (for metallic deposits), and the relatively denser
intersplat boundaries of VPS-processed coatings. The elastic modulus values were
changed after heat treatments that were associated with microstructural changes in
porosity, pore morphology, and interlamellar structures.
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Errors in microhardness testing for thermal spray coatings 2.5.8.
The accuracy of the microhardness test depends on many factors, such as
flatness, surface finish, specimen dimension, operator error, and calibration error.
Among these, flatness is the most important factor and a maximum angle of
approximately ±1° would be regarded as acceptable. Surface grinding and
machining may be necessary to achieve the required flatness. There should not be
any friction in the loading system since it can produce a smaller impression than the
expected impression. The condition of the indenter is also important. The duration of
applied load is important and must be controlled. Regular maintenance and
calibration of the machine is, therefore, essential.
The dimension of the specimen is also important since a test specimen that is too
thin would influence the microhardness values. According to the rule of thumb, the
specimen thickness should be twice than that of the Vickers diagonal. Also the
specimen table should be tightly fixed to the machine. Figure 2-26 shows the factor
that influences the microhardness results for thermal spray coatings.
2.6. Summary
HA is well accepted as a bioactive, biocompatible and bioresorbable material
closely resembling the mineral phase of bone and hard tissues in the human
skeleton. Thus, HA can form a strong implant-bone interfacial bond to improve the
prosthesis fixation. HA also has the ability to avoid releasing metal ions, a feature
that has further increased interest.
This literature survey has shown that plasma spray power, stand-off distance, and
powder feed rate are important factors that influence coating properties. Many
studies have been performed to understand the effects of these process parameters
on coating properties. However, very few have considered the mechanical properties
of the coating in terms of responses such as microhardness, and other important
responses, such as deposition efficiency.
It is necessary to understand the microhardness distribution to fully understand
the thermal spray microstructure. In the literature, several studies were conducted to
understand microhardness distribution using the indentation technique and statistical
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Figure 2-26 Cause-effect diagram of microhardness measurement for thermal spray coatings (based on Erne et al. [171]).
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analysis. However, more studies are necessary to understand the effects of applied
load throughout the coating thickness. There is also a need to understand indenter
tip roughness variation within the coatings.
Coatings prepared by sol-gel techniques are usually uniform, while plasma
sprayed coatings are full of pores and cracks. Therefore, it may be possible to fill in
the pores and cracks of the plasma sprayed HA coatings using sol-gel dip coatings.
The microstructures and mechanical properties of the plasma sprayed HA coatings
could be enhanced through surface modification by employing sol-gel dip coatings in
conjunction with plasma sprayed coatings.
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58 | P a g e Author: Md. Fahad Hasan
3. Experimental equipment, procedure, and materials characterization
3.1. Plasma spray system
The plasma spray equipment used in this work was an atmospheric plasma spray
system installed in United Surface Technology (UST) Pty Ltd, Australia. The booth
with plasma spray equipment is shown in Fig. 3-1.
Figure 3-1 Plasma spray booth.
There are four main components in the booth:
• Plasma torch
• Control and instrumentation system
• Powder feeder unit and
• Gas supply system
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Plasma torch
The plasma torch used in this research was the SG 100 (Praxair, USA) with an
internal powder injection mode, Figure 3-2. The torch is attached with a machine
mountable base that allows the torch to move frequently.
Figure 3-2 Plasma spray torch SG 100.
Control and instrumentation system
The control system shown in Fig. 3-3 was the Plasmadyne 3600 (California). This
unit controls the plasma voltage, current, primary gas flow rate, secondary gas flow
rate, and carrier gas flow rate.
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Figure 3-3 Control system.
Powder feeder unit
The powder feeder used was the 3MP Plasmadyne dual rotating powder hopper
1275 (California), Figure 3-4. This unit controls the powder feed rate. The powders
for spraying are stored in the powder hopper are transported to the torch by a carrier
gas.
Gas supply system
The gas supply system with argon and helium cylinder are shown in Figure 3-5.
Primary and secondary gases are stored in composed cylinders outside the main
factory.
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Figure 3-4 Powder feeder unit.
Figure 3-5 Gas supply system.
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3.2. Feedstock morphology
Captal 60/1, thermal spraying hydroxyapatite powder supplied by Plasma Biotal
Ltd (UK), was used in this study. This HA powder was produced for thermal spray
applications. The powders have a mean particle size of 45±10 µm, d(10) of 20±5 µm,
d(90) of 80±10 µm.
Figure 3-6 shows hydroxyapatite powder morphology and particle size
distribution. Powders are composed of spherical and angular morphologies.
3.3. Preparation of substrate and coating cross-sections
Substrate 3.3.1.
Mild steel substrates were used for plasma spraying of HA. The substrate was flat
with a size of 40×30×3 mm.
Grit blasting and substrate cleaning procedure 3.3.2.
Substrate surface condition plays a major role in depositing thermal spray
coatings. The substrate was kept in an ultrasonic cleaner with acetone solution for
15 minutes. The substrates were grit blasted prior to spray coating. The grit blasting
procedure was carried out using 500 mesh pure alumina (Al2O3) at a blast pressure
of 0.5 MPa until the surface was uniformly roughened. The stand-off distance of the
blasting was varied between 120-150 mm. Plasma spray coating was performed
immediately after completion of grit blasting.
Coating mounting, grinding and polishing 3.3.3.
The HA coated samples were sectioned by an automatic cutter to allow their
cross-section to be examined. A high speed precision cutting machine (Secotom 50,
Struers, Australia) was used for sectioning samples, Figure 3-7. Then, the samples
were mounted in epoxy resin for firm holding during grinding and polishing. The resin
used was Buehler epoxide resin and Buehler epoxide hardener that were mixed at a
ratio of 5:1. The samples were placed in moulds with a clip to make the sample
stable. Then, the moulds were filled with the resin slowly and care taken to maintain
the desired sample orientation. They were cured at least 24 hours prior to removal
from the moulds.
Chapter 3 Experimental equipment, procedure, and materials characterization
63 | P a g e Author: Md. Fahad Hasan
0 20 40 60 80 100 120 140
0
10
20
30
40
50
60
70
% (Volume) % (Cumulative)
Particle diameter (um)
Vol
ume
frequ
ency
(%)
b
0
20
40
60
80
100
Cum
ulat
ive
frequ
ency
(%)
Figure 3-6 HA powder (a) morphology, and (b) particle size distribution.
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Specimens were ground using a Buehler grinder by P240, P320, P400, P600,
P800, and P1200 grit SiC papers, followed by polishing on the Buehler Microcloth
polisher with 15, 5, and 1 µm diamond pastes. Grinding was carried out using each
sand paper until the damage caused by the sectioning of the HA coated samples
was completely removed; with the sample being planar and exhibiting polishing
makes in the same direction. When a change of paper or cloth occurred, the sample
was rotated to 90º and then polished until uniform scratches were visible. The speed
of the grinding and polishing machine was varied in the range of 200-300 rpm. The
grinding machine used in this study was the Leco VP 150. The polishing machines
used were the Leco GP 25 (coarse polishing 15 and 5 µm) and the Leco VP 160
(smooth polishing 1 µm). The grinding and polishing machines are shown in Fig. 3-8
for reference and archival purposes.
Figure 3-7 Automatic Struers cutter.
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65 | P a g e Author: Md. Fahad Hasan
Figure 3-8 Metallographic preparation (a) grinding (P240-P1200), (b) coarse
polishing (15 and 5 µm), and (c) smooth polishing (1 µm).
3.4. Characterization of HA coatings
Scanning electron microscopy (SEM) & energy dispersive X-ray 3.4.1.spectroscopy (EDS)
Plasma spray coated specimens, polished cross sections, and powder
morphology were observed using a field emission scanning electron microscope
(FESEM or SEM, ZEISS Supra 40 VP), Figure 3-9. The samples tested for SEM
should be appropriate to fit inside the SEM specimen vacuum chamber. HA is a non-
conducting material. Thus, surface of the sample must be electrically conductive
otherwise charging effects may arise during scanning. Thin gold coatings are widely
used to make the surface conductive. All samples studied in this research were gold
coated with a DYNAVAC (CS 300) deposition system prior to the SEM analysis.
Chapter 3 Experimental equipment, procedure, and materials characterization
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Figure 3-9 Scanning electron microscopy (SEM).
The sample was mounted on a sample holder using a carbon tape that made a
connection between the sample holder and thin gold coating. After completion of
gold sputtering, the sample was placed under the SEM observation as quickly as
possible. The sample was kept in a vacuum between the gold sputtering and SEM
observation. The scanning parameters used in this study are shown in Table 3-1.
Table 3-1 Parameters used for SEM analysis of HA coatings and HA powder.
Parameters Value Accelerating voltage (kV) 3-15
Magnification (x) 500-1300 Working distance (mm) 10-17
Energy dispersive X-ray spectroscopy (EDS) is an analytical technique. It is also
referred to as EDX analysis. The elemental composition of a specimen can be
analysed using EDX. The EDX analysis system used in this study worked as an
integrated feature of the SEM.
X-Ray diffraction (XRD) 3.4.2.
The phase components in the HA coatings were determined by X-ray
diffractometry (XRD, Bruker D8 Advance Diffractometer), Figure 3-10. The obtained
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67 | P a g e Author: Md. Fahad Hasan
d-values were compared with the characteristic d-values taken from JCPDS cards to
identify various X-ray peaks. In order to carry out the scan, samples were mounted
on a sample holder using double-sided tape. The sample holder was then placed on
the XRD slot. ASTM F2024 [172] was followed to carry out the scan of HA coatings
and powder. Parameters used for the XRD scan are shown in Table 3-2.
Figure 3-10 X-ray diffractometry (XRD).
Table 3-2 Parameters used for XRD analysis of HA coatings and HA powder.
Parameters Value Range 20-60º
Increment 0.02 Scan speed 1º/min
Voltage 40 kV Current 40 mA
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Raman spectroscopy 3.4.3.
Raman spectroscopy is a non-destructive method. The sample preparation for
this method is minimal. The composition, chemistry, and structure can be obtained
from the spectra generated from the specimens. Micro-Raman scattering
experiments were performed via the Raman spectrometer (Renishaw plc, UK) shown
in Fig. 3-11. The analyses were conducted with an excitation wavelength of 514 nm
over a spectrum of range 200-2000 cm-1 with cosmic ray removal. The resolution
was 1 cm-1 and 10% power was used for 10 seconds.
Figure 3-11 Raman spectroscopy system.
Profilometer 3.4.4.
A profilometer allows the measurement of surface roughness. Surface roughness
of the coatings was measured using the Surtroic 25 (Taylor Hobson, UK)
profilometer, Figure 3-12. This is a 2D profilometer that has a stylus that is run over
the surface of the coating. Accuracy of the roughness tester was checked prior to the
measurement with a calibration sample.
After indentation using a Vickers indenter, the indenter tip roughness was
measured using a 3D profilometer (Bruker AXS ContourGT-K) with Vision 64
analysis software, Figure 3-13.
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Figure 3-12 Two dimensional profilometer.
Figure 3-13 Three dimensional profilometer.
3.5. Analysis of coatings
Porosity measurements 3.5.1.
The porosity of a coating is an important factor that describes the inherent
characteristics of the coating. Porosity is most important for orthopaedic applications.
The level of porosity required depends on the application. There is no required level
of porosity specified by the Food and Drug Administration (FDA). To obtain good
mechanical properties, a porosity of less than 5% is preferable. Sun et al. [69] stated
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70 | P a g e Author: Md. Fahad Hasan
that the porosity of commercially available plasma sprayed HA coatings can be as
high as 50%.
The porosity of HA coatings can be calculated from high resolution microscope
images of the cross-section of the coated sample. The pore area fraction can be
calculated manually by drawing a calibrated grid on the microscope image. The
following equation is then used to calculate the pore area fraction [22]:
1(x x )Ay+
= (24)
where A is the area fraction, x is the number of intersections of the grid that fall
within a pore, x1 is half the number of intersections of the grid that fall on a pore
boundary, and y is the total number of grid intersections in the field of view.
Image processing and analysis in Java (ImageJ) v1.46p software from the
National Institutes of Health (NIH) was used to calculate the pore area fraction. This
software allows the pores in the coating to be highlighted and the pore fraction of the
coating can then be calculated by the software. First of all, it is necessary to set up
the scale of the image. Secondly, the threshold value needs to be adjusted so that all
the pores are highlighted. The image then needs to be smoothed to resolve the
pores. After that, particles are analysed to measure the area fraction or porosity of
the coatings. The British standards institution (BSI) standard testing method for the
determination of the porosity of ceramics coatings is outlined in draft documents
(DD) European pre-standard (ENV) 1071-5:1995 [173].
Microhardness and elastic modulus measurements 3.5.2.
Hardness is defined as the ratio of applied force to contact surface area. Vickers
and Knoop hardness testers are very popular for microhardness measurements. The
Vickers test is a non-destructive test. Micro force ranges from 10 g to 1000 g. The
test point is highly finished to allow a clear image for accurate measurement. The
test is very slow and the indent size is optically measured. The Vickers hardness
number can be calculated using the following formula:
2
PVH 1.8544d
= (25)
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71 | P a g e Author: Md. Fahad Hasan
where ‘P’ is the force applied to the indenter in kgf and ‘d’ is the mean diagonal of
the indentation in mm.
The Knoop microhardness and elastic modulus were determined following the
theory proposed by Marshall et al. [146] and Leigh et al. [147]. The Knoop
microhardness measurement can be obtained from the following formula:
KHN = 14229 2
Pa
(26)
where P is the applied load in grams, a is the major diagonal length of the Knoop
indentation given in micrometres, and KHN is the microhardness number. The elastic
modulus can be calculated by the following formula:
'
' 'b b b αKHN= -a Ea a≈ (27)
where α is a constant and is taken as 0.45; a and b are the major and minor
diagonals of the Knoop indentation; a' and b' are the major and minor diagonal of
ideal Knoop indentation, b ' 0.14a'
= ; and E is the elastic modulus and KHN is the
microhardness number.
Deposition efficiency measurements 3.5.3.
Deposition efficiency (DE) of the coatings has been measured by the following
equation:
Mass of the coatingsDE = Powder feed rate×Time required during the spray process
(28)
The substrate weight was measured before and after the coatings to measure the
mass.
Crystallinity measurements 3.5.4.
Crystallinity of a coating is important. According to the ISO standard specification
(ISO 13779-2 [49]), the crystalline content should be greater than 45% for a HA
coating to have sufficient mechanical properties in vivo. For medical applications, the
required crystallinity is more than 95%. In general, the crystallinity of HA plasma
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72 | P a g e Author: Md. Fahad Hasan
spray coatings vary from 65% to 70% for biomedical use [79]. Dalton and Cook [174]
found crystallinity varied between 57% and 61% by comparing four commercially
available plasma spray coatings.
There are three methods used to measure the crystallinity of a coating achieved
by X-ray diffraction:
• The Relative intensity method [70]
• The Rietveld method [175, 176]
• The Rutland method [68, 69, 71]
In this study, the Rutland method was used since it is a commonly used method
for determining crystallinity. According to this method, crystallinity is defined as the
ratio of crystalline area to the total area; i.e., summation of crystalline ( cA ) and
amorphous ( aA ) areas under diffraction pattern, which can be presented in the
following form:
c
c a
ACrystallinity (%) = ×100%
A + A∑
∑ ∑ (29)
Surface roughness measurements 3.5.5.
The roughness of a coating is important because bone growth depends on this
physical characteristic. Osteoblast cell attachment is affected by the surface
roughness of the HA coatings. The bone growth on the coating is affected by the
surface roughness once it is implanted into the body. Powder particles used in the
coating affects the coating roughness and coating thickness also influences the
roughness.
