Cambridge Polymer Group, 56 Roland Street, Suite 310
Boston, MA 02129(617) 629 4400
www.campoly.com
7-17 Presentation (10/1/2010)
Connecting mechanical testing techniques to user perception
“Psychorheology”
Gavin Braithwaite
“Psycho-rheology”
• Where analytical rheology doesn’t provide the complete answer– Rheology reliably analyzes and ranks materials
• Generally linear functions– Consumer perception is overall experience
• “psycho-rheology”• First coined by G.W. Scott Blair (1930’s)
• Real-world usage rarely one deformation– “performance” based tests often useful in linking
“real world” experience with fluid properties– Tests that inherently use multiple relevant
deformations can sometimes provide better insight to consumer perception
– Almost certainly non-linear– Less “transferable”
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Origins of the concept
• Psychorheology– Psychology– Physics/rheology– Sensory evaluation (sensory psychology)
• Late 19th century - Introspectionism– True study of perception requires isolation of the perceptual experience
• Mid-20th century - Psychometricians use statistical processes– Texture descriptors correlated with each other– Yields set of texture “primaries”
• Early 1960s Szcesniak et al (General Foods) formalized– Built large number of descriptive terms
• assumed to be independent– Termed the “texture profile system”– Related “ranking” to analytical techniques
3 Cambridge Polymer GroupPsychorheology – its foundations and current outlook, HR Moskowitz (1977) Journal of Texture Studies V8, 229-246
March 2015
Texture Profile Characterization (Szcesniak)
4 Cambridge Polymer GroupClassification of Textural Characteristics, A.S. Szczesniak (1963) Journal of Food Science V28 N4 285-289
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Psychophysical properties
• Mid-20th C - efforts to correlate analytical parameters to experience– Magnitude estimation
• Generation of a power function by observers• Relates physical intensity (I) to sensory intensity (S)
5 Cambridge Polymer GroupPsychorheology – its foundations and current outlook, HR Moskowitz (1977) Journal of Texture Studies V8, 229-246
March 2015
Texture Analysis
• Initial attempts were instruments for specific applications– Gelometers– Tenderometers– Consistometers– Exact physics of the deformation less important– Difficult to transfer, rarely standardized and subjective use
• First “integrative” machines– General Foods Texturometer
• Imitative of mastication• Coupled to secondary “combined” texture functions
– Allo Kramer Shear Press– Largely superceded
• “Instron” type instruments• Rheometers
• Highly complex correlations6 Cambridge Polymer GroupMarch 2015
General Foods Texturometer
• Based on an MIT design– Hanau articulator simulates mastication through model of the mandible
condyle– Additional added viscosity measurement
• Standardized configuration– Deformation– Sample size/shapes
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The Texturometer – A New Instrument for Objective Texture Measurement, H.H. Friedman et al. (1963) Journal of Food Science V28 N4 390-396
March 2015
Texturometer parameters
• Hardness - Inverse of modulus on first chew – Highest deflection at A1 normalized by force
• Cohesiveness - work in chewing– Area under second peak (A2) normalized by first peak (A1)
• Elasticity - Recovery– Distance B
• Adhesiveness - negative peak height (A3) – Work required to separate samples
• Brittleness– Height for first break in the peak A1
• Chewiness– Hardness x Cohesiveness x Elasticity
• Gumminess– Hardness x Cohesiveness x 100
• Viscosity– Simple bob-and-cup
8 Cambridge Polymer GroupDevelopment of Standard Rating Scales for Mechanical Parameters of Texture and Correlation Between the Objective and the Sensory Methods of Texture Evaluation, A.S. Szczesniak et al. (1963) Journal of Food Science V28 N4 397-403
March 2015
Rheology
• Modern shear rheometers exceptionally robust tools– Wide torque and strain range
• Many orders of magnitude– Robust control systems with wide dynamic range– Well understood flow-fields– Industry accepted instrumentation and models
• Other geometries– Capillary– Vane– Extensional
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Quantitative characterization
• Simplifying flow-fields aids analysis– Shear flows
• Viscosity• Shear thinning/thickening• Elasticity• Temporal evolution• Relaxation times• Yield stress
– Pipe flow• Extensional properties• Melts
– Extensional rheometers• Breakup times• Relaxation times
– Reduce flow-fields and deformations to tractable situations
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What tests are “right”?
