Multiscale study of the dynamic friction coefficient due to asperity plowing

TL;DR

This study combines molecular dynamics and statistical modeling to understand how nanoscale asperities influence the macroscopic friction coefficient, revealing unconventional load dependence observed in nanoscale tests.

Contribution

It introduces a multiscale approach integrating nanoasperity shear behavior into a statistical model to predict macroscale friction properties.

Findings

Friction coefficient depends on system parameters like roughness and velocity.

Model predicts unconventional load dependence consistent with nanoscale experiments.

Nanoscale dislocation plasticity influences macroscale friction behavior.

Abstract

A macroscopically nominal flat surface is rough at the nanoscale level and consists of nanoasperities. Therefore, the frictional properties of the macroscale-level rough surface are determined by the mechanical behaviors of nanoasperity contact pairs under shear. In this work, we first used molecular dynamics simulations to study the non-adhesive shear between single contact pairs. Subsequently, to estimate the friction coefficient of rough surfaces, we implemented the frictional behavior of a single contact pair into a Greenwood-Williamson-type statistical model. By employing the present multiscale approach, we used the size, rate, and orientation effects, which originated from nanoscale dislocation plasticity, to determine the dependence of the macroscale friction coefficient on system parameters, such as the surface roughness and separation, loading velocity, and direction. Our model predicts an unconventional dependence of the friction coefficient on the normal contact load, which has been observed in nanoscale frictional tests. Therefore, this model represents one step toward understanding some of the relevant macroscopic phenomena of surface friction at the nanoscale level.