Gross and Babovic [177] demonstrated that partially melted particles were not
able to flatten on the coating surface, giving rise to large undulations and thus higher
coating roughness. Osteoblast cells attach and proliferate better on rough surfaces,
whereas fibroblasts and epithelial cells prefer smooth surfaces [178, 179]. The
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73 | P a g e Author: Md. Fahad Hasan
roughness [180] of the surface of HA coating can be calculated using the following
formula:
1
0a
y dxR =
L
∫ (30)
where Ra = average surface roughness
The Ra parameter is the average distance between the surface of the coating and
the mean line, as shown in Fig. 3-14.
Figure 3-14 The Ra parameter.
X
Ra Y
Chapter 4 Relationship between process parameters according to literature survey
74 | P a g e Author: Md. Fahad Hasan
4. Relationship between process parameters according to literature survey
4.1. Introduction
Thermal spraying is a well-established technology for the production of overlay
protective coatings and is used extensively for metallic and ceramic coatings in
industry to operate under extreme conditions of wear, corrosion and high-
temperature exposure. More recently, multilayer coatings have been considered for
functional surfaces. Atmospheric plasma spraying is one of these processes. Plasma
spraying, a complex deposition method, involves a myriad of process parameters,
equipment, and powder parameters, which have a direct effect on the coating
properties [181, 182].
To develop new functional and reproducible coatings, an empirical approach is
often adopted to identify those processing parameters that have significant effect on
the coating properties. This process is expensive and time consuming. The
requirement in industry is the reliability and reproducibility of the coatings, as well as
the establishment of a knowledge base of their intrinsic material properties and
behaviour [183-185].
Thus, there is a need to develop strong scientific correlations among these
parameters to accomplish the requirement of prime reliant coatings. This requires a
concerted, integrated interdisciplinary approach, and this chapter demonstrates such
an approach for a specific spray system and material, and focuses on establishing
the relationships between process parameters, such as power, powder feed rate,
stand-off distance and powder particle size.
4.2. Methodology
Data were collected from the available published literature [3, 7, 22, 55, 66, 68,
78, 92, 119, 120, 175, 186-264].
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75 | P a g e Author: Md. Fahad Hasan
4.3. Results & discussions
Relationship between power and stand-off distance 4.3.1.
To prepare a relationship between power and stand-off distance 89 data [3, 66,
69, 78, 119, 120, 175, 186, 187, 192, 195, 197, 198, 200-203, 205, 208, 209, 211-
213, 215-218, 220, 223, 225, 228, 230-233, 236, 237, 240-244, 247-249, 251, 252,
260, 262, 263] have been collected and used to plot the graph shown in Figure 4-1.
Figure 4-1 (a) indicates that, for hydroxyapatite, as the power increases, stand-off
distance needs to increase. The fitted equation shows an adjusted R squared value
0.22 due to the scattered data. To improve the R squared value, the averaged data
was used. Figure 4-1 (b) shows the graph with average SOD vs. power. However,
this approach does not improve the R squared value.
The third analysis removed the ‘outlier’ points that were considered
unrepresentative of the data sets. For instance, some of the literature values
demonstrated poor microstructures that would gave rise to poor performance. After
excluding outlier points and poor data, Fig. 4-1 (c) indicates an improved R squared
value of 0.85.
From Fig. 4-1 (c), it can be seen that the fitted equation suggests a power range
of 5-43 kW and a stand-off distance of 5-23 cm for hydroxyapatite coatings. This
provides a guideline for selecting appropriate process parameters to achieve high
quality hydroxyapatite coatings.
Relationship between power and powder feed rate 4.3.2.
Figure 4-2 shows the relationship between power and powder feed rate for
hydroxyapatite coatings. Fifty data [78, 119, 186, 189, 190, 192, 195, 197, 201, 202,
204-206, 208, 209, 211, 212, 222, 223, 227-229, 237, 239, 241-246, 248, 249, 255-
257, 259-261] were collected from the literature. This graph shows a range of power
of 10-45 kW and a powder feed rate of 8-43 g/min. The fitted equation shows a good
match with these 50 data points with a R squared value of 0.71.
Chapter 4 Relationship between process parameters according to literature survey
76 | P a g e Author: Md. Fahad Hasan
Figure 4-1 Relationship between power and stand-off distance (a) with all data, (b)
with average data, and (c) with good data.
Figure 4-2 Relationship between power and powder feed rate.
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77 | P a g e Author: Md. Fahad Hasan
Relationship between power and powder particle size 4.3.3.
Figure 4-3 shows the relationship between power and powder particle size with
38 data [66, 119, 175, 186-188, 190, 193, 197, 198, 201, 204-206, 208, 211-214,
225, 229, 231, 234-237, 239, 243, 246, 247, 249, 259, 260, 265]. In this study, data
from the literature relating to powder particle sizes were divided into the following
three categories:
• Fine particles (<45 µm) scaled as 1
• Medium particles (45-75 µm) scaled as 2 and
• Coarse particles (>75 µm) scaled as 3
Figure 4-3 Relationship between power and powder particle size.
This graph shows increasing particle size initially requires an increase in power
level. A maxima appears at a power of 31 kW for coarse particles. It is noteworthy
that low power (~10-15 kW) and high power (~35-40 kW) levels have been used for
fine HA feed stocks.
Chapter 4 Relationship between process parameters according to literature survey
78 | P a g e Author: Md. Fahad Hasan
Relationship between powder feed rate and powder particle size 4.3.4.
Figure 4-4 shows the relationship between powder feed rate and powder particle
size with 27 data [22, 186, 188, 191, 192, 196, 197, 199, 201, 206-208, 224, 227-
229, 237, 239, 245, 254, 255, 257, 259]. An increase in powder feed rate can be
used as the powder particle size increases initially. A maximum feed rate of 33 g/min
has been achieved for coarse particles; whereas medium particles may be feed at
rates of up to 45 g/min.
Figure 4-4 Relationship between powder feed rate and powder particle size.
4.4. Summary
A relationship between plasma spray process parameters has been developed.
These relationships enable selection of appropriate process parameters rather than
a trial and error approach. The relationships developed in this critical analysis of the
literature were used in this current study to implement the plasma spray protocol.
Chapter 5 Taguchi design of experimental study on HA coatings
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5. Taguchi design of experimental study on HA coatings
5.1. Introduction
Plasma spraying, a complex deposition method, involves a myriad of process
parameters, equipment, and powder parameters that have a direct effect on the
coating properties [181, 182]. An empirical approach is often adopted to identify
those process parameters that have a significant influence on the coating properties.
The conventional trial and error optimization process is expensive and time
consuming. Thus, there is a need to develop strong scientific correlations among the
prime thermal spray parameters that permit the manufacture of quality coatings.
Statistical design of experiment methods has been demonstrated to be a cost-
effective and time-efficient technique, with the means to systematically investigate
process parameters. Researchers [22, 66, 119, 120, 266] have used Taguchi,
response surface methodology, and factorial design to optimize plasma sprayed
hydroxyapatite coating properties in terms of porosity, crystallinity, purity, adhesion
strength, roughness, and thickness. There have been a limited number of studies
that have focused on deposition efficiency and mechanical properties such as the
microhardness of plasma sprayed HA coatings: the focus of this current
investigation. High deposition efficiency is related to the economic manufacture of
thick and large-scale coatings under shorter process times [267]. Microhardness is
important since it is a material property that is related to coating performance and
reliability.
The Taguchi design of experiment method is an effective and time saving
procedure that employs a smaller number of experiments for process optimization. In
this study, a Taguchi L9 (34) design has been used that allows to understand the
influence up to 4 different independent variables with each variable having 3 set of
values. Among many process parameters of plasma spray; the power, powder feed
rate, and stand-off distance have been identified as parameters that strongly
Materials from this chapter have been accepted in the following journal:
Hasan, Md. Fahad; Wang, James; Berndt, C.C.; 2014, A Taguchi design study of
plasma sprayed hydroxyapatite coatings. Materials Science Forum, vols. 773-
774, pp 598-609 (In press)
Chapter 5 Taguchi design of experimental study on HA coatings
80 | P a g e Author: Md. Fahad Hasan
influence the coating properties. Secondary gas flow rate is related to power, and
carrier gas flow rate is related to powder feed rate; thus, these related parameters
have been combined as one factor in order to indicate a co-dependence.
5.2. Methodology
Taguchi L9 design of experiments (DOE) was used in this study, as this design
needs a small number of experiments compared to other designs for 3 factors with 3
levels each to optimise coating properties. The literature study reveals that power,
powder feed rate, and stand-off distance are the most influential factors in terms of
altering the coating properties. Process parameters were selected based on the
literature review. Power was selected as an independent variable, while stand-off
distance and powder feed rate were corresponding dependent variables. All data
collected from the literature (shown in Sections 4.3.1 and 4.3.2) were used to plot a
graph, fit them, and establish a relationship using Origin v9 software (OriginLab,
Northampton, MA), as shown in Fig. 5-1. From the graphs, different levels of power
of 20, 30 and 40 kW, and their corresponding values of stand-off distances, and
powder feed rates were selected and used for plasma spraying, as shown in Table
5-1. These selected process parameters are indicated as a red circle on these
graphs.
A Taguchi L9 table with 3 factors (power, powder feed rate, and stand-off
distance) and 3 levels for each factor is shown in Table 5-2. In the rest of the
chapter, for simplicity, factor power and secondary gas flow rate will be named as
‘power’ and factor powder feed rate, and carrier gas flow rate will be named as
‘powder feed rate’. Figure 5-2 indicates the factors and responses considered for the
optimisation of the coatings.
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Figure 5-1 Plasma spray process parameters graph from literature survey a) power
vs. stand-off distance, and b) power vs. powder feed rate.
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Table 5-1 Plasma spray process parameters predicted from literature study.
Power (kW) Stand-off distance (cm) Powder feed rate (g/min)
20 8 16.31≈16
30 10.53≈11 22.47≈22
40 15.68≈16 27.18≈27
Figure 5-2 Plasma spray process with factors and responses for Taguchi L9 design.
Table 5-2 Process parameters used in Taguchi L9 design.
Sample Power (kW)
Primary gas flow
rate, Argon (slpm)
Secondary gas flow
rate, Helium (slpm)
Carrier gas flow rate,
Argon (slpm)
Powder feed rate
(g/min)
Stand-off distance
(cm)
1 20 50 6 3 16 8 2 20 50 6 5 22 11 3 20 50 6 7 27 16 4 30 50 9 3 16 11 5 30 50 9 5 22 16 6 30 50 9 7 27 8 7 40 50 12 3 16 16 8 40 50 12 5 22 8 9 40 50 12 7 27 11
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5.3. Results & discussions
The coating characterization results for experimental samples 1 to 9 are provided
in Table 5-3.
Table 5-3 Coating properties.
Sample Porosity
% (n=10)
Microhardness HV
(n=20)
Deposition efficiency
% (n=5)
Crystallinity %
Surface roughness
µm (n=10)
1 16.0±4.1* 172±43* 25.0±7.2 73* 10.9±1.4* 2 11.7±1.1 213±44 19.6±4.2 59 7.9±0.7 3 10.9±3.7 235±29 10.9±1.5* 38 7.0±0.5* 4 5.3±1.5 220±24 46.2±9.4 50 9.6±0.7 5 4.1±1.5 237±44 30.9±10.3 43 9.9±0.9 6 7.2±2.0 211±32 35.5±5.7 66 8.2±0.9 7 3.8±0.9* 278±44 53.4±7.4 46 9.5±0.8 8 4.0±0.3 284±42 59.0±3.6* 28* 8.7±0.7 9 4.0±0.9 329±40* 58.4±3.0 48 7.8±0.9
* indicates maximum and minimum values
Porosity 5.3.1.
Porosity was determined via SEM image analysis of the coating cross-sections.
Ten fields were selected arbitrarily for measuring porosity. Table 5-3 indicates that
porosity varied from 3.8% to 16%. Run 1 exhibited the highest porosity and run 7 the
lowest. The high porosity was obtained at lower power and shorter stand-off
distances due to a poor melting status [69]. Greater power levels reduced the
porosity. Figure 5-3 shows the plot of the main effects on the porosity generated by
Minitab v16 software (Minitab, Inc.). The porosity has been reported to 1/10th of a
percentage point, since this represents the numerical average of 10 measurements.
Note, however, that traditional measurements of porosity report values to the nearest
integer, since this is considered more appropriate considering the variable nature of
the microstructure. Thus, the higher resolution data reported here should not be
used to imply that changes on 1/10th of a percentage point can influence the material
properties of thermal spray coatings.
After plotting this porosity data in the response table of Design of Expert v8
software (Stat-Ease, Inc.), an ANOVA (analysis of variance) table was generated,
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84 | P a g e Author: Md. Fahad Hasan
which is shown in Table 5-4. In this table, the F value determines whether the
variances between two independent samples are equal and the p-value is the
probability, ranging from zero to one, that the results observed in a study have
occurred by chance. A p-value of 0.05 or below is desired as being statistically
significant. From this table it can be seen that power and secondary gas flow rate
(X1) have major effects (87.2%) on the porosity. ANOVA analysis indicates that the
porosity results are significant. The ANOVA table shows a p-value of 0.04 and
implies that the model is significant.
Figure 5-3 Main effects plot generated by Minitab software.
Table 5-4 ANOVA table for coatings porosity.
Terms Sum of squares
Degrees of
freedom (df)
Mean square F value p-value
Prob>F %
Contribution
Model 153.5 6 25.58 19.66 0.0497 Power and
secondary gas flow rate (X1)
136.14 2 68.07 52.32 0.0188 87.21
Powder feed rate and carrier gas flow
rate (X2) 4.71 2 2.35 1.81 0.3559 3.02
Stand-off distance (X3) 12.65 2 6.32 4.86 0.1706 8.10
Residuals 2.60 2 1.30 1.67
Core total 156.10 8 100
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Microhardness 5.3.2.
Table 5-3 shows that microhardness data are the average of twenty
measurements and were found to lie between 172 HV and 329 HV. Higher power
and secondary gas flow rate increased the microhardness because of better particle
melting [69]. High microhardness was found at run 9 with 40 kW power and low
microhardness was found at run 1 with 20 kW power. Figure 5-4 demonstrates the
plot of the main effects on the microhardness generated by Minitab software.
Figure 5-4 Main effects plot generated by Minitab software.
Design of Expert software generates an ANOVA table after plotting all the
microhardness data. Table 5-5 indicates that power has a major effect (77.9%) on
the microhardness. ANOVA analysis shows that the microhardness results are
significant. The ANOVA table shows that the p-value is 0.04, which implies that the
model is significant.
Deposition efficiency 5.3.3.
The deposition efficiency data presented in Table 5-3 are the average of five
measurements and they ranged from 10.9% to 59%. The high deposition efficiency
obtained at run 8 arose due to a higher power, centre powder feed rate, and lower
stand-off distance. The ANOVA table demonstrates that power and secondary gas
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flow rate (X1) influenced the deposition efficiency with a contribution ratio of 90.1%.
Although the deposition efficiency has been reported to 1/10th of a percentage point
it is more realistic, in commercial practice, that the accuracy of this measurement is
within several percentage points.
Table 5-5 ANOVA table for coatings microhardness.
Terms Sum of squares
Degrees of
freedom (df)
Mean square F value p-value
Prob>F %
Contribution
Model 17592.67 6 2932.11 19.80 0.0489 Power and secondary
gas flow rate (X1) 13941.56 2 6970.87 47.06 0.0208 77.93
Powder feed rate and carrier gas flow rate
(X2) 1866.89 2 933.44 6.30 0.1369 10.44
Stand-off distance (X3) 1784.22 2 892.11 6.02 0.1424 9.97
Residuals 296.22 2 148.11 1.66
Core total 17888.89 8
Figure 5-5 illustrates the plot of the main effects on the deposition efficiency
generated by Minitab software. Powder feed rate and stand-off distance do not have
any significant effects on coating deposition efficiency. However, by comparing
deposition efficiency data of experimental runs 1, 2, 3, it can be concluded that an
increase of powder feed rate and stand-off distance reduces the deposition
efficiency. It is likely that the higher powder feed rate and stand-off distance (i)
increases the amount of powder loss, or (ii) fewer particles of optimum melting
characteristics are available for deposition onto the substrate.
