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PTFE Composite Wear Behavior: AFM Study of Transfer Film Formation

In a recent Tribology Letters article, researchers used atomic force microscopy (AFM) to investigate the formation of transfer films during the sliding of polytetrafluoroethylene (PTFE) composites against stainless steel. Their goal was to uncover the complex interplay of tribochemical and mechanical processes that lead to these materials' ultralow wear behavior.

PTFE Composite Wear Behavior: AFM Study of Transfer Film Formation

Image Credit: Elizaveta Galitckaia/Shutterstock.com

Background

PTFE is widely used as a solid lubricant due to its low friction and high thermal and chemical stability. However, its low wear resistance limits its applications. To enhance its wear performance, PTFE is often filled with substances such as polymers, fibers, and nanoparticles.

Among these fillers, alpha-phase alumina has been shown to reduce PTFE wear rate by almost four orders/degrees of magnitude to the ultralow regime of k < 1 × 10-7 mm3/(N·m). The ultralow wear behavior of PTFE/alumina composites is attributed to the formation of robust tribofilms on the PTFE composite and the metal countersurface, which protect the underlying materials from excessive wear.

These tribofilms are composed of a mixture of fluoropolymer and alumina, and their properties depend on the tribochemical reactions and topographical changes that occur during sliding.

About the Research

The authors conducted sliding experiments using a custom linear reciprocating tribometer in a pin-on-flat configuration. The pin was made of PTFE/alumina composite with 5 wt% alpha-phase alumina, and the flat was 304L stainless steel. Experiments were performed under ambient conditions.

Periodically, the sliding was interrupted to remove the metal countersurface for ex-situ AFM measurements of the developing transfer film. AFM characterized the three-dimensional (3D) topography of the same region for sequential scans using fiducial markers inscribed on the countersurface. The AFM tip was also periodically checked for damage or fouling by scanning a smooth silicon wafer.

The researchers also employed scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) to map the elemental composition of transfer film asperities. They used a web application called "Contact Engineering" to perform power spectral density (PSD) calculations of the AFM height data, providing length-scale-dependent statistical information on surface roughness.

Research Findings

The study revealed that transfer film formation occurred in three phases: run-in, transition, and steady state. During the run-in phase, wear debris was generated and swept aside. In the transition phase, islands of PTFE composite nucleated and grew within the valleys of the countersurface, reducing surface roughness and wear rate. In the steady-state phase, continuous transfer film formation occurred, and the wear rate decreased further.

After 10,000 cycles, the transfer film developed a bronze coloration, coinciding with the emergence of nanoscale features on the surface. EDX identified these features as aluminum-rich domains, indicating the presence of alumina particles formed by the fragmentation and agglomeration of alumina filler due to tribomechanical stresses.

PSD calculations showed that surface roughness at different length scales varied with sliding cycles, reflecting changes in the transfer film's morphology and composition. The friction coefficient was largely insensitive to microscale surface roughness after the first 1,000 cycles, suggesting that macroscale friction behavior may be independent of the nanoscale or microscale topography of the tribofilm

The researchers also discussed the limitations and challenges of using AFM and other probe-based techniques to study transfer film development, such as tip geometry, resolution, alignment, and damage.

Applications

This research provides insights into the development of transfer films at the nanoscale and microscale levels, aiding in understanding the mechanisms of friction and wear of solid lubricants.

This approach can be applied to other tribological systems, such as liquid lubricants, and combined with plasmonic diagnostics and surface-enhanced Raman spectroscopy for more information on tribochemical processes. It can also correlate the roughness of the transfer film surface with tribological performance.

The authors demonstrated the usefulness of AFM in characterizing the evolving 3D topography of transfer films. The findings may help design longer-lasting materials and reduce waste in applications requiring low friction and wear, such as aerospace, automotive, biomedical, and microelectromechanical systems.

The study also shows the potential of using web applications for spectral analysis of surface topography data, facilitating the quantitative characterization and comparison of tribological surfaces.

Conclusion

The study concluded that the transfer film development of PTFE/alumina composites against stainless steel is a complex process involving tribochemical and mechanical mechanisms. It identified three phases of transfer film formation and observed nanoscale features, likely alumina particles. The authors showed that surface roughness at different length scales changed with sliding cycles, while the friction coefficient remained relatively constant.

Future work could include in situ measurements of transfer film development and tribochemistry, as well as investigations of other filler materials and sliding conditions.

Journal Reference

Shaffer, KE., et al. (2024) Atomic Force Microscopy of Transfer Film Development. Tribol Lett. DOI: 10.1007/s11249-024-01893-

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Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

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