• What are the dominant deformations?• Two approaches
– Model the process• Texturometer
– Break the process down• Some connections are obvious
– Sticky/slippery• Some are not
– “mouth feel”
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5
10
15
20
25
dressing 1 dressing 2 dressing 3 dressing 4
Breakup Time [sec]Relaxation Time [sec]
Poor “mouthfeel”
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Consumer perception
• Consumer perception is not solely one “phase”– Example from foods
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Texture Profile Method, M.A. Brandt et al. (1963) Journal of Food Science V28 N4 404-409
March 2015
Case studies
1. Food products– Differentiating milk products
2. Consumer healthcare– Tactile feel of personal care fluids
3. Haircare products– Competitive analysis
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Case 1: Milk rheology
• Bovine milk similar composition, with breed variations– Fat
• Holstein/Friesian - 3.6wt%, Jersey - 5.2 wt%– Proteins
• 3.4-3.9 wt%– Lactose
• ~5 wt%
• Proteins act to stabilize fat globules– Strongly influence feel and behavior– Agglomeration and separation important– Other solids impact shear viscosity
• Normally considered Newtonian• Motivation: Replacement of fats and sugars
– Desirable for health reasons– Need to preserve consumer perception
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Microalgal flour
• Microalgal biomass contains nutrition-providing materials – carotenoids– dietary fiber– tocotrienols and tocopherols– varying lipid compositions– low levels of saturated lipids
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Experimental
• AR-G2 cone-and-plate– 60 mm 1º SS cone, 25 ºC– Stepped shear 0.1-1000 s-1
• Milk (fresh)– Whole (~4% fat)– Skimmed (2% fat)– Skimmed (1% fat)– Non-fat (0.5 wt% fat)
• Starch solutions• Sugar solutions• Proprietary food additives
– Consumer testing indicates best alternative
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Impact of composition
• Milk normally considered “newtonian”• Stabilized fat globules
– Deformable spheres– Hydrodynamic interactions dominate
• Einstein/Taylor/Schowalter etc– Spheres in Newtonian solution– Packing fraction depends on proteins
and sugars (~10%)– Not mono-disperse– Globules prone to cluster
• Critical response for mouth-feel – Shear thinning with zero-shear plateau– Fat provides viscosity– Fat % does not change behavior
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Fat volume fraction
Shear rate5 s-1
10 s-1
0.1 s-1
Kyazze, G. and Starov, V., Viscosity of Milk: Influence of Cluster Formation. Colloid Journal 66(3),316-321 (2004)
C.W. Macosko Rheology: Principles, Measurements, and Applications, VCH Publishers Inc., New York, 1994.
March 2015
• What is the most relevant deformation?
0.001
0.01
0.1
0.1 1 10 100 1000
She
ar v
isco
sity
[Pa.
s]
Shear rate [s-1]
whole milk (G2)
2% fat (G2)
1% skimmed (G2)
non-fat (G2)
Milk
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Error bars SD for three runs
Fat wt% down
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Reducing fat
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0.001
0.010
0.100
1.000
10.000
0.1 1.0 10.0 100.0 1000.0
Shear rate [s-1]
Shea
r Vis
cosi
ty [P
a.s]
Alginate flourAlgal Flourwhole milk2% fat1% skimmednon-fat1% starch2% starch3% starch 5% starch
March 2015
Conclusions
• Consumer testing implies– Algal flour closest to milk response– Shear rheology indicates starch is the best
• Complex fluids can yield deceptively simple responses– Milk (stabilized fat globules)
• Shear thinning• Shear rate response controlled by fat content plus proteins and sugars
– Choosing “dominant” deformation does not always allow replacement of ingredients
• Milk “feel” expected to be dominated by shear viscosity• Corn syrup, algal flour and starch all provide reasonable rheological
responses• But rheology does not provide separation between systems
– So where is the difference?• Wrong deformation?• Wrong range of deformation?