The ANOVA table shown in Table 5-6 was created by Design of Expert software
after plotting all the deposition efficiency data in the response table. From this table,
it can be seen that power has a major effect (90.10%) on the deposition efficiency.
ANOVA analysis proves that the deposition efficiency results are significant. It shows
that the p-value is 0.01, which implies that the model is significant.
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Figure 5-5 Main effects plot generated by Minitab software.
Table 5-6 ANOVA table for coatings deposition efficiency.
Terms Sum of squares
Degrees of
freedom (df)
Mean square F value p-value
Prob>F %
Contribution
Model 2448.61 6 408.10 77.62 0.0128 Power and
secondary gas flow rate (X1)
2215.75 2 1107.87 210.71 0.0047 90.10
Powder feed rate and carrier gas flow rate
(X2) 71.35 2 35.67 6.79 0.1285 2.90
Stand-off distance (X3) 161.51 2 80.75 15.36 0.0611
6.57
Residuals 10.52 2 5.26 0.43
Core total 2459.12 8
Crystallinity 5.3.4.
Crystallinity data, Table 5-3, varied from 28% to 73%. Figure 5-6 demonstrates
the plot of the main effects on the microhardness generated by the Minitab software.
In general, higher power produces higher heat input to the particles as well as higher
flame velocities, resulting in more particles in a molten state, which produces an
amorphous phase [268]. Thus, higher power reduces the crystallinity of the coatings.
Chapter 5 Taguchi design of experimental study on HA coatings
88 | P a g e Author: Md. Fahad Hasan
On the other hand, higher stand-off distance provides more time for particles to cool
and resolidify, and thus, exhibit a crystalline character [78, 269].
Also, powder feed rate has an effect on the coating crystallinity. An increase in
powder feed rate reduces the flame temperature and therefore decreases the
number of molten particles; thereby increasing the proportion of the crystalline
phase. As a result, all these three factors (X1, X2, and X3) have an effect on the
crystallinity, which is reflected in the contribution ratio of crystallinity in the ANOVA
table. The p-value in the Table 5-7 indicates that no single factor has a significant
influence on the crystallinity.
Figure 5-6 Main effects plot generated by Minitab software.
Surface roughness 5.3.5.
Surface roughness data presented in Table 5-3 are the average of ten
measurements and vary between 7.02 and 10.92 µm. Figure 5-7 depicts the plot of
the main effects on surface roughness. The ANOVA table shows that powder feed
rate and carrier gas flow rate (X2) have an effect on surface roughness with a
contribution ratio of 66.4%. The p-value in the Table 5-8 confirmed that no single
factor significantly influenced the surface roughness.
Chapter 5 Taguchi design of experimental study on HA coatings
89 | P a g e Author: Md. Fahad Hasan
Table 5-7 ANOVA table for coatings crystallinity.
Terms Sum of squares
Degrees of
freedom (df)
Mean square F value p-value
Prob>F % Contribution
Model 965.33 6 160.89 0.54 0.7644 Power and
secondary gas flow rate
(X1) 426.56 2 210.78 0.71 0.5863 26.97
Powder feed rate and
carrier gas flow rate (X2)
254.89 2 127.44 0.43 0.7010 16.31
Stand-off distance (X3) 288.89 2 144.44 0.48 0.6741 18.48
Residuals 597.56 2 298.78 38.24 Core total 1562.89 8
Figure 5-7 Main effects plot generated by Minitab software.
Numerical optimization of coating properties 5.3.6.
Design of Expert numerical optimization was used in this study to optimise the
coating properties all. It is necessary to set up criteria for each response to optimise
the process parameters. The criteria for the coating properties were chosen as
shown in Table 5-9. Addition of ‘+’ indicates more importance; i.e., ‘+++’ indicates
lowest importance and ‘+++++’ indicates highest importance in the table.
Chapter 5 Taguchi design of experimental study on HA coatings
90 | P a g e Author: Md. Fahad Hasan
Table 5-8 ANOVA table for coatings surface roughness.
Terms Sum of squares
Degrees of
freedom (df)
Mean square F value p-value
Prob>F % Contribution
Model 10.10 6 1.68 1.51 0.4497 Power and
secondary gas flow rate (X1)
0.83 2 0.41 0.37 0.7295 6.73
Powder feed rate and carrier gas flow rate (X2)
8.19 2 4.10 3.68 0.2137 66.42
Stand-off distance (X3) 1.09 2 0.54 0.49 0.6720 8.84
Residuals 2.23 2 1.11 18.01
Core total 12.33 8
After selecting these criteria in Design of Expert software, it was possible to
optimise process parameters by considering all optimisation criteria. Design of
Expert software produces the best solution for these entire criteria with a desirability
of 0.7. The solutions suggest that the optimal process parameters are power 40 kW,
powder feed rate 16 g/min, and stand-off distance 11 cm. The solution also predicts
coating properties for these optimum settings. It predicts porosity (%), microhardness
(HV), deposition efficiency (%), crystallinity (%), and surface roughness (µm) of
4.4%, 290 HV, 64%, 49%, 9.4 µm, respectively, for the optimum settings of process
parameters. Table 5-10 comprises results between actual and predicted coating
properties.
Table 5-9 HA optimisation criteria.
Properties name Goal Importance Porosity (%) Minimise ++++
Microhardness (HV) Maximise +++++ Deposition efficiency (%) Maximise +++++
Crystallinity (%) Maximise +++++ Surface roughness (µm) Maximise +++
Chapter 5 Taguchi design of experimental study on HA coatings
91 | P a g e Author: Md. Fahad Hasan
Table 5-10 Comparison of results between actual and estimated performance of
coating properties.
Porosity %
(n=10)
Microhardness HV
(n=20)
Deposition efficiency
% (n=5)
Crystallinity %
Surface roughness
µm (n=10)
Predicted 4.4±1.2 290±12 64.6±2.3 49 9.4±1.0 Experimental 4.2±0.9 285±44 61.6±3.6 47 9.2±0.7
Mean difference 0.2 5 3.00 2 0.2
Mean percentage difference
(%)
4.55 1.72 4.64 4.08 2.23
5.4. Summary
A Taguchi L9 design of experiment was used to study and optimize
hydroxyapatite coatings manufactured by the plasma spray process. The study
determined the effects of (i) power and secondary gas flow rate (X1); (ii) powder feed
rate and carrier gas flow rate (X2); and (iii) stand-off distance (X3) on the coating
responses of porosity, deposition efficiency, microhardness, crystallinity, and surface
roughness. The Taguchi design allowed the following observations to be made
concerning hydroxyapatite coatings.
1. Power and secondary gas flow rate (X1) influences the porosity, deposition
efficiency, and microhardness. Powder feed rate and carrier gas flow rate
(X2) has a major effect on surface roughness, but the effect is not
significant. No single factor has a major influence on the crystallinity alone,
due to the distribution of effects among the three factors.
2. Higher power and secondary gas flow rate (X1) reduces porosity and
increases microhardness due to better particle melting.
3. Powder feed rate and stand-off distance do not have a significant effect on
coating deposition efficiency. However, higher power feed rate and stand-
off distance reduces deposition efficiency because they may increase the
amount of powder loss.
Chapter 5 Taguchi design of experimental study on HA coatings
92 | P a g e Author: Md. Fahad Hasan
4. Optimum coating properties with desired attributes were obtained in nine
experiments. Optimum experimental coating properties exhibit a porosity of
4%, a deposition efficiency of 61%, a microhardness of 285 HV, crystallinity
of 47%, and surface roughness of 9 µm. There is good agreement between
optimum and predicted values with less than 5% difference.
5. Optimum process parameters were predicted by Design of Expert software
with a desirability of 0.7. Optimum process parameters are power of 40 kW,
secondary gas flow rate of 12 slpm, powder feed rate of 16 g/min, carrier
gas flow rate of 3 slpm, and stand-off distance of 11 cm.
Chapter 6 Effect of power and stand-off distance on the HA coatings
93 | P a g e Author: Md. Fahad Hasan
6. Effect of power and stand-off distance on the HA coatings
6.1. Introduction
Plasma sprayed coatings build up on the substrate by melting material feedstock
at high temperature and velocity, accelerating the molten particles towards the
substrate, onto which they impact and cool under rapid solidification conditions [270].
The thermal spray parameters play a pivotal role in determining the microstructures
and properties of HA coatings. Power and stand-off distance have been identified as
two decisive factors that influence the microstructures and properties of HA coatings.
It was reported that changing the current, voltage, gas flow rate, and the stand-off
distance resulted in variations of phase component, microstructure and crystallinity
of coatings [215]. Sun and Lu et al. [69, 78] demonstrated that the power and stand-
off distance influence the microstructure, phase, crystallinity, and microhardness of
the hydroxyapatite coating. Higher power evolved a much longer plasma spray flame
than low power and created good quality coatings, but these operational parameters
were more likely to superheat the powder particles and possibly melt the
substrate[69, 215]. The stand-off distance must be coupled with power to avoid the
overheating of the substrate [78, 269]. Therefore, in this chapter, the coupled effect
of power and stand-off distance on coating properties were investigated.
6.2. Methodology
From Table 5-2, process parameters used for samples 1 (Power 20 kW, SOD
8cm), 4 (Power 30 kW, SOD 11 cm), and 7 (Power 40 kW, SOD 16 cm) are
presented in Table 6-1. The same samples are used in this chapter to analyse the
effect of power and stand-off distance, which are coupled by a single factor that is
denoted as ‘x’.
Materials from this chapter have been accepted in the following journal:
Hasan, Md. Fahad; Wang, James; Berndt, C.C.; Effect of power and stand-off
distance on plasma sprayed hydroxyapatite coatings. Materials and
Manufacturing Process, vols. 28(2), pp 1279-1285, 2013.
Chapter 6 Effect of power and stand-off distance on the HA coatings
94 | P a g e Author: Md. Fahad Hasan
Table 6-1 Plasma spray process parameters.
Sample Power (kW)
Primary gas flow
rate, Argon (slpm)
Secondary gas flow
rate, Helium (slpm)
Carrier gas flow
rate, Argon (slpm)
Powder feed rate (g/min)
Stand-off distance
(cm)
1 20 50 6 3 16 8 4 30 50 9 3 16 11 7 40 50 12 3 16 16
6.3. Results & discussions
Morphology and microstructure of the coatings 6.3.1.
Figure 6-1 exhibits the SEM microstructures on the top surface under the three
spray parameters. Figure 6-1 (a) reveals a microstructure consisting of unmelted
particles, semi-melted particles and some partially melted lamellae. Figure 6-1 (b)
shows spheroidized particles, partially melted lamellae and some melted lamellae.
Figure 6-1 (c) displays many spheroidized particles and flattened well-melted splats.
It can be seen that the number of spheroidized particles increases with an increase
in power and stand-off distance.
The coatings were composed of a combination of well-melted, partially melted,
and unmelted adhering irregular splats/particles with pores and microcracks. All
coatings were porous and contained fine spherical particles. The scope of particle
melting increased with increasing power and stand-off distances; i.e., ‘x’, as
indicated by the shape change from unmelted particles to flat splats. The higher
power increased the processing temperature of the plasma effluent, and the greater
stand-off distance lead to an increased residence time for the particle to heat; hence,
both factors provided conditions that gave rise to enhanced particle melting [228].
Cracks were presented as white lines for the higher power and stand-off
distances due to quenching stress generated during the spraying process. Similar
crack results were reported by Lu et al. [78], although findings from Sun et al. [69]
and Zhao et al. [215] indicated that there was an absence of cracks on the surface of
the coatings. The significance of cracks is beneficial from the viewpoint of the
Chapter 6 Effect of power and stand-off distance on the HA coatings
95 | P a g e Author: Md. Fahad Hasan
application; however, the large numbers of cracks are detrimental to the mechanical
strength of the coatings. Any voids will allow physiological media to penetrate the
coating and influence remodelling of the artificial HA if the phase structure is
appropriate.
Figure 6-1 SEM surface morphology a) sample 1: (20 kW, 8 cm), b) sample 4:
(30kW, 11 cm), and c) sample 7: (40 kW, 16 cm).
By comparing the microstructures of three cross-sections for sample 1, 4, and 7
in Fig. 6-2, it is noticed that the microstructure consisted of pores, cracks and
lamellae. The microstructure of Fig. 6-2 (a) depicts many pores, whereas Fig. 6-2 (b)
demonstrates a structure with less porosity; which is indicative of improved particle
melting that gives rise to a typical lamellae structure. Figure 6-2 (c) reveals plasma
spray process conditions that produced the least porous coating. It can be
summarised that the degree of unmelted particles was greater and the pore size
larger, in the qualitative sense, when power and stand-off distance were decreased.
Thus, for the purposes of the bioengineering application, the quality of the
microstructure in terms of the degree of particle melting; which influences the phase
A- Unmelted particle
B- Semi-melted particle
C- Partially melted lamellae
D- Spheroidized particle
E- Melted lamellae
Chapter 6 Effect of power and stand-off distance on the HA coatings
96 | P a g e Author: Md. Fahad Hasan
content and porosity, can be controlled by adjusting the thermal spray process
envelope.
Figure 6-2 Cross-section of the coatings a) sample 1: (20 kW, 8 cm), b) sample 4: (30 kW, 11 cm), and c) sample 7: (40 kW, 16 cm).
No distinct, unambiguous lamellae structure was observed in Fig. 6-2 (a) for
sample 1 (20 kW, 8 cm), whereas Fig. 6-2 (b) for sample 4 (30 kW, 11 cm) exhibits a
lamellae structure in good agreement with the results of Sun et al. [69]. Many
microcracks were observed in Fig. 6-2 (b) and Fig. 6-2 (c) that indicated quenching
phenomena occurred during deposition.
Porosity and deposition efficiency 6.3.2.
Figure 6-3 (a) indicates the influence of plasma spray parameters on the porosity
of HA coatings, where porosity is the average of 10 measurements and the error
bars represent +/- one standard deviations. The trend confirmed that porosity was
reduced at the greater power and stand-off distance, since the plasma power
increased the in-flight particle temperature and velocity. The increase of in-flight
particle temperature and velocity increased the degree of molten lamellae and
reduced the porosity; both features that will influence the physical characteristics of
the HA coating. Also, the porosity error bar reduced with increases in power and
stand-off distance, which demonstrates that porosity is less variable; the coating also
Chapter 6 Effect of power and stand-off distance on the HA coatings
97 | P a g e Author: Md. Fahad Hasan
shows improved homogeneity and reliability with increasing power and stand-off
distance.
Greater stand-off distances offer particles more time to resolidify and produce
coatings that exhibit a crystalline character [78, 269]. However, at higher power and
stand-off distance, several well-melted lamellae may stack together and molten
particles will fill in voids between neighbouring splats so that porosity is reduced.
Figure 6-3 (b) shows the effect of plasma spray parameters on the deposition
efficiency of HA coatings. The deposition efficiency ranged from 25% to 53%. Higher
power and stand-off distance produced less porous coatings, with well-melted
lamellae that also revealed an increase in deposition efficiency.
Figure 6-3 Influence of spraying parameters on the porosity of hydroxyapatite
coatings (a) porosity, (b) deposition efficiency, (c) microhardness, and (d) surface
roughness.
