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Susan B. Sinnott,1 Simon R. Phillpot,1 Scott Perry,1 and W. Gregory Sawyer1,2
University of Florida, 1 Materials Science and Engineering2 Mechanical and Aerospace Engineering
Design of PTFE Solid Lubricant Nanocomposites through Coupled Simulation and Experiment
Students and postdocs who carried out the work:
Peter BarryPatrick ChiuInkook JangJennifer Vale
The goal is to understand how wear and friction in PTFE depends on orientation
Objective and Motivation
2nd Generation REBO potential: Brenner et al. (2002) PTFE surfaces cross-linkedFluorocarbon extension: Jang and Sinnott (2004) Cross-linking density: 2.82 nm-3
Parallelized software: Hsu, Phillpot, and Sinnott (2007)
Computational Details
PTFE-PTFE Sliding
Parallel Sliding Perpendicular Sliding
T= 300 K
Effect of Chain Orientation: Evolution of Sliding Surface
FN
FF
Relationship Between Chain Orientation and Molecular Wear
Analysis of Chain Displacement
Experimental Details
Experimental Evidence of Oriented PTFE Films
Intermittent contact AFM image of the transfer film produced through reciprocal sliding of PTFE on a polished steel substrate. The observed oriented features are highly correlated with the direction of sliding during the generation of the PTFE transfer film.
The single line profile orthogonal to the sliding direction portrays surface features on the order of 10 nm in width and 2-3 nm in height; such features within the image strongly suggest the fibrillated and oriented nature of the transfer film.
Effect of Chain Orientation: Sliding Parallel to Chains
5 10 15 20 25 30 35 400.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
fric
tion
coef
ficie
nt
sliding distance (nm)
300 K
Effect of Chain Orientation: Sliding Perpendicular to Chains
5 10 15 20 25 30 35 400.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
fric
tion
coef
ficie
nt
sliding distance (nm)
300 K
Effect of Chain Orientation: Comparison of Parallel vs. Perpendicular
• Simulations predict anisotropic dependence of friction coefficient with orientation of PTFE (parallel versus perpendicular configurations) and illustrate the mechanisms by which the anisotropy occurs
• Experimental data validates these predictions; computational simulations explain the experimental data
ExperimentSimulation
5 10 15 20 25 30 35 400.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
perpendicular parallel
fric
tion
co
effic
ien
t
displacement (nm)
300 K
PTFE-PTFE Sliding: Parallel Orientation
-45 -30 -15 0 15 30 450
2
4
6
8
10
12
14fr
ictio
nal f
orce
(nN
)
normal force (nN)
m x (nN)0.56 0 300 K0.09 8 300 K
Additive effects of adhesion on contact pressures can be dominant, especially at the nano-scale. Efforts to report friction coefficients that are independent of load, area, and adhesive contributions to contact should use a load-ramp technique.
0.1 300 K
5 10 15 20 25 30 35 400.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
fric
tion
coef
ficie
nt
sliding distance (nm)
PTFE-PTFE Sliding at Variable Loads
0 5 10 15 20 25 30 350
4
8
12
16 perpendicular sliding parallel sliding
Ff (
nN)
Fn (nN)
Objective and Motivation
Combinatorial Simulation of Multifunctional Polymer System
System size53.4 nm in x direction12.5 nm in y direction12.5 nm in z direction
x
y
z
• 1,004,008 atoms simulated• 300 K Temperature• Top surface: Polyethylene (PE)• Bottom surface: PE-PTFE nanocomposite
– Crosslink density 3.58/nm3
– Lower substrate: stationary 14 PTFE-filled bucket configuration
Top View
Side View
PE-PE Sliding
Perpendicular
Parallel
PTFE-PE Sliding at 300K
0 8 16 24 32 40 48 560
4
8
12
16
20
24 parallel sliding perpendicular sliding
Ff (
nN)
Fn (nN)Perpendicular sliding
52 nN load
13.2 nm of sliding
13.2 nm of sliding
75 nN load
50 K temperature
PTFE-PE Composite
Top down view of lower surface during sliding
Focus on one aspect of the composite:
PTFE-PE Sliding at 300K
PE upper surface
(bottom up view)
PTFE lower surface
(top down view)
perpendicular sliding
52 nN load
13.2 nm of sliding
Conclusions
• Orientation of PTFE chains influences processes: aligned chains do not exhibit obvious wear, while misaligned chains undergo obvious molecular wear
• The combination of experimental and computational approaches has dramatically improved our ability to design multifunctional nanocomposites for tribological applications
Effect of Sliding Rate on Computational Chain Orientation Results
Perpendicular Parallel
4 8 12 16 20 240.0
0.4
0.8
1.2
1.6
2.0
fric
tion
coef
ficie
nt
sliding distance (nm)
5 m/s 10 m/s 15 m/s 20 m/s
4 8 12 16 20 240.0
0.4
0.8
1.2
1.6
2.0
sliding distance (nm)
5 m/s 10 m/s 15 m/s 20 m/s
Crosslinking Density Variation (PE)
0 4 8 12 16 20 24 28 32 36 400
4
8
12
16 3% (randomized) 6% (randomized) 12% (randomized) 19% (randomized) 19% (ordered)
Ff (
nN)
Fn (nN)