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• Consumer products represent a massive market in US– Emulsions, emollients, moisturizers and personal lubricants
• Perception of efficacy influenced by “feel” and “look” of system– Complex interplay of
• Viscosity• Yield stress• Absorption• Wetting • Elasticity• Loading
Case 2: Consumer Products
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Personal Lubricants
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0102030405060708090Firmness
Thickness
Residue Thickness
Slipperiness
Stickiness
Runniness
Spreadability
Wetness
124568910
AqueousSiliconeEmulsion
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Consumer ranking (selected)
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0
1
2
3
4
5
6
7
8
9Fi
rmne
ss
Thic
knes
s
Stic
kine
ss
Run
nine
ss
Spr
eada
bilit
y
Ave
rage
1
2
4
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6
8
9
10
AqueousSiliconeEmulsion
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0.1000 1.000 10.00 100.0 1000Ang. frequency (rad/s)
0.01000
0.1000
1.000
10.00
100.0
1000
G' [
Pa]
0.01000
0.1000
1.000
10.00
100.0
1000
G''
[Pa]
1
10
2
4
56
9
Small Amplitude Oscillatory Shear
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1
4
9
AqueousSiliconeEmulsion
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Yield Stress
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AqueousSiliconeEmulsion
1
4
9
0.01000 0.1000 1.000 10.00 100.0 1000Shear stress [Pa]
1.000E-3
0.01000
0.1000
1.000
10.00
100.0
1000
Visc
osity
[Pa.
s]
1
10
2
4
6
9
5
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0.01
0.1
1
10
0 2 4 6 8 10Time [s]
Diam
eter [m
m]
14925610
Capillary Breakup
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• Thermo Haake CaBER
0.01
0.1
1
10
0 2 4 6 8 10Time [s]
Diam
eter [m
m]
14925610
Sample
Laser micrometer
1
99
4
AqueousSiliconeEmulsion
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Observations
• High ranking materials appear to have– High low-shear viscosity and low high-shear viscosity– High shear viscosity seems to be more important– Elasticity less important– Extensional properties appear related
• What is missing?– “slipperiness” (lubricity)
• Related to shear viscosity and surface chemistry• “Thin” film with gap governed by shear properties• Coefficient of Friction
– “stickiness” (tack)• Related to elasticity and adhesion• Large contact area, dependent on pull speed and fluid properties• Tack test
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Lubricity
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CoF on a rheometer
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1 Kavehpour and McKinley “Tribo-rheometry: from gap-dependent rheology to tribology” Tribology Letters (2004) 17(2) 327-335
Spring
Annulus
Surface
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Coefficient of Friction
• CoF fixture on AR-G2. Controlled normal stress (82 kPa) and rotation rate
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-0.10.00.10.20.30.40.50.60.7
0.1 1 10 100Coe
ffici
ent o
f Fric
tion
[]
Velocity [rad/s]
1
4
9
2
5
8
6
10
water
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0.1 1 10 100
Coe
ffici
ent o
f Fric
tion
[]
Velocity [rad/s]
1
49
2
5
8
6
10
Hydrogel
Neoprene
1, 4, 9
4
9
1
AqueousSiliconeEmulsion
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Comparisons
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0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
1 4 9 2 5 8 6 10 water
Coe
ffici
ent o
f Fric
tion
[]
Hydrogel Neoprene
Em
ulsi
on
Aqu
eous
NA
• CoF fixture on AR-G2. Controlled normal stress (82 kPa) and rotation rate (0.3 rad/s)– 12 N load, linear velocity of 3 cm/s
Aqu
eous
Aqu
eous S
ilico
ne
Aqu
eous
Aqu
eous
Sili
cone
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Tackiness
• Combination of accurate vertical position and normal force allow tack to be measured on a conventional rheometer– AR-G2 has a “fast sampling” mode that allows 250 Hz– Squeeze/pull-off allows tack-like test using parallel plates
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Normal force
Velocity