Chapter 6 Effect of power and stand-off distance on the HA coatings
98 | P a g e Author: Md. Fahad Hasan
Other studies [69] indicated that the plasma power level did not distinctly
influence the deposition efficiency; whereas Vijay et al. [271] reported that deposition
efficiency increased when there was an increase of power for plasma sprayed
alumina-titania coatings. The coatings produced in this study revealed a significant
influence of power and stand-off distance on the deposition efficiency, since the
selected spray parameters influenced the coating microstructure.
The HA particles were partially melted or unmelted at lower power and stand-off
distance. Such particles were not fully incorporated into the coating or may have
bounced off the substrate, leading to physical conditions that reduced the deposition
efficiency under these thermal spray process parameters. The increase of input
power increased the flame temperature and, consequently, increased the degree of
melting so that the deposition efficiency was improved.
Physical properties: microhardness and roughness 6.3.3.
The microhardness results, Fig. 6-3 (c), indicated an expected increase with
power levels and stand-off distance, as would be expected since the density
increased. This result is a direct reflection of the microstructure that evolves due to
the melting conditions within the plasma processing zone [69].
There is an inverse relationship between porosity and microhardness; i.e., the
porosity reduced as the microhardness increased. Higher power and stand-off
distance produced well-melted lamellae and splat bonding as indicated in the
microstructural study. The inference is that such microstructural conditions enhanced
the cohesion between splats and gave rise to improved mechanical properties of
these HA coatings.
Increasing power and stand-off distance produced more smooth coatings as
exhibited in Fig. 6-3 (d) that reflects the results of 10 measurements. Figure 6-1 (a)
reveals the roughest coating that was produced due to unmelted and partially melted
particles; whereas highly flattened particles, Fig. 6-1 (c), gave rise to the smoothest
surfaces.
Chapter 6 Effect of power and stand-off distance on the HA coatings
99 | P a g e Author: Md. Fahad Hasan
Phase structure and crystaliinity 6.3.4.
The percentages of crystallinity are 73%, 50% and 46% for samples 1, 4, and 7,
respectively. Increasing power decreased the crystallinity, while increasing stand-off
distance had the reverse effect of increasing crystallinity [69], Figure 6-4 (a). Higher
power increased the proportion of well-melted lamellae and the glassy phase, which
lead to an increased amount of amorphous phase as confirmed by the literature [69].
Higher stand-off distance provided more time for particles to cool, resolidify and
recrystallize, which ultimately increased crystallinity. Therefore, the degree of
crystallinity is a coupled effect of power and stand-off distance that preserves
crystallinity at an acceptable level. Hydroxyapatite coatings for bioengineering
applications should demonstrate a crystallinity of at least 45%, according to ISO
standards [49].
Figure 6-4 (b) represents X-ray diffraction (XRD) patterns of plasma sprayed
coatings. It shows both crystalline and amorphous HA. In addition, other
contaminations such as tri-calcium phosphate (TCP), tetra-calcium phosphate
(TTCP), and calcium oxide (CaO) are also noticed. The amorphous trace on the
XRD pattern increased, implying reduced crystallinity as the power and stand-off
distance increased. The intensity of HA peak (211) decreased with the increase of
power and stand-off distance, which indicates the reduction of HA contents and the
reduction of crystallinity.
EDX analyses were performed to calculate the Ca/P ratio of the coatings, Table
6-2, by the averaging of 5 measurements. The percentages of Ca, P, and O varied
by less than 5%, and the Ca/P ratio varied from 1.51, 1.61, and 1.62 in molar ratio
for samples 1, 4, and 7, respectively. This indicated that the coatings deposited at
higher power and stand-off distance have a Ca/P ratio closer to the nominal value of
stoichiometric hydroxyapatite (1.67). These increases of Ca/P ratio value are due to
the change of plasma spray parameters.
Chapter 6 Effect of power and stand-off distance on the HA coatings
100 | P a g e Author: Md. Fahad Hasan
Figure 6-4 Influence of process parameters on the a) crystallinity, b) XRD pattern for
i) sample 1: (20 kW, 8 cm), ii) sample 4: (30 kW, 11 cm), and iii) sample 7: (40 kW,
16 cm) of hydroxyapatite coatings.
Chapter 6 Effect of power and stand-off distance on the HA coatings
101 | P a g e Author: Md. Fahad Hasan
Table 6-2 Chemical composition of the coatings for samples.
Element Sample 1
wt.% (n=5)
Sample 4 wt.% (n=5)
Sample 7 wt.% (n=5)
Ca 37.60±0.46 35.68±0.30 38.05±0.23 P 19.17±0.23 17.08±0.30 18.10±0.31 O 43.23±0.25 47.24±0.60 43.85±0.54
Ca/P ratio (wt.%) 1.96 2.08 2.10 Ca/P ratio (molar ratio) 1.51 1.61 1.62
The Ca/P ratio was also measured via the X-ray diffraction [272] from the heights
of the crystalline HA peaks at (210) and (202), TTCP (Tetracalcium phospahte), ß-
TCP (ß-Tricalcium phosphate), and CaO (Calcium oxide). Crystalline peaks were
identified according to JCPDS cards. The calculation of the amorphous phase Ca/P
ratio (denoted as ‘Ca/Pamorphous’) was deduced from the XRD results by following the
method of Carayon et al. [272]. The Ca/P ratio remained constant at 1.66 for the
three experimental conditions measured by the XRD technique. The Ca/P ratio was
constant since the plasma power increase was compensated by a corresponding
increase in the stand-off distance.
6.4. Summary
Power and stand-off distance were coupled in this series of experiments and
selected on the basis of a comprehensive literature survey. The result shows that
coupled power and stand-off distance strongly influence the properties of coatings.
The following conclusions can be drawn:
1. The coating microstructure was improved with increasing power and stand-
off distance (i.e., ‘x’) due to enhanced particle melting and an increased
proportion of melted lamellae.
2. Porosity, and surface roughness were reduced with increasing power and
stand-off distance. Coating porosity was reduced due to an increase of in-
flight particle temperature and velocity. The reduction in porosity error bars
with increasing power and stand-off distance indicates the improved
homogeneity and reliability of the coatings. A longer stand-off distance
Chapter 6 Effect of power and stand-off distance on the HA coatings
102 | P a g e Author: Md. Fahad Hasan
permitted particles to either (i) resolidify and recrystallize, or (ii) to produce
well-melted lamellae depending on the initial particle size. The crystallinity
reduced with increasing power and stand-off distance as did the
smoothness due to better particle melting. The intensity of the HA peak
(211) decreased with the increase in power and stand-off distance, which
indicates the reduction of HA content.
3. Deposition efficiency and microhardness increased with increasing power
and stand-off distance. Microhardness increased due to reduced porosity,
since well-melted lamellae were able to stack together.
4. The combined effect of increasing power and stand-off distance allowed the
Ca/P ratio of the coatings to be maintained at a constant of 1.66. However,
the Ca/P ratio measured from EDX analyses indicated that higher power
and stand-off distance provides a Ca/P ratio of the coatings closer to the
nominal value of stoichiometric hydroxyapatite (1.67).
This chapter provides guidelines concerning operational conditions of the plasma
spray process that can be used to manufacture an appropriate hydroxyapatite
coating that exhibits the appropriate microstructure, porosity, and Ca/P ratio. The
operational conditions of roughness and deposition efficiency have also been related
to the physical attributes of the coating.
Chapter 7 Microhardness study using indentation techniques
103 | P a g e Author: Md. Fahad Hasan
7. Microhardness study using indentation techniques
7.1. Introduction
Thermal spray coatings exhibit complex microstructures with highly
heterogeneous and anisotropic behaviour. They feature flat plate–like lamellae,
cracks, pores, unmelted particles, weak interfaces between splats, and oxides [164,
273-276]. It is, therefore, important to consider measurement direction, location, and
applied load condition when determining the microhardness of thermal sprayed
coatings. Microhardness is reported in the literature as an average value with a
standard deviation of a certain number of random indentations (usually from 10 to
30) on the cross section of the coatings. However, the average with standard
deviation does not reflect the actual microstructural characteristics of thermal spray
coatings.
As a result, studies have investigated microhardness and elastic modulus using
indentation techniques [142, 147, 156, 161, 163, 167, 170, 277, 278]. However,
further work is necessary to investigate the effect of applied loads throughout the
coating thickness; as well as these studies need to take into consideration the dense
and porous areas, and the indentation angle, to fully understand the characteristics
of thermal spray coatings.
7.2. Methodology
The plasma sprayed HA coating used for the microhardness study was of
thickness 346±24 µm. Table 7-1 shows the plasma spray parameters used for this
coating. The Vickers and Knoop microhardness measurements were executed on
the top surface and the cross-section of the coating by indenting at loads of 50, 100,
300, and 500 gf for a dwell time of 15 s. More detailed procedures are described in
Materials from this section (Section 7.3) have been published in the following
journal:
Hasan, Md. Fahad; Wang, James; Berndt, C.C.; Evaluation of the mechanical
properties of plasma sprayed hydroxyapatite coatings. Applied Surface Science,
vols. 303, pp 155-162, 2014.
Chapter 7 Microhardness study using indentation techniques
104 | P a g e Author: Md. Fahad Hasan
Sections 7.3 and 7.4 in relation to the Vickers and Knoop microhardness methods
employed in this study.
Table 7-1 Plasma spray parameters.
Parameters Value Power (kW) 40
Primary gas flow rate, Ar (slpm) 50 Secondary gas flow rate, He (slpm) 12
Carrier gas flow rate, Ar (slpm) 7 Powder feed rate (g/min) 27 Stand-off distance (cm) 11
7.3. Microhardness study using Vickers indentation
Indentations were performed on the cross-section of coatings at locations of 75,
175, and 275 µm distance from the substrate-coating interface for all loads to avoid
the effect of impinging stress fields, Figure 7-1. Twenty readings were taken along
each region of interest, considering dense and porous areas for each indenter loads,
testing directions, and indent locations; Figure 7-2. The distance between each
indentation was three times greater than the indent diagonal [279].
The rule of mixtures was used to determine a composite microhardness from
dense and porous areas with varying percentage contributions (25%, 50%, and
75%). The composite microhardness can be calculated from the following equation:
Hc = dHd + (1-d)Hp (31) where d is the percentage contribution of the dense area, and Hc, Hd, Hp are the
composite microhardness, dense microhardness and porous microhardness,
respectively.
The surface roughness was measured using a 3D profilometer (Bruker AXS
ContourGT-K) on the polished cross-section after Vickers indentation. Roughness
was measured from the corner of the horizontal indent impression to a 5 µm distance
along the horizontal direction. This procedure is denoted as ‘indent roughness’ in this
chapter. For each indent, roughness was measured at the two corners of the
horizontal indent impression, and the averages of these two indent roughnesses are
presented. The intent of this experimental study was to gauge the influence of the
Chapter 7 Microhardness study using indentation techniques
105 | P a g e Author: Md. Fahad Hasan
indent experiment on the surface deformation near the indent. For example, it may
be possible to detect splat movement and crack features. For clear visualisation of
the graphs, 100 and 300 gf data are presented (Figs. 7-4, 7-6, and 7-8) analytically
by displacing the data on the x-axis position by 2 µm.
Figure 7-1 Schematic of Vickers indentation at different indent location within a
typical thermal spray coating microstructure.
Chapter 7 Microhardness study using indentation techniques
106 | P a g e Author: Md. Fahad Hasan
Figure 7-2 SEM micrographs of plasma sprayed hydroxyapatite coating (a) top
surface, and (b) cross-section.
Effects of applied load on the microhardness and indenter tip roughness 7.3.1.
Figure 7-3 shows the effect of applied load on the microhardness of the coating
top surface. Increasing the applied load, decreases the microhardness for both
dense and porous areas. The effects of 50, 100, 300, and 500 gf loads on the
microhardness of the coating cross-section followed similar trends, as shown in Fig.
7-4.
Thermal spray coatings are formed from many thousands of molten particles that
stack up as flat plate-like lamellae that are parallel to the substrate. The coatings
consist of defects such as pores, cracks, unmelted particles and weak interfaces due
to the uneven and irregular shape of the lamellae. At low loads, the indentor diagonal
length is small and might cover almost pore free areas and few lamellae. However, it
is more probable that pores will be encompassed by the indent area at higher loads.
Also, a higher load results in large cracks with permanent deformation, whereas a
lower load leads to small cracks that may recover due to the elastic recovery of
indentation. Thus, at a higher load, the microhardness decreases since it
encompasses coating defects such as, pores and cracks. In addition [146, 147], the
effect of stress relaxation encourages a decrease in microhardness at a higher load.
Figure 7-5 shows the effects of applied load on the indent roughness of the
coating top surface. Indent roughness increases with an increase in applied load,
since a higher load directly increases cracking from the indent corners. As the load
increases, the error increases, since the roughness is more scattered at higher loads
due to the inhomogeneous microstructure. Also, the indent roughness on the cross-
section of the coating shows similar results, Figure 7-6.
Chapter 7 Microhardness study using indentation techniques
107 | P a g e Author: Md. Fahad Hasan
0 100 200 300 400 500 600
200
250
300
350M
icroh
ardn
ess
(HV)
Load (gf)
n=20 Top surface Dense areaa
0 100 200 300 400 500
200
250
300
350
Micr
ohar
dnes
s (H
V)
Load (gf)
n=20 Top surface Porous areab
Figure 7-3 Effects of applied load on the microhardness of the coating top section a)
dense area, and b) porous area.
Chapter 7 Microhardness study using indentation techniques
108 | P a g e Author: Md. Fahad Hasan
50 100 150 200 250 300100
150
200
250
300
350
400a 50 gf
100 gf 300 gf 500 gf
Micr
ohar
dnes
s (H
V)
Distance from the substrate-coating interface (um)
n=20 Cross-section Dense area
50 100 150 200 250 300100
150
200
250
300b 50 gf
100 gf 300 gf 500 gf
Micr
ohar
dnes
s (H
V)
Distance from the substrate-coating interface (um)
n=20 Cross-section Porous area
Figure 7-4 Effects of applied load and distance from the substrate-coating interface
of the coating on the microhardness a) dense area, and b) porous area (indent
location is presented in Fig. 7-1; 100 and 300 gf data are presented on the x-axis
position of 77, 177, and 277 µm for clear visualisation).
Chapter 7 Microhardness study using indentation techniques
109 | P a g e Author: Md. Fahad Hasan
0 100 200 300 400 500 6000.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Surfa
ce ro
ughn
ess
near
the
horiz
onta
l in
dent
er ti
p (u
m)
Load (gf)
n=20 Top surface Desnse area
Figure 7-5 Effects of applied load on the surface roughness of indenter horizontal tip.
50 100 150 200 250 3000.0
0.2
0.4
0.6
0.8
1.0 50 gf 100 gf 300 gf 500 gf
Surfa
ce ro
ughn
ess
near
the
horiz
onta
l in
dent
er ti
p (u
m)
Distance from the substrate-coating interface (um)
n=20 Cross-section Dense area
Figure 7-6 Effects of applied load and distance from the substrate-coating interface
of coating on the indent roughness (indent location is presented in Fig. 7-1; 100 and
300 gf data are presented on the x-axis position of 77, 177, and 277 µm for clear
visualisation).
Chapter 7 Microhardness study using indentation techniques
110 | P a g e Author: Md. Fahad Hasan
Effects of indenter location on the microhardness and indenter tip 7.3.2.roughness
Figure 7-4 shows the variation of microhardness with the indenter location
throughout the thickness of the coating cross-section. Maximum microhardness is
found on the central location (175 µm) of the cross-section. From Fig. 7-4 (a), it can
be observed that the distribution of microhardness throughout the coatings for 50
and 100 gf shows a similar trend due to the smaller test volume. Similarly, 300 and
500 gf loads exhibit a similar trend due to testing a larger volume that may contain
defects (i.e., pores and cracks).
