Strain-rate and temperature dependence of yield stress of amorphous solids via self-learning metabasin escape algorithm

TL;DR

This study introduces a self-learning metabasin escape algorithm coupled with shear deformation to accurately predict the yield stress of amorphous solids across a wide range of strain rates and temperatures, revealing new insights into deformation mechanisms.

Contribution

The paper presents a novel computational approach that extends the ability to simulate yield stress at experimental strain rates, surpassing the limitations of classical molecular dynamics.

Findings

Yield stress decreases with lower strain rates.

Activation volume involves about 10 LJ particles.

Yield stress is highly sensitive to temperature changes.

Abstract

A general self-learning metabasin escape (SLME) algorithm~\citep{caoPRE2012} is coupled in this work with continuous shear deformations to probe the yield stress as a function of strain rate and temperature for a binary Lennard-Jones (LJ) amorphous solid. The approach is shown to match the results of classical molecular dynamics (MD) at high strain rates where the MD results are valid, but, importantly, is able to access experimental strain rates that are about ten orders of magnitude slower than MD. In doing so, we find in agreement with previous experimental studies that a substantial decrease in yield stress is observed with decreasing strain rate. At room temperature and laboratory strain rates, the activation volume associated with yield is found to contain about 10 LJ particles, while the yield stress is as sensitive to a $1.5\%T_{\rm g}$ increase in temperature as it is to a one order of magnitude decrease in strain rate. Moreover, our SLME results suggest the SLME and extrapolated results from MD simulations follow distinctly different energetic pathways during the applied shear deformation at low temperatures and experimental strain rates, which implies that extrapolation of the governing deformation mechanisms from MD strain rates to experimental may not be valid.