Microscopic contributions to the deviation from Amontons friction law

TL;DR

This study uses molecular dynamics simulations to analyze nanoscale friction in MX2 monolayers on metal substrates, revealing complex sliding behaviors and deviations from classical friction laws.

Contribution

It introduces a machine-learning-based simulation approach to accurately explore atomic-scale friction mechanisms and mode contributions in 2D material heterostructures.

Findings

Friction force shows non-monotonic dependence on normal load.

Multiple sliding modes coexist and influence overall friction.

Substrate-monolayer combinations significantly affect friction magnitude and modes.

Abstract

We investigate the nanoscale friction behaviour of MX2 monolayers (M = Mo, W; X = S, Se) on Au(111) and Ag(111) substrates with a silicon tip using classical molecular dynamics simulations with machine-learning-based force fields. This approach enables an accurate description of tip-surface interactions and friction mechanisms at the atomic scale. We observe a pronounced non-monotonic dependence of the friction force on the applied normal load, indicating a breakdown of Amontons's law at the nanoscale. Analysis of lateral force' signals and their spatial Fourier transforms reveals the coexistence of multiple sliding modes, including longitudinal sliding, lateral slip, and zig-zag motions. We show that the overall friction response is governed by the relative contributions of these motions. While the qualitative features of friction are largely substrate-independent, both the magnitude of friction and the balance between sliding modes depend sensitively on the substrate-monolayer combination. In particular, Au/MoSe2/Si exhibits significantly reduced friction due to suppression of lateral slip motion. Our results indicate that the method is broadly applicable for probing nanoscale friction in related heterostructures.