The coating cross-sections were encased into epoxy mounts. Therefore, in the
following discussions, reference to the coating-epoxy interface implies coating
locations that are near to the coating surface. Coatings are brittle near the two
interfaces of the coatings; i.e., substrate-coating and coating-epoxy interface for
higher loads (300 and 500 gf). Coatings are more brittle near the coating-epoxy
interface position (275 µm) and exhibit low microhardness compared to the position
near the substrate-coating interface (75 µm) for higher loads (300 and 500 gf).
Kuroda et al. [280] also observed similar results for HVOF processes on 316
stainless steel substrates. Increased microhardness observed near the substrate-
coating interface may arise from a strain-hardening effect due to the grit blast
preparation of the substrate [280].
Figure 7-6 reveals the indent location influence on the indent roughness. This
data indicates that indent roughness follows two distinct trends that can be graphed
according to (i) 50 and 100 gf loads, and (ii) 300 and 500 gf loads.
Effects of testing direction 7.3.3.
The microhardness variations on the polished top surface and on the cross-
section are shown in Fig. 7-3 and Fig. 7-4, respectively. Thermal spray coatings
consist of globular and interlamellar flat pores, intralamellar cracks, flat splats, and
partially melted splats, and exhibit microstructural anisotropy. The Vickers indentor
interacts with small flat pores, intralamellar cracks, and thin impact splats on the
cross-section; whereas it interacts with large flattened droplets and pores on the top
surface. As a consequence, microhardness values are higher on the cross-section
Chapter 7 Microhardness study using indentation techniques
111 | P a g e Author: Md. Fahad Hasan
than the top surface of the plasma spray coatings, as has been reported in the
literature [162, 163, 276, 278]. However, plasma spray hydroxyapatite coatings
exhibited fewer pores on the top surface than on the cross-section. Plasma sprayed
hydroxyapatite coating exhibits porosity of 4.1% on the cross-section, as opposed to
3.2% on the top surface. There are some cracks on the cross-section that may have
the effect of reducing microhardness, whereas the top surface exhibits a crack free
coating with a dense area, which may have the effect of increasing the
microhardness.
Top surface microhardness is compared with the central position (175 µm)
microhardness on the cross-section. For 50 and 100 gf indentation in the dense
area, microhardness on the top surface and cross-section shows almost similar
hardness, since the small load does not interact with pores, Figure 7-3 (a) and
Figure 7-4 (a). For 300 and 500 gf loads in the dense area, microhardness on the top
surface are higher compared to the cross-section near the central position (175 µm)
since the top surface has less pores compared to the cross-section, Figure 7-3 (a)
and Figure 7-4 (a). For indentation in a porous area, microhardness on the top
surface exhibits a higher value compared to the cross-section.
Thermal spray coatings are formed by numerous splats stacked together. On the
cross-section of thermal spray coatings, indentations are facing along the thickness
of the splat, which is thin (2-5 µm), Figure 7-1 (b). It is easier for the indentor to
penetrate along this thin splat layer since the bonding of these attached splats is
weak. However, on the top surface, the splat surface area is large and the indentor
breaks this melted top surface, Figure 7-2. Top surface splats also have much more
support from underlying splats due to the large area. Thus, the indentor faces
relatively a hard surface from the top orientation compared to the cross-section
profile.
Rule of mixture 7.3.4.
The combined microhardness was calculated by using the rule of mixture
technique from dense and porous area microhardness values for the top surface and
cross-section, Figs. 7-7 and 7-8. The percentage contributions of dense and porous
area microhardness varied between 75%, 50%, and 25%. It can be seen that
Chapter 7 Microhardness study using indentation techniques
112 | P a g e Author: Md. Fahad Hasan
combined microhardness decreases with the increase of porous area percentage
microhardness. These results indicated that, for comparison of microhardness, it is
necessary to consider similar percentages of microhardness from dense and porous
areas.
0 100 200 300 400 500 600150
200
250
300
350 75 % dense 25% porous area 50% dense and 50% porous area 25% dense and 75% porous area
Micr
ohar
dnes
s (H
V)
Load (gf)
Top surface
Figure 7-7 Combined microhardness on the top surface using rule of mixture for 75%
dense and 25% porous area, 50% dense and 50% porous area, 25% dense and
75% porous area microhardness.
Chapter 7 Microhardness study using indentation techniques
113 | P a g e Author: Md. Fahad Hasan
Figure 7-8 Microhardness on the cross-section calculated using rule of mixture for a)
75% dense and 25% porous area, b) 50% dense and 50% porous area, and c) 25%
dense and 75% porous area microhardness (100 and 300 gf data are presented on
the x-axis position of 77, 177, and 277 µm for clear visualisation).
Weibull modulus analysis 7.3.5.
Weibull modulus measures the variability of material strength. A high Weibull
modulus indicates a low variability in strength, and vice-versa. From Figs. 7-9 and 7-
10, it can be seen that the increases in load lead to an increase in the Weibull
modulus of microhardness. Since a larger load interacts with a large test volume, this
reflects less scattering in the distribution of microhardness data because the
influence of material heterogeneity is less. Similar results are also reported in the
literature [156, 278]. Weibull moduli of microhardness are higher in the dense area
than in the porous area since microhardness values are less scattered in the dense
area.
Chapter 7 Microhardness study using indentation techniques
114 | P a g e Author: Md. Fahad Hasan
0 100 200 300 400 500 600
5
10
15
20
25
Wei
bull m
odul
us o
f micr
ohar
dnes
s
Load (gf)
n=20 Top surface Dense areaa
0 100 200 300 400 500
5
10
15
20
25
Wei
bull m
odul
us o
f micr
ohar
dnes
s
Load (gf)
n=20 Top surface Porous areab
Figure 7-9 Weibull modulus of microhardness on the top surface a) dense area, and
b) porous area.
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115 | P a g e Author: Md. Fahad Hasan
50 100 150 200 250 3000
5
10
15
20
25 50 gf 100 gf 300 gf 500 gf
Wei
bull m
odul
us o
f micr
ohar
dnes
s
Distance from the substrate-coating interface (um)
n=20 Cross-section Dense areaa
50 100 150 200 250 3000
5
10
15
20
25 50 gf 100 gf 300 gf 500 gf
Wei
bull m
odul
us o
f micr
ohar
dnes
s
Distance from the substrate-coating interface (um)
n=20 Cross-section Porous areab
Figure 7-10 Weibull modulus of microhardness on the cross-section a) dense area,
and b) porous area (indent location is presented in Fig. 7-1).
Chapter 7 Microhardness study using indentation techniques
116 | P a g e Author: Md. Fahad Hasan
Figure 7-10 represents the Weibull modulus distribution of microhardness for
different applied loads throughout the coating thickness. Figure 7-10 (a) shows that
the Weibull modulus of microhardness in the dense area, followed similar trends
throughout the coating thickness for lower loads (50 and 100 gf). Similarly, the
Weibull modulus of microhardness for higher loads (300 and 500 gf) exhibited similar
trends throughout the coating thickness.
Maximum and minimum Weibull modulus of microhardness on the cross-section
of dense area was found to be 21 and 6.3, close to the substrate-coating interface
position for 300 and 50 gf, respectively. Maximum and minimum Weibull modulus of
microhardness on the cross-section of the porous area are 10.2 on the centre
position and 4.4 close to the substrate-coating interface position for 500 and 100 gf,
respectively. Lima et al. [278] reported a Weibull modulus of 20 for titania coatings
with 300 gf on the cross-section. From Fig. 7-10, it can be concluded that the high
Weibull modulus of microhardness depends not only on the base material, but is also
related to the applied load and the indent position.
7.4. Microhardness study using Knoop indentation
Indentations were performed on the cross-section of coatings at locations of 75,
175, and 275 µm away from the substrate-coating interface, Figure 7-11. On the
cross-section, indentations were carried out with the major diagonal at an angle of
0⁰, 45⁰, and 90⁰ with respect to the spray direction. Indentation angle is considered
as the angle between the major diagonal and the substrate-coating interface.
Instead of optical micrograph images connected with the microhardness tester, a
high magnification scanning electron microscopy (SEM) picture was used for
measuring microhardness and elastic modulus to reduce the error in measurement.
The distance between each indentation was at least three times the minor diagonal
and two times the major diagonal to avoid any interference from the superposition of
stress fields [281].
Twenty readings were taken randomly along each region of interest with respect
to indentation angle, testing direction, measurement location, and applied load.
Microhardness data were then adjusted by subtracting the two largest and two
smallest readings to represent data for typical material properties that documented
Chapter 7 Microhardness study using indentation techniques
117 | P a g e Author: Md. Fahad Hasan
outliers. These outlier data points may arise from high or low porosity regions of the
microstructure, which are unrepresentative structures of the material.
Figure 7-11 Schematic of Knoop indentation at different indent location within typical
thermal spray coatings microstructure.
Microhardness measured at 0⁰, 45⁰, and 90⁰ indentation angles are denoted as
H0, H45, and H90, respectively. Similarly, elastic modulus measurements are denoted
as E0, E45, and E90, respectively. Weibull moduli of microhardness and elastic
Chapter 7 Microhardness study using indentation techniques
118 | P a g e Author: Md. Fahad Hasan
modulus are denoted as mH and mE, respectively. For clear visualisation of the graph,
100 and 300 gf data are presented (Fig. 7-12) by adding an extra 2⁰ on the x-axis
position, i.e., 2⁰, 47⁰,92⁰. Similarly, 2 µm are added on the x-axis position for Fig. 7-
14, i.e., 77, 177, 277 µm.
Effects of indentation angle on the microhardness and elastic modulus 7.4.1.
Figure 7-12 shows the effect of indentation angle on microhardness and elastic
modulus. The dependence of microhardness and elastic modulus on the indentation
angle exhibits a parabolic shape. Maximum microhardness is found at a 45⁰
indentation angle for all applied loads (50, 100, 300, and 500 gf) on the coating
cross-sections. A similar effect is revealed for the elastic modulus.
Figure 7-12 Distributions of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted
data) with change of indentation angle with the substrate-coating interface
(indentation angle is presented in Fig. 7-11; 100 and 300 gf data are presented on
the x-axis position at 2⁰, 47⁰,92⁰ for clear visualisation).
Chapter 7 Microhardness study using indentation techniques
119 | P a g e Author: Md. Fahad Hasan
For H0, since the major diagonal of the indenter is parallel to the substrate-coating
interface, it covers fewer lamellae that are also parallel to the substrate-coating
interface. For H90, the major diagonal of the indenter is perpendicular to the
substrate-coating interface; therefore, it covers the boundaries of several lamellae
along the thickness. For H45, the major diagonal of the indenter is at 45⁰ with the
substrate-coating interface, and it may cover several lamellae (giving more extensive
coverage than that of the 0⁰ angle) and fewer lamellae boundaries than the indenter
faces at 90⁰ angle. These two effects in combination may increase the
microhardness of H45 compared to the other microhardness values of H0 and H90.
Figure 7-11 (b) illustrates these features clearly.
It is interesting to note that the dependence of the microhardness values on the
indentation angle follows Pythagoras’ theorem that can be presented as:
2 2 245 0 90(H ) (H ) (H )= + (32)
The calculated values according to Pythagoras’ theorem and the measured
values at an indentation angle of 45⁰ show good agreement with a maximum 16%
error, Table 7-2. The percentage error may result from the variation in microstructure
and the accuracy of the indentation angle.
Table 7-2 Comparison of microhardness data with Pythagoras’ theorem.
Load (gf)
Microhardness with
indentation parallel to the
substrate-coating
interface, H0, (KHN) n=20
Microhardness with
indentation perpendicular
to the substrate-
coating interface, H90
(KHN) n=20
Microhardness with
indentation at 45º angle to
the substrate-coating
interface, H45 (KHN) n=20
Microhardness calculated
according to Pythagoras’
theorem (KHN)
Difference between
calculated and
measured data (%)
50 282±37 289±42 340±43 404 16
100 223±28 236±34 289±35 325 11
300 195±19 210±21 248±20 287 14
500 174±14 193±21 237±18 260 9
Chapter 7 Microhardness study using indentation techniques
120 | P a g e Author: Md. Fahad Hasan
Figure 7-12 (a) and (c) shows a graph with original data, whereas Fig. 7-12 (b) and (d) shows a graph with adjusted data. The adjusted graph shows a much clearer
picture since it is plotted without outliers. Similar results are seen for Figs. 7-13 and
7-14.
Figure 7-13 Distributions of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted
data) with change of testing directions and applied loads.
Effects of testing direction on the microhardness and elastic modulus 7.4.2.
Comparisons of microhardness and elastic modulus of the coating on the top surface
and cross-section for different applied loads are shown in Fig. 7-13. It can be seen
that microhardness and elastic modulus value are higher on the top surface than the
cross-section. The top surface of the coating is dense and almost crack free,
whereas the cross-section exhibits cracks, Figure 7-2. A lower porosity of 3.2% was
Chapter 7 Microhardness study using indentation techniques
121 | P a g e Author: Md. Fahad Hasan
found on the top surface compared to 4.1% on the cross-section. These cracks and
pores may reduce microhardness and elastic modulus values on the cross-section.
Figure 7-14 Distributions of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic modulus
(adjusted data) at different locations on the cross-section (indent location is
presented in Fig. 7-11; 100 and 300 gf data are presented on the x-axis position
of 77, 177, and 277 µm for clear visualisation).
These obtained results are in good agreement with those of Saeed et al.’s [131],
who reported higher microhardness values on the top surface for flame sprayed HA
coatings compared to the cross-section using a nano-indentation technique.
However, Li et al. [170] reported higher microhardness on the cross-section
compared to the top surface for plasma sprayed Cr3C2-NiCr coatings using Knoop
indentation. This difference in observation may be due to the different materials
investigated since they exhibit different microstructures. In addition, porosity values
Chapter 7 Microhardness study using indentation techniques
122 | P a g e Author: Md. Fahad Hasan
on the top surface and cross-section may have a significant effect on the
microhardness.
Elastic modulus values of thermal spray coatings depend on porosity,
interlamellar boundaries and intralamellar cracks. The effect of spherical shaped
pores on the elastic modulus can be expressed as [282]:
05a 3E E 1 ( )P4c 4
= − + (33)
where P is the porosity, c is the axis that is parallel to the stress direction, a is the
axis in the plane that is perpendicular to the axis c, and E0 is the elastic modulus for
a zero porosity material.
Equation 33 indicates that materials that have spherical pores decrease elastic
modulus values. Interlamellar boundaries and intralamellar cracks can be assumed
as pores that may have a detrimental effect on elastic modulus values. According to
equation 33, the elastic modulus will be higher on the top surface than on the cross
section. The apparent high density of the surface Knoop measurements may be
attributed to the small sampling depth and less likelihood of encountering volume
defects.
Effects of indent location on the microhardness and elastic modulus 7.4.3.
The microhardness and elastic modulus variations on the cross-sections at
different locations and applied loads throughout the coating thickness are shown in
Fig. 7-14. Microhardness and elastic modulus decrease with increased applied loads
since this leads to a larger indentation area. A smaller area contains small pores
whereas a large area covers a combination of several large and small pores that
may have a detrimental effect on the microhardness and elastic modulus with an
increase in applied load. Microhardness distributions follow a parabolic trendline for
all applied loads with different locations. Microhardness reaches a maximum at the
central position (175 µm) of the coatings.
Elastic modulus distributions follow a parabolic trendline for lower loads (50 and
100 gf). However, higher load (300 and 500 gf) shows on almost constant elastic
modulus. A small load samples only a small area and produces a small indentation
Chapter 7 Microhardness study using indentation techniques
123 | P a g e Author: Md. Fahad Hasan
depth, leading to minor local variation in microstructure. On the other hand, high load
samples a large area and penetrate a large indentation depth. Small indentation
depth produces a short minor diagonal, whereas a large penetration depth produces
a greater minor diagonal.
It is recommended to use high magnification pictures for measuring elastic
modulus, especially for lower loads (50 and 100 gf); since the lower load produces a
short minor diagonal that may lead to measurement errors at lower magnification.