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Tackiness
• 4 cm parallel plate loaded to fixed gap and pulled at 500 micron/s
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-20
-15
-10
-5
0300 600 900 1200 1500 1800 2100 2400
Forc
e [N
]
Position (relative to bottom plate) [mm]
1 4 9 2 5 8 6 10
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
300 600 900
Forc
e [N
]
Position (relative to bottom plate) [mm]1
4
9
AqueousSiliconeEmulsion
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Work of Adhesion
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0
0.001
0.002
0.003
0.004
0.005
0.006
1 4 9 2 5 8 6 10
Wor
k of
adh
esio
n [J
]
Sample
Aqu
eous
Aqu
eous
Sili
cone
Aqu
eous
Aqu
eous
Sili
cone
Aqu
eous
Em
ulsi
on
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Conclusions
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Correlation between physical and sensory measures Intimate Health products, (p<0.05)
Shear Viscosity
Oscillatory Viscosity
Lubricity
Extensional Viscosity
Adhesion
FirmnessThicknessResidueSlipperinessStickinessRunninessSpreadabilityControllabilityWetnessCooling
March 2015
Case 3: Hair products
• Commercial hair care comparisons– Hold (how well the style is held)
• Adhesion between strands• Lap shear
– Rehold (ability to reform/restyle)• Adhesion between strands after disruption• 180° peel
– Feel (tactile feel)• Coefficient of Friction
– Conflicting needs?
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Lap Shear and 180° Peel test
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• Based on – ASTM F2255 “Strength properties of Tissue Adhesives in Lap-Shear by
Tension Loading”• Materials pulled apart at 5 mm/min• Shear loading
– ASTM D1876 “Peel Resistance of Adhesives”• Materials pulled apart at 305 mm/min• Tensile decohesion• After testing, samples were reformed• Retested five times
• Conventional servo hydraulic load frame– Material spread on stainless steel– Mesh pushed on to material with a dead weight– Allowed to dry
March 2015
Lap shear testing
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0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 0.2 0.4 0.6 0.8 1
Force
Displacement
0
0.2
0.4
0.6
0.8
1
1.2
Average Peak She
ar Force
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
Average Work To
End
Bad
Good
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180 ° Peel - Recovery of adhesion
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0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1R
un 1
Run
2
Run
3
Run
4
Run
5
Run
1
Run
2
Run
3
Run
4
Run
5
Good Bad
Forc
e
Bad
Good
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Coefficient of Friction
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0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
CoF
Normal Force
Bad
Good
March 2015
Conclusions
• Test selection– Important to pick relevant deformations– May not be trivial– If the tests are too complex – may not be the right ones
• Good analytical tests should– Be relatively simple– Capture critical aspect(s) of use– Generate a clear picture of sample differences
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Lessons and comments
• Understanding the rheology of fluids critical for understanding consumer perception and use
• But mode of use can be just as important– Usage rarely simple shear
• Or only in a limited range– Perception is therefore governed by response to variety of deformations
• Simple shear• Compression• Extension• Pipe-flow etc
• Collating data in more relevant configurations can provide useful correlations with field data
• Superb force and position control of a conventional rheometer still useful
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Thank you
Cambridge Polymer Group is a contract research laboratory specializing in polymers and their applications. We provide outsourced research and development, consultation and failure analysis as well as routine analytical testing and custom test and instrumentation design.
Cambridge Polymer Group, Inc.56 Roland St., Suite 310Boston, MA 02129(617) 629-4400http://[email protected]
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