Microstructure and properties of plasma sprayed and sol ...€¦ · Author: Md. Fahad Hasan Plasma...

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

iii | P a g e

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

vi | P a g e Author: Md. Fahad Hasan

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


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


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

xi | P a g e Author: Md. Fahad Hasan

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

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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

List of Figures

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Figure 5-3 Main effects plot generated by Minitab software. ........................................ 84





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


of coating on the indent roughness (indent location is presented in Fig.

List of Figures

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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



modulus (adjusted data) with change of testing directions and applied

loads. .......................................................................................................... 120



modulus (adjusted data) at different locations on the cross-section

(indent location is presented in Fig. 7-11; 100 and 300 gf data are

List of Figures

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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


modulus (adjusted data) with different indentation angles (indentation

angle is presented in Fig. 7-11). ................................................................. 124



modulus (adjusted data) with change of testing directions. ........................ 125



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

xvii | P a g e Author: Md. Fahad Hasan

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

List of Tables

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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

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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



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.



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 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.

Chapter 2 Literature review


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.



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.



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



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.



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



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].



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)



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



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.



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;



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



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:



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].



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



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



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.



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.



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].



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].



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].



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.



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.



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



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].



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



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



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.



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



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].



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.



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]:



• 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



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].



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



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.



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



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.



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;



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;


• 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;


• Spray distance;

• Thickness;

• Adhesion strength;

• Porosity;

• Roughness;



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



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



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].



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].



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.



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]:



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,



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



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.



• 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].



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.



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



Figure 2-26 Cause-effect diagram of microhardness measurement for thermal spray coatings (based on Erne et al. [171]).



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.

Chapter 3 Experimental equipment, procedure, and materials characterization


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



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.



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.



Figure 3-4 Powder feeder unit.

Figure 3-5 Gas supply system.



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.



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.



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.



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.



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



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



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.



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



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)



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



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



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


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].



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.



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.



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.



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


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)



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.



Figure 5-1 Plasma spray process parameters graph from literature survey a) power

vs. stand-off distance, and b) power vs. powder feed rate.



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




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,



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



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.


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



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.


Degrees of

freedom (df)


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


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.




Table 5-6 ANOVA table for coatings deposition efficiency.


Degrees of

freedom (df)


Prob>F %

Contribution

Model 2448.61 6 408.10 77.62 0.0128 Power and


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.



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.


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.



Table 5-7 ANOVA table for coatings crystallinity.


Degrees of

freedom (df)


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


Residuals 597.56 2 298.78 38.24 Core total 1562.89 8


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.



Table 5-8 ANOVA table for coatings surface roughness.


Degrees of

freedom (df)


Prob>F % Contribution

Model 10.10 6 1.68 1.51 0.4497 Power and


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


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 +++



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.



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


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.



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


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



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



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



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.



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.



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.



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.



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



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


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.



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



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.



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.



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.



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)


n=20 Cross-section Porous area


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).



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)


n=20 Cross-section Dense area


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).



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



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



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.



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.



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.



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


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


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).



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



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



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.


(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).



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



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.



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



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.


(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



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



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,



since outliers were removed based on the microhardness results, whereas the

Weibull modulus of elastic modulus shows little change.



data) with different indentation angles (indentation angle is presented in Fig. 7-11).





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.





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).



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.



75 175 2750

2

4

6

8

10 50 gf 100 gf 300 gf 500 gf

Dep

th o

f ind

enta

tion

(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.



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.



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



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



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:



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.



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).



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


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.



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.



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.



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.



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



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.



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.



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.



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



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.



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.



20 25 30 35 40 45 50 55 60 65 70

2 theta


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



0 500 1000 1500 2000Raman frequency (cm-1)


a

3000 3500 4000 4500 5000


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).



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



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



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



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



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


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



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



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



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.

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Appendix


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.

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