Weibull modulus analysis for microhardness and elastic modulus 7.4.4.
Variability of data in relation to mechanical properties can be determined by the
Weibull modulus measurement. Figure 7-15 shows the effect of indentation angle on
the Weibull modulus of microhardness (mH) and elastic modulus (mE). It can be seen
that maximum mH and mE values are found at a 45⁰ indentation angle in most of the
cases. These values indicate that H45 and E45 data are less variable.
Figure 7-16 demonstrates the dependence of mH and mE values on the testing
direction. The mH and mE values are varied and not really distinguishable with
respect to the top surface and cross-section.
Figure 7-17 reveals the mH and mE on the cross-section at different locations
throughout the coating thickness. Maximum values of mH and mE are found at the
central position (175 µm) of the coatings.
Figures 7-15 to 7-17 indicate that increasing applied loads increases the values of
mH and mE, since a low load covers a small area, and the data obtained become
scattered. With an increase in the applied load, the area covered by the indenter is
greater, and the data obtained become less scattered, which improves the Weibull
modulus.
Also, Figs. 7-15 to 7-17 indicate that the adjusted data show higher Weibull
modulus values than the original data, due to the removal of outliers. The Weibull
modulus of microhardness and elastic modulus for original data are in the range of
6.3-13.4 and 1.8-4.1, respectively; whereas for adjusted data, they are in the range
of 9.1-20.5 and 2.1-4.1, respectively. From these results, it can be seen that the
Weibull modulus of microhardness improved considerably with the adjusted data,
Chapter 7 Microhardness study using indentation techniques
124 | P a g e Author: Md. Fahad Hasan
since outliers were removed based on the microhardness results, whereas the
Weibull modulus of elastic modulus shows little change.
Figure 7-15 Weibull modulus of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted
data) with different indentation angles (indentation angle is presented in Fig. 7-11).
Chapter 7 Microhardness study using indentation techniques
125 | P a g e Author: Md. Fahad Hasan
Figure 7-16 Weibull modulus of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted
data) with change of testing directions.
Elastic modulus values are more scattered than microhardness values, since mH
values are found in the range of 6.3 to 13.4 (for original data), while mE are in the
range of 1.8 to 4.1 (for original data). These results indicate a high Weibull modulus
for microhardness compared to the elastic modulus. This observation is in good
agreement with that of Li et al. [170]. There are some exceptional cases that arose
for Weibull modulus values where a few of the latter showed different values
compared to other characteristic trendlines, which may have been due to the
variation of sample polishing.
Chapter 7 Microhardness study using indentation techniques
126 | P a g e Author: Md. Fahad Hasan
Figure 7-17 Weibull modulus of (a) microhardness (original data), (b) microhardness
(adjusted data), (c) elastic modulus (original data), and (d) elastic modulus (adjusted
data) on the cross-section (indent location is presented in Fig. 7-11).
Depth of indentation 7.4.5.
Change of depth of indentation with respect to indentation angle, testing direction,
and indent location are presented in Figs. 7-18 to 7-20. From Figs. 7-18 and 7-20, it
can be seen that the depth of indentation is almost unchanged for 50 and 100 gf with
respect to the change of indentation angle and indentation location, whereas for 300
and 500 gf shows variation and also indicate that 45 º indentation angle and indent
location at the centre (i.e., 175 µm) of the coating shows minimum indentation depth.
Figure 7-19 indicates that the depth of indentation is small for the top surface
compared to the cross-section since top surface has much more support from
underlying layer compared to the cross-section (described in Section 7.3.3).
Chapter 7 Microhardness study using indentation techniques
127 | P a g e Author: Md. Fahad Hasan
0 20 40 60 80 100
2
4
6
8
10Cross-section 50 gf
100 gf 300 gf 500 gf
Dep
th o
f ind
enta
tion
(um
)
Indentation angle (degree)
n=20
Figure 7-18 Depth of indentation variation with change of indentation angles
(indentation angle is presented in Fig. 7-11).
0 100 200 300 400 500 600
2
4
6
8
10 Cross-section Top surface
Dep
th o
f ind
enta
tion
(um
)
Load (gf)
n=20
Figure 7-19 Depth of indentation variation with change of testing directions.
Chapter 7 Microhardness study using indentation techniques
128 | P a g e Author: Md. Fahad Hasan
75 175 2750
2
4
6
8
10 50 gf 100 gf 300 gf 500 gf
Dep
th o
f ind
enta
tion
(um
)
Distance from the substrate-coating interface (um)
Cross-sectionn=20
Figure 7-20 Depth of indentation variation with change of indent locations on the
cross-section (indent location is presented in Fig. 7-11).
Frequency distribution 7.4.6.
Frequency plots of Knoop microhardness (original data) are shown in Figs. 7-21
and 7-22 with respect to the cross-section and top surface. From all these graphs, it
can be seen that a bimodal distribution may exist for smaller loads (i.e., 50 and 100
gf), whereas it cannot be clearly distinguished for higher loads (i.e., 300 and 500 gf).
Valente et al. [156] and Lin et al. [142] also reported similar results.
Chapter 7 Microhardness study using indentation techniques
129 | P a g e Author: Md. Fahad Hasan
160 200 240 280 320 3600
1
2
3
4
5
6
7
8
9
Freq
uenc
y co
unts
Microhardness (HV)
50 gf 100 gf 300 gf 500 gf
Cross-section (175 um)n=20
Figure 7-21 Frequency distribution of microhardness on the cross-section at the
centre (175 µm) of the coatings.
160 200 240 280 320 360 4000
2
4
6
8
10
12
Freq
uenc
y co
unts
Microhardness (HV)
50 gf 100 gf 300 gf 500 gf
n=20 Top surface
Figure 7-22 Frequency distribution of microhardness on the top surface.
Chapter 7 Microhardness study using indentation techniques
130 | P a g e Author: Md. Fahad Hasan
Student’s t-test 7.4.7.
Student’s t-test results for the top surface and cross-section with original data and
adjusted data are presented in Tables 7-3 and 7-4. Student’s t-test determines the
probability of whether two sets of data are completely different or not. It also allows
examination of whether a null hypothesis exists or not, based on the probability
value. If the probability value is less than 0.05, then a null hypotheses can be
rejected. T stat values suggest the similarity of two data sets. A higher T stat value
indicates a completely different data set.
From Tables 7-3 and 7-4, it can be seen that T stat values are higher for load 50
vs. 500 gf and lower for load 300 vs. 500 gf. These figures explain that a load of 50
and 500 gf show completely different data sets whereas loads of 300 and 500 gf
show close data sets. The probability values for load 300 vs. 500 gf show greater
than 0.05 in most of the cases whereas other load comparisons show less than 0.05.
These also indicate that the data sets for loads of 300 and 500 gf are similar,
whereas others data sets may be different from one another.
Table 7-3 Student’s t-test for the microhardness on the top surface with original
(n=20) and adjusted data (n=16).
Load (gf) T stat Probability
Original data
(n=20)
Adjusted data
(n=16)
Original data
(n=20)
Adjusted data
(n=16) 50 vs. 100 3.59 3.63 0.0009 0.0010 50 vs. 300 7.01 7.88 ˂ 0.0001 ˂ 0.0001 50 vs. 500 8.28 9.33 ˂ 0.0001 ˂ 0.0001
100 vs. 300 3.50 4.48 0.0012 0.0001 100 vs. 500 4.90 6.26 ˂ 0.0001 0.0007 300 vs. 500 1.54 2.77 0.1301 0.0094
Chapter 7 Microhardness study using indentation techniques
131 | P a g e Author: Md. Fahad Hasan
Table 7-4 Student’s t-test for the microhardness on the cross-section with original
(n=20) and adjusted (n=16) data.
H90 and H45 indicates indentation angles of 90º and 45º with the substrate-coating٭
interface
Load (gf)
Indent distance from the
substrate-coating interface (µm) or
indentation angles (º)
T stat Probability
Original data
(n=20)
Adjusted data
(n=16)
Original data
(n=20)
Adjusted data
(n=16)
50 vs. 100
75 6.45 8.61 ˂ 0.0001 ˂ 0.0001 175 5.67 6.87 ˂ 0.0001 ˂ 0.0001 275 3.46 4.45 0.0013 0.0001
H90 (٭) 0.0001 ˂ 0.0001 ˂ 6.11 4.37 H45 (٭) 0.0002 0.0005 4.13 3.78
50 vs. 300
75 8.68 11.51 ˂ 0.0001 ˂ 0.0001 175 9.30 10.63 ˂ 0.0001 ˂ 0.0001 275 8.51 10.21 ˂ 0.0001 ˂ 0.0001 H90 7.48 8.96 ˂ 0.0001 ˂ 0.0001 H45 7.75 9.62 ˂ 0.0001 0.0002
50 vs. 500
75 10.94 14.22 ˂ 0.0001 ˂ 0.0001 175 12.23 13.84 ˂ 0.0001 ˂ 0.0001 275 9.12 10.78 ˂ 0.0001 ˂ 0.0001 H90 9.04 11.05 ˂ 0.0001 ˂ 0.0001 H45 8.70 10.77 ˂ 0.0001 ˂ 0.0001
100 vs. 300
75 1.96 2.18 0.0570 0.0366 175 3.73 4.91 0.0006 ˂ 0.0001 275 5.44 6.84 ˂ 0.0001 ˂ 0.0001 H90 2.90 4.73 0.0061 ˂ 0.0001 H45 4.63 5.25 ˂ 0.0001 ˂ 0.0001
100 vs. 500
75 4.43 5.15 ˂ 0.0001 ˂ 0.0001 175 7.14 9.39 ˂ 0.0001 ˂ 0.0001 275 6.02 7.44 ˂ 0.0001 ˂ 0.0001 H90 4.79 8.58 ˂ 0.0001 ˂ 0.0001 H45 5.87 6.49 ˂ 0.0001 ˂ 0.0001
300 vs. 500
75 2.85 3.79 0.0068 0.0006 175 4.03 4.46 0.0002 0.0001 275 0.19 0.07 0.8440 0.9386 H90 2.59 3.89 0.0135 0.0005 H45 1.68 1.67 0.1001 0.1063
Chapter 7 Microhardness study using indentation techniques
132 | P a g e Author: Md. Fahad Hasan
Effects of indentation on the microstructure 7.4.8.
The effects of indentation with an applied load of 100 gf on the cross-section of
coatings microstructure are shown in Fig. 7-23. There is evidence of splat movement
or possibly ductile plastic deformation or tearing. Figure 7-23 (a, b) shows
indentation without splat movement whereas Fig. 7-23 (c, d, e, f) shows evidence of
splat movement. It also shows that the indentation without splat movement (Fig. 7-23
(a, b)) exhibit higher microhardness values than the indentation with splat movement
(Fig. 7-23 (c, d, e, f)). The splat movement may occur due to the splat corners being
loosely connected and therefore liable to break during the indentation measurement.
Figure 7-23 Indentation on the cross-section of the coatings at the centre position
(175 µm) with an applied load of 100 gf (a, b) without splat movement, and (c, d, e, f)
with splat movement (‘HK’ indicates Knoop microhardness value and ‘a’ indicates
major diagonal length of Knoop indentation).
7.5. Summary
The microhardness of plasma sprayed HA coatings was measured using Vickers
indentation with respect to testing direction, different applied load, and indent
location. Dense and porous areas throughout the coating thickness were taken into
accounts that are related to the microstructure and anisotropic behaviour of the
coatings. Also, indent roughness at the tip after Vickers indentation was measured to
establish the effects of indentation on the coatings. Statistical analyses were used to
determine the reliability and variability of the measured data. The following
conclusions can be drawn from this Vickers indentation study:
Chapter 7 Microhardness study using indentation techniques
133 | P a g e Author: Md. Fahad Hasan
1. Loads of 50 and 100 gf, as well as 300 and 500 gf, show similar effects on
the microhardness, indent roughness and Weibull modulus of
microhardness throughout the coating thickness in the dense area. Loads
of 50 and 100 gf present microhardness information on a small volume of
the coatings for almost pore free areas; whereas loads of 300 and 500 gf
show microhardness information on a large volume of the coating that
contains defects (i.e., pores and cracks).
2. Coatings are brittle near the two interface positions (i.e., substrate-coating
and coating-epoxy interface) of the coatings for higher loads (300 and 500
gf). Coatings are more brittle near the coating-epoxy interface position (275
µm) and exhibit low microhardness compared to the position near the
substrate-coating interface (75 µm) of the coatings at higher loads (300 and
500 gf). This effect is due to strain-hardening that may arise during grit
blast preparation of the substrate.
3. Indent roughness increases as the load increases since a higher load
increases the crack on the two horizontal tips.
4. The combined microhardness calculated from a rule of mixtures decreases
with an increase of porous percentage area microhardness. These
measurements indicated that, for comparison of microhardness results, it is
necessary to consider similar percentages of microhardness from dense
and porous areas.
5. Weibull modulus values of microhardness are higher in the dense area than
in the porous area, since microhardness values are less scattered in the
dense area. The Weibull modulus of microhardness depends not only on
the base material but is also related to the applied load and indent position,
since the Weibull modulus value changes with change in applied load and
indent position.
The microhardness and elastic modulus of plasma sprayed HA coatings were
investigated in terms of indentation angle, testing direction, different applied load,
and indent location throughout the coating thickness using Knoop indentation.
Chapter 7 Microhardness study using indentation techniques
134 | P a g e Author: Md. Fahad Hasan
Statistical analyses were used to study the variability of the measured data. The
following conclusions can be drawn from this Knoop indentation study:
1. The dependence of microhardness and elastic modulus on the indentation
angle is a parabolic curve. Maximum microhardness and elastic modulus
were found at 45⁰ indentation angle. H0, H45 and H90 values are found to
approximately satisfy Pythagoras’ theorem.
2. Microhardness and elastic modulus is higher on the top surface than the
cross-section, since the top surface is less porous and is almost crack free
compared to the cross-section of the coatings.
3. Microhardness distribution follows a parabolic trendline for all applied loads
at different locations on the cross-section. Maximum microhardness is
found in the central position (175 µm) of the coating’s cross-section. Elastic
modulus values are almost constant on the coating cross-section for higher
loads (300 and 500 gf), since the area of measurement is greater and the
minor diagonal is long enough compared to the lower loads (50 and 100
gf). However, elastic modulus shows a variation along the coating thickness
for lower loads (50 and 100 gf).
4. Microhardness and elastic modulus decreases with increasing applied
loads, since the increase in applied load increases the indenter testing area
that covers more large and small pores, which, in turn, may decrease the
microhardness and elastic modulus.
5. On the cross-section, the maximum Weibull modulus of microhardness
(mH) and elastic modulus (mE) are found at the central position (175 µm) of
the coatings.
6. Depth of indentation remains almost unchanged on the cross-section with a
change of indent location for lower loads (50 and 100 gf). This depth shows
variation changes for higher loads (300 and 500 gf). An increase in applied
load increases the depth of indentation.
7. The frequency distribution of Knoop microhardness indicates that a bimodal
distribution may exist for smaller loads (i.e., 50 and 100 gf), whereas it
cannot be clearly distinguished for higher loads (i.e., 300 and 500 gf).
Chapter 7 Microhardness study using indentation techniques
135 | P a g e Author: Md. Fahad Hasan
8. Student’s t-test demonstrates that T stat values are higher for load 50 vs.
500 gf and lower for load 300 vs. 500 gf. The probability values for load 300
vs. 500 gf show greater than 0.05 in most of the cases, whereas other load
comparisons show less than 0.05. These statistical results indicate that
data sets for loads of 300 and 500 gf are similar; whereas other data sets
may be different from one another.
9. Splat movement evidence was visible due to the indentation on the
microstructure.
10. It is recommended to use high magnification SEM picture for measuring
elastic modulus, especially for lower loads (50 and 100 gf) to overcome the
measurement error of the minor diagonal.
Chapter 8 Sol-gel modified thermal spray coatings
136 | P a g e Author: Md. Fahad Hasan
8. Sol-gel modified thermal spray coatings
8.1. Introduction
HA has been widely studied and clinically applied for bone substitution and bone
reconstruction in the human skeletal system. This is due to it possessing the crystal
structure and chemical composition identical to apatite, which makes it suitable for
such applications [205]. It has attracted promising interest in areas such as bioactive
and biocompatible coatings on metal implants in dentistry, maxillofacial surgery,
bone filler and orthopaedics [24, 205, 283-287]. Clinical observation of coatings has
indicated failure by chipping, spalling, delamination and dissolution for explanted
endoprostheses due to the brittle nature of HA coatings [257].
Among several deposition techniques, thermal spray, in particular plasma spray,
is very popular for depositing HA coatings. Plasma spraying of HA offers good
mechanical properties with superior osteoconductivity of HA [272] . However, plasma
spray coatings contain cracks, pores and residual stress that reduce the durability,
mechanical properties and can results in partial or complete delamination of the
coatings. On the other hand, pores and cracks are beneficial for bone growth. Thus,
a novel technique was applied to fulfil these two conflicting requirements.
Sol-gel coatings were applied onto the thermal spray coating to fill up the pores
and cracks; and thereby strengthen the mechanical properties. These sol-gel
coatings could also act as an active top layer, as shown in Fig. 8-1. These active top
layers could dissolve more quickly within the body due to their poor adhesion
compared to the thermal spray coating. They could, thus, provide calcium and
phosphate ions; which have been reported to increase the bone growth on the
coating surface [288].
Figure 8-1 Sol-gel modified thermal spray coatings with active top layer.
Chapter 8 Sol-gel modified thermal spray coatings
137 | P a g e Author: Md. Fahad Hasan
8.2. Methodology
Typical thermal sprayed HA coatings were prepared by using plasma spray
parameters, as shown in Table 8-1. These typical thermal spray coatings were
modified by sol-gel HA solution. Sol-gel HA solution was prepared by dissolving pure
HA powder into dilute nitric acid. Dilute nitric acid was prepared by mixing 3.2 ml of
nitric acid with 50 ml of distilled water and then it was stirred for 30 minutes using a
magnetic stirrer. Then, 3 g of HA powder was mixed with dilute nitric acid and further
stirred for 1 hour. In the next step, 1 g of HA powder was added and stirred for 1
hour and this step was repeated once. The concentration of HA in the solution
became 0.2 M. Then, the thermal spray HA coating sample (20×10 mm) was dipped
into the prepared solution and withdrawn slowly after 1 min. The as-dipped liquid
coating was dried in a vacuum hood for 3 hours, after which, it was heated using an
air furnace at 200 ºC for 2 hours and subsequently cooled to room temperature.
A sol-gel modified thermal spray sample was sectioned into small pieces and
then ground and polished to remove the scratches. Grinding (grit sizes P600, P800,
P1200) and polishing (15, 5, and 1 µm) was performed with care so that the sol-gel
coatings were subjected to minimal effects during the metallographic preparation.
However, evidence was seen on the cross-section that indicated delamination of the
sol-gel coatings.
As a result, a thin gold coating (200 nm thicknesses) was deposited on the dried,
as-dipped sol-gel modified sample top surface using a DC magnetron sputtering
(CMS 18 Kurt J Lesker-USA sputtering unit) to protect the sol-gel coatings from
delamination during metallographic preparation. The base pressure was set at 5x10-8
torr with an argon gas flow rate of about 40 sccm. The working pressure was 4 x10-3
torr and the power was 150 W. Samples were examined by SEM after 3 days and 7
days of sol-gel treatment.
Chapter 8 Sol-gel modified thermal spray coatings
138 | P a g e Author: Md. Fahad Hasan
Table 8-1 Plasma spray parameters.
Parameters Value Power (kW) 40
Primary gas flow rate, Ar (slpm) 50 Secondary gas flow rate, He (slpm) 12
Carrier gas flow rate, Ar (slpm) 7 Powder feed rate (g/min) 27 Stand-off distance (cm) 11
8.3. Effects of sol-gel coatings on microstructure improvement
Figure 8-2 demonstrates that a typical thermal spray coating surface consists of
melted lamellae and partially melted lamellae. Figure 8-3 and Fig. 8-4 shows the top
surface of sol-gel modified thermal spray coatings after 3 days and 7 days of sol-gel
treatment, respectively. Figure 8-3 indicates a variation in several shapes on the top
surface; whereas Fig. 8-4 shows the final stage of the top surface after completion of
crystal growth.
Figure 8-3 (a) shows the dried sol-gel solution with evidence of several HA
particle shapes and Fig. 8-3 (b) shows evidence of crystal growth on the top surface
with the presence of spherical HA particles. Figure 8-3 (c) exhibits thin top layers that
cover the whole coating, which could be the previous stage of crystallization or the
start of the crystallization step. The reasoning here is that, Fig. 8-3 (d) shows the
existence of a thin layer that covers the coating and crystal growth of the coatings
together. This morphology indicates that some thin layers could already have been
converted to crystal and that some regions are under a thin top layer that is still in
the process of crystal growth.
Figure 8-3 shows the top surface after 7 days from the sol-gel treatment day,
which indicates that crystallization processes are complete on the top surface.
Crystallization of the top surface occurs in a normal temperature range. Some
spherical particles, which could be partially dissolved or undissolved HA particles,
are visible on the top surface. Also, evidence of platelet particles and crystal growth
are discerned on the top surface.
Chapter 8 Sol-gel modified thermal spray coatings
139 | P a g e Author: Md. Fahad Hasan
Figure 8-2 Typical thermal spray coatings top surface.
Figure 8-3 Sol-gel modified thermal spray coating top surface morphology after 3
days from the sol-gel treatment day.
Chapter 8 Sol-gel modified thermal spray coatings
140 | P a g e Author: Md. Fahad Hasan
Figure 8-4 Sol-gel modified thermal spray coating top surface after 7 days from the
sol-gel treatment day.
Figure 8-5 represents a typical thermal spray coating cross-section with many
pores and cracks. In comparison, Fig. 8-6 shows a sol-gel modified thermal spray
coating with fewer pores and almost crack free coatings since the sol-gel solution
can penetrate to the thermal spray coating that fills the pores and cracks. However,
there is a large gap that exists at the coating-epoxy interface, as shown in Fig. 8-6.
From Fig. 8-3, it can be seen that the top surface shows some partially dissolved
spherical particles and some platelet particles. During polishing of the cross-section
of the sol-gel modified thermal spray coatings, these particles could be removed
from the surface which would evolve small gaps between the coating and epoxy.
Due to these small gaps, the rest of the sol-gel layer coating may be removed from
Chapter 8 Sol-gel modified thermal spray coatings
141 | P a g e Author: Md. Fahad Hasan
the coating-epoxy interface during polishing and, therefore create the large gap
between the epoxy and the coating.
Figure 8-7 shows a cross-section image after sol-gel treatment on the thermal
spray coatings. Thin sol-gel coating layers with few HA particles are visible in Fig. 8-
7. HA particles in the sol-gel coatings are denoted as ‘particle’ and sol-gel coatings
formed from sol-gel solution are denoted as ‘sol-gel solution’ in this chapter.
Figure 8-5 Typical thermal spray coating cross-section.
Figure 8-6 Sol-gel modified thermal spray coating cross-section.
Chapter 8 Sol-gel modified thermal spray coatings
142 | P a g e Author: Md. Fahad Hasan
Figure 8-7 Sol-gel modified thermal spray coating cross-section after using gold
coatings by PVD technique on the top surface of the sample.
8.4. Coating properties
Porosity 8.4.1.
Comparisons of porosity variation for thermal spray coatings and sol-gel modified
thermal spray coatings are presented in Fig. 8-8 with respect to the different coating
areas (i.e., coating-epoxy, coating-centre, and substrate-coating area). Porosity was
reduced the most near the coating-epoxy interface area; since the sol-gel solution
can penetrate most at this location. Porosity of sol-gel modified thermal spray
coatings increased as the measurement position moved from the coating-epoxy
interface to the substrate-coating interface. The sol-gel solution penetration
decreased with the increase in distance from the surface. Sol-gel modified thermal
spray coatings showed 54% less total porosity than the porosity of the total typical
thermal spray coatings.
Chapter 8 Sol-gel modified thermal spray coatings
143 | P a g e Author: Md. Fahad Hasan
Coating-epoxy Coating-centre Substrate-coating Overall porosity2
3
4
5
6 Typical thermal spray coatings Sol-gel modified thermal spray coatings
Poro
sity
(%)
Porosity position
n=10
Figure 8-8 Porosity variation for typical thermal spray coatings and sol-gel modified
thermal spray coatings throughout the coating’s thickness.
Microhardness 8.4.2.
Microhardness variations of the typical thermal spray coatings and sol-gel
modified thermal spray coatings for loads of 50, 100, 300 gf are shown in Fig. 8-9.
Indentations were performed on the cross-section of the coatings at locations of 75,
175, and 275 µm distance from the substrate-coating interface, and microhardness
distributions throughout the coatings were investigated. In Fig. 8-9, microhardness
values for the sol-gel modified thermal spray coatings are presented at 77, 177, and
277µm positions for convenience of interpretation. For all applied loads and indent
locations, sol-gel modified thermal spray coatings exhibit a higher microhardness
than typical thermal spray coatings. For 50 and 100 gf loads, sol-gel modified
thermal spray coatings reveal a smaller error bar than that of thermal spray coatings.
However, for 300 gf loads, sol-gel modified thermal spray coatings exhibit a larger
error bar than typical thermal spray coatings. At higher load (300 gf), sol-gel coatings
may break abnormally or polishing may be affected, both of which may increase the
error bar.
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144 | P a g e Author: Md. Fahad Hasan
Figure 8-9 Microhardness variation for typical thermal spray coatings and sol-gel
modified thermal spray coatings throughout the coatings thickness with load of (a) 50
gf, (b) 100 gf, and (3) 300 gf (sol-gel modified coatings microhardness data are
presented on the x-axis position of 77, 177, and 277 µm for clear visualisation).
Surface roughness 8.4.3.
Surface roughness values (n = 10) of sol-gel modified thermal spray coatings and
typical thermal spray coatings are 7.1±0.5 and 7.8±0.9 µm, respectively. So, sol-gel
modified coatings show 9% less surface roughness.
Weibull modulus analysis for coating properties 8.4.4.
Variations of data are measured by the Weibull modulus. Figure 8-10 shows the
comparison of the Weibull modulus of microhardness within the coatings for typical
thermal spray coatings and sol-gel modified thermal spray coatings with applied
loads of 50, 100, and 300 gf. Lower loads (50 and 100 gf) reveal a high Weibull
modulus, whereas higher loads (300 gf) show a low Weibull modulus for the sol-gel
Chapter 8 Sol-gel modified thermal spray coatings
145 | P a g e Author: Md. Fahad Hasan
modified thermal spray coatings compared to the typical thermal spray coatings. It
could be that lower loads could not fracture the sol-gel coatings due to the lower
applied force, whereas at higher loads, sol-gel coatings could fail abnormally; this
resulting in a large variation in the data. Maximum Weibull moduli are found at the
central position (175 µm) of the coatings for all applied loads.
Figure 8-11 shows the comparative Weibull modulus of porosity, which is higher
for sol-gel modified thermal spray coatings than for typical thermal spray coatings.
Weibull modulus of surface roughness for typical thermal spray coatings and sol-gel
modified thermal spray coatings are 9.6 and 14.5, respectively.
Figure 8-10 Comparison of Weibull modulus of microhardness on the cross-section
of typical thermal spray coatings and sol-gel modified thermal spray coatings with
applied loads of (a) 50 gf, (b) 100 gf, and (c) 300 gf.
Chapter 8 Sol-gel modified thermal spray coatings
146 | P a g e Author: Md. Fahad Hasan
Coating-epoxy Coating-centre Substrate-coating Overall porosity0
4
8
12
Typical thermal spray coatings Sol-gel modified thermal spray coatings
Wei
bull m
odul
us o
f por
osity
Porosity position
n=20
Figure 8-11 Comparison of Weibull modulus of porosity for typical thermal spray
coatings and sol-gel modified thermal spray coatings.
8.5. Phase structure and crystallinity
Figure 8-12 depicts the XRD patterns of typical thermal spray coatings and sol-
gel modified thermal spray coatings. The peak intensities are higher with very few
peak shifts after sol-gel modification of thermal spray coatings. This high peak
intensity increases the crystallinity of the coatings. The crystallinity values of typical
thermal spray coatings and sol-gel modified thermal spray coatings are 48% and
53%, respectively. Thus, sol-gel modified thermal spray coatings reveal a 10%
improvement in crystallinity.
Chapter 8 Sol-gel modified thermal spray coatings
147 | P a g e Author: Md. Fahad Hasan
20 25 30 35 40 45 50 55 60 65 70
2 theta
Typical thermal spray coatings Sol-gel modified thermal spray coatings
Inte
nsity
Figure 8-12 Comparison of XRD spectra for typical thermal spray coatings and sol-
gel modified thermal spray coatings.
Raman spectra
Raman shift spectra for typical thermal spray coatings and sol-gel modified
thermal spray coatings with PO4 and OHˉ bands are presented in Fig. 8-13. Table 8-
2 shows the comparison of full width at half maximum (FWHM) for PO4 and OHˉ
bands. For both PO4 and OHˉ band, FWHM decreases after sol-gel modification
compared to the typical thermal spray coatings. The reductions in FWHM values
reveal that the crystallinity of the coating increases after sol-gel modification.
Table 8-2 Full width at half maximum (FWHM) comparison for typical thermal spray
coatings and sol-gel modified thermal spray coatings with PO4 band and OHˉ band.
Types of coatings Full Width at Half Maximum (FWHM) PO4 band OHˉ band
Typical thermal spray coatings 37.6 137.3
Sol-gel modified thermal spray coatings 32.9 104.7
Chapter 8 Sol-gel modified thermal spray coatings
148 | P a g e Author: Md. Fahad Hasan
0 500 1000 1500 2000Raman frequency (cm-1)
Typical thermal spray coatings Sol-gel modified thermal spray coatings
a
3000 3500 4000 4500 5000
Typical thermal spray coatings Sol-gel modified thermal spray coatings
Raman frequency (cm-1)
b
Figure 8-13 Raman spectra comparison for typical thermal spray coatings and sol-
gel modified thermal spray coatings within a Raman frequency of (a) 200-2000 cm-1
(PO4 band), and (b) 3000-5000 cm-1 (OHˉ band).
Chapter 8 Sol-gel modified thermal spray coatings
149 | P a g e Author: Md. Fahad Hasan
8.6. Ca/P ratio
The chemical composition of typical thermal spray coatings and sol-gel modified
thermal spray coatings is shown in Fig. 8-14. The Ca/P ratios are low on the top
surface and high on the cross-section for typical thermal spray coatings, whereas
sol-gel modified thermal spray coatings show inverse results, Table 8-3. Sol-gel
modified thermal spray coatings exhibit a higher Ca/P ratio on the top surface and
cross-section than the typical thermal spray coatings. On the top surface of sol-gel
modified thermal spray coatings, the oxygen percentage increases and the calcium
and phosphorus percentages decrease compared to typical thermal spray coatings.
Figure 8-14 Comparison of Ca/P ratio on the top surface and cross-section.
On the cross-section, the Ca/P ratio increases for sol-gel modified thermal spray
coatings throughout the thickness as the measurement location moves from the
coating-epoxy interface position towards the substrate-coating interface position,
Figure 8-15. For sol-gel modified thermal spray coatings, the calcium percentage
increases along the thickness compared to the calcium percentage for typical
thermal spray coatings, Table 8-4. This increase in the calcium percentage indicates
the existence of sol-gel solution along the thickness. The maximum Ca/P ratio is
Chapter 8 Sol-gel modified thermal spray coatings
150 | P a g e Author: Md. Fahad Hasan
found near the coating-epoxy interface due to the maximum penetration of sol-gel
solution.
Table 8-3 Comparison of chemical composition on the top surface and cross-section
of typical thermal spray and sol-gel modified thermal spray coatings.
Figure 8-15 Ca/P ratio variations throughout the coating thickness.
Types of coating
Testing direction
Ca (wt.%)
n=5
P (wt.%)
n=5
O (wt.%)
n=5
Ca/P ratio
(wt.%)
Ca/P ratio
(molar)
Thermal spray
coatings
Top surface 34.92±0.55 15.90±0.29 48.99±0.55 2.19 1.68
Cross-section 40.69±0.55 19.01±0.60 40.29±0.78 2.14 1.64
Sol-gel modified thermal spray
coatings
Top surface 28.96±1.68 11.10±3.00 59.94±4.60 2.60 1.99
Cross-section 44.62±0.71 19.45±1.11 35.93±1.04 2.29 1.76
Chapter 8 Sol-gel modified thermal spray coatings
151 | P a g e Author: Md. Fahad Hasan
Table 8-4 Comparison of chemical composition throughout the thickness for typical
thermal spray coatings and sol-gel modified thermal spray coatings.
A point analysis was carried out to investigate the variation of the Ca/P ratio on
the coatings with respect to spherical particles, platelet particles, and the sol-gel
solution, Table 8-5. Spherical particles, platelet particles, and sol-gel solutions were
visible (Figure 8-3) on the top surface. On the other hand, on the cross-section, sol-
gel solutions and particles were visible; however, it was not possible to distinguish
whether the particles were spherical or platelet.
From Table 8-5, it can be seen that the sol-gel solution exhibits a higher Ca/P
ratio on both the top surface and cross-section than the particles. These sol-gel
solutions show chemical compositions that mostly exhibit calcium and oxygen
percentages, with a very low percentage of phosphorous. These sol-gel solutions
can penetrate in the thermal spray coatings, which increases the Ca/P ratio on the
cross-section after sol-gel modification. Similarly, due to the presence of sol-gel
solutions on the top surface, the coatings show higher Ca/P ratio after sol-gel
modification. Spherical particles show higher Ca/P ratio than the platelet particles.
Types of coating
Testing area
Ca (wt.%)
n=5
P (wt.%)
n=5
O (wt.%)
n=5
Ca/P ratio
(wt.%)
Ca/P ratio
(molar)
Typical thermal spray
coatings
Coating-epoxy 40.35±0.57 18.78±0.26 40.89±0.72 2.15 1.65
Coating-centre 41.00±0.55 18.95±0.22 40.05±0.76 2.16 1.66
Substrate- coating 40.10±0.66 18.50±0.41 41.40±0.55 2.17 1.67
Sol-gel modified thermal spray
coatings
Coating-epoxy 43.23±3.03 20.07±1.14 36.69±3.90 2.15 1.65
Coating-centre 43.12±3.01 19.29±1.46 37.58±2.40 2.23 1.71
Substrate- coating 43.39±2.24 18.20±1.47 38.55±3.35 2.38 1.83
Chapter 8 Sol-gel modified thermal spray coatings
152 | P a g e Author: Md. Fahad Hasan
Table 8-5 Chemical composition of the sol-gel coatings.
Testing direction
Testing point
Ca wt.% (n=5)
P wt.% (n=5)
O wt.% (n=5)
Ca/P ratio wt.%
Ca/P ratio
(molar)
Top surface
(Fig. 8-4)
Spherical particle 27.59±3.38 12.85±2.89 59.46±6.01 2.15 1.65
Platelet particle 38.51±15.82 22.26±5.67 39.23±21.32 1.73 1.33
Sol-gel solution 27.74±1.24 4.88±0.63 67.37±1.35 5.68 4.36
Cross-section
(Fig. 8-7)
Particle 33.58±5.17 18.45±1.82 47.97±4.14 1.82 1.29 Sol-gel solution 21.84±3.11 4.22±6.45 74.82±7.33 5.17 3.97
8.7. Summary
Thermal spray HA coatings were modified using a sol-gel treatment to modify the as-
received coating properties. The sol-gel coatings on the top surface of thermal spray
coatings could be beneficial, as they could increase bone growth on the coating
surface. The following conclusions can be drawn from this study:
1. Sol-gel modified thermal spray coatings show crystal growth on the top
surface that fills the pores and cracks of the coating cross-section. As a
result, the porosity of sol-gel modified thermal spray coatings is decreased
by 54% compared to that of the typical thermal spray coatings. The top
surface indicates that there are some spherical undissolved or partially
dissolved HA particles.
2. Sol-gel modified thermal spray coatings exhibit higher microhardness than
the typical thermal spray coatings for all applied loads (50, 100, and 300 gf)
throughout the coating thickness, i.e., 75, 175, 275 µm distance from the
substrate-coating interface.
3. The surface roughness of sol-gel modified coatings was reduced by 9%
compared to that of the typical thermal spray coatings.
4. The Weibull modulus of microhardness shows a high Weibull modulus for
lower loads (50 and 100 gf) and low Weibull modulus for higher loads (300
gf) on the sol-gel modified thermal spray coatings, compared to the Weibull
modulus for typical thermal spray coatings. Since higher load could break
Chapter 8 Sol-gel modified thermal spray coatings
153 | P a g e Author: Md. Fahad Hasan
the sol-gel coatings abnormally, which, as a result, would lead to large
variation of data. Maximum Weibull modulus values of microhardness are
found at the central position (175 µm) of the coatings for all applied loads.
The Weibull modulus of porosity and surface roughness indicates
improvement in Weibull modulus values for sol-gel modified thermal spray
coatings.
5. XRD results shows improvement in crystallinity for sol-gel modified thermal
spray coatings compared to the typical thermal spray coatings. The PO4
and OHˉ bands from Raman spectra also indicate reduction of FWHM for
sol-gel modified thermal spray coatings, which also confirms the higher
incidence of crystallinity in the latter when compared to the typical thermal
spray coatings.
6. The Ca/P ratio shows higher values on the sol-gel modified thermal spray
coatings than the typical thermal spray coatings on both the top surface
and cross-section. The Ca/P ratio throughout the coating thickness shows
maximum improvement near the substrate-coating interface due to the
maximum penetration of sol-gel solution. Analysis of the Ca/P ratio on
spherical particles, platelet particles, and sol-gel solution indicates that sol-
gel solution has the maximum Ca/P ratio when compared to the others.
Sol-gel solution can penetrate into the thermal spray coatings and, as a
result, improve the Ca/P ratio.
Chapter 9 Conclusions, major contributions, and future works
154 | P a g e Author: Md. Fahad Hasan
9. Conclusions, major contributions, and future work
9.1. Conclusions
The following conclusions can be drawn from this study.
Process parameter and DOE study 9.1.1.
The relationships between plasma spray process parameters have been
established based on the data from the available literature, which provides the spray
engineer and scientist with preliminary notions about process parameters and
eliminates the need for the adoption of a trial and error approach. Thus, the data
assists interested researchers in the selection of the process parameters best suited
for producing good coatings.
A Taguchi L9 DOE study can provide optimum process parameters with the need
for only a few experiments. The effects of power and secondary gas flow rate (X1),
powder feed rate and carrier gas flow rate (X2), and stand-off distance (X3) on the
coating responses of porosity, microhardness, deposition efficiency, crystallinity, and
surface roughness have been determined.
Optimum coating properties with desired attributes have been obtained from nine
experiments using a Taguchi DOE L9 design with a desirability of 0.7. Optimum
experimental coating properties have a porosity of 4%, deposition efficiency of 61%,
microhardness of 285 HV, crystallinity of 47%, and surface roughness of 9 µm.
There is good agreement between optimum and predicted values with less than 5%
difference. Optimum process parameters are as follows: power of 40 kW, secondary
gas flow rate of 12 slpm, powder feed rate of 16 g/min, carrier gas flow rate of
3 slpm, and stand-off distance of 11 cm. The parameters are valid for the
commercially available hydroxyapatite feedstock.
Power and stand-off distance were coupled and increased together to obtain the
combined effect on the coatings. Porosity, crystallinity, and surface roughness were
reduced, and the coating microstructure was improved due to enhanced particle
melting. The proportion of melted lamellae increased with increasing power and
Chapter 9 Conclusions, major contributions, and future works
155 | P a g e Author: Md. Fahad Hasan
stand-off distance (i.e., ‘x’). The crystallinity reduced with increasing power and
stand-off distance, as did the smoothness due to better particle melting.
Deposition efficiency and microhardness increased with increasing power and
stand-off distance. The combined effect of increasing power and stand-off distance
allowed the Ca/P ratio of the coatings to be maintained at 1.66. However, the Ca/P
ratio measured from EDX analyses indicated that higher power and stand-off
distance provides a Ca/P ratio of the coatings closer to the stoichiometric value of of
hydroxyapatite, i.e., 1.67.
Micromechanical study 9.1.2.
The Vickers microhardness values of plasma spray HA coatings were measured
with respect to testing direction, applied load, and indent location. The dense and
porous areas throughout the coating thickness were evaluated; which are related to
the microstructure and the anisotropic behaviour of coatings. Loads of 50 and 100 gf,
as well as 300 and 500 gf, show similar effects on the microhardness, indent
roughness and Weibull modulus of microhardness throughout the coating thickness
in the dense area.
Combined Vickers microhardness values calculated from a rule of mixture
method decreases with an increase in porous percentage area microhardness.
These findings indicated that, for comparison of microhardness results, it is
necessary to consider similar percentages of microhardness from dense and porous
areas. Weibull moduli of microhardness values are higher in dense areas than in the
porous area since the microhardness values are less scattered in the dense area.
The Weibull modulus of microhardness depends not only on the base material but is
also related to the applied load and position of indents, since the Weibull modulus
value changes with regard to applied load and indent position. Indent roughness
increases as the load increases, since a higher load increases cracking on the two
indenter.
The Knoop microhardness and elastic modulus of plasma sprayed HA coatings
were investigated in terms of indentation angle, testing direction, applied load, and
indent location throughout the coating thickness. The dependence of microhardness
and elastic modulus on the indentation angle can be represented as a parabolic
Chapter 9 Conclusions, major contributions, and future works
156 | P a g e Author: Md. Fahad Hasan
curve. H0, H45, and H90 values were found to satisfy an analysis based on empirical
Pythagoras’ theorem. Microhardness and elastic modulus is higher on the top
surface than at the cross-section.
The Knoop microhardness distribution varies within the coating for all applied
loads on the cross-section. Elastic modulus is almost constant on the coating cross-
section for higher loads (300 and 500 gf) but varies along the coating thickness for
lower loads (50 and 100 gf). Microhardness and elastic modulus decreases with
increasing applied loads. Increase in applied load increases the depth of indentation.
The frequency distribution of Knoop microhardness indicates that a bimodal
distribution may exist for smaller loads (i.e., 50 and 100 gf) whereas it cannot be
clearly distinguished at higher loads (i.e., 300 and 500 gf). The student’s t-test
indicates that T stat values are higher for load 50 vs. 500 gf and lower for load 300
vs. 500 gf.
Study of the sol-gel modified thermal spray coatings 9.1.3.
Thermal spray HA coatings were modified using sol-gel treatment to improve the
coating properties. A sol-gel modified thermal spray coating demonstrated crystal
growth on the top surface. It also filled up the pores and cracks of the coating as
observed on the cross-section. Thus, the porosity improved by decreasing as much
as 54%. Sol-gel modified thermal spray coatings show higher microhardness than
the typical thermal spray coatings at all applied loads (50, 100, and 300 gf)
throughout the coating thickness (i.e., at distance of 75, 175, and 275 µm from the
substrate-coating interface).
Surface roughness of sol-gel modified thermal spray coatings was reduced by 9%
more than the typical thermal spray coatings. XRD results for a sol-gel modified
thermal spray coating shows improvement of coating crystallinity. The PO4 and OHˉ
bands from Raman spectra also indicate reduction of FWHM for sol-gel modified
thermal spray coatings that confirms the latter’s comparatively higher crystallinity
when compared to a typical thermal spray coating. The Ca/P ratio revealed a higher
value for the sol-gel modified thermal spray coatings for both the top surface and
cross-section in comparison to the typical thermal spray coating. The Ca/P ratio
Chapter 9 Conclusions, major contributions, and future works
157 | P a g e Author: Md. Fahad Hasan
throughout the coating thickness shows maximum improvement near the substrate-
coating interface due to the maximum penetration of the sol-gel solution.
9.2. Future work
The present work has contributed to the knowledge regarding thermal spray
coatings and their micromechanical properties. Also, it contributes to the further
improvement of coatings by employing sol-gel treatment. This research opens a wide
scope for related work, and further studies could contribute much to this field. The
following studies are recommended to enhance further research into this area.
• A relationship between plasma spray process parameters could be
developed by collecting data from the available literature for all ceramic
coatings to provide a basic guideline for spray engineers.
• A similar DOE study, adopting the parameters used in this research, could
be carried out using response surface methodology.
• The microhardness distribution throughout the HA coatings could be
investigated using nano-indentation to obtain results at the nanoscale.
Also, microstructural analysis after indentation could be carried out to
understand thermal spray coatings.
• The effect of heat treatment on the crystallinity of HA coatings is not clearly
known which could be investigated.
• A sol-gel hydroxyapatite solution could be prepared from a mixture of
calcium nitrate tetrahydrate (Ca(NO3)2.4H2O) and phosphoric pentoxide
(P2O5). This prepared solution could be used instead of dissolving HA
powder to form the sol-gel. Also, the temperature of sol-gel treatment
could be increased to 500-800 ºC to establish the effect of temperature on
the sol-gel modified thermal spray coatings. Last but not least, cell culture
studies can be carried out to find out the effect of sol-gel coatings.
The above studies would build on the work presented in this thesis and further
advance this typical area of science and engineering.
References
158 | P a g e Author: Md. Fahad Hasan
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Appendix
186 | P a g e Author: Md. Fahad Hasan
Appendix
List of publications
Journal articles
1) Hasan, Md. Fahad; Wang, James; Berndt, Christopher C.; A Taguchi design
study of plasma sprayed hydroxyapatite coatings. Materials Science Forum,
vols. 773-774, pp 598-609, 2014.
2) Hasan, Md. Fahad; Wang, James; Berndt, C.C.; Effect of power and stand-off
distance on plasma sprayed hydroxyapatite coatings. Materials and
Manufacturing Process, vols. 28(2), pp 1279-1285, 2013.
3) Hasan, Md. Fahad; Wang, James; Berndt, C.C.; Evaluation of the mechanical
properties of plasma sprayed hydroxyapatite coatings. Applied Surface
Science, vols. 303, pp 155-162, 2014.
Book chapters
1) Berndt, Christopher C.; Hasan, Md. Fahad; Tietz, U.; Schmitz, K.-P.; Book
Chapter title: A review of hydroxyapatite coatings manufactured by thermal
spray, Book title: Advances in calcium phosphate biomaterials, Series title:
Springer Series in Biomaterials Science & Engineering, Editor: Ben‐Nissan,
B., Vols. 2, pp 267-329, 2014
Conference papers
1) Sanpo, Noppakun; Ang, Andrew Siao Ming; Hasan, Md Fahad; Wang, James;
Berndt, Christopher C., Phases and microstructures of solution precursor
plasma sprayed cobalt ferrite splats. Proceedings of the 5th Asian Thermal
Spray Conference (ATSC 2012), Tsukuba, Japan, 145-146, 2012.