Thermodynamics and dynamics of non-compact prismatic dislocation loops simulated using a machine-learning model

TL;DR

This paper develops a machine-learning model to predict the formation energy of complex dislocation loop configurations, enabling analysis of their thermodynamics and dynamics with high accuracy.

Contribution

It introduces a novel ML-based approach to evaluate the thermodynamic properties and mobility of dislocation loops considering microscopic geometric variations.

Findings

ML model achieves 1% error in energy prediction

A universal parameter describes loop irregularity affecting properties

Thermodynamic and mobility variations depend on morphological irregularity

Abstract

We explore how the thermodynamic properties and dynamics of a self-interstitial prismatic dislocation loop are affected by microscopic-scale variations in its geometric configuration, an aspect that rarely received attention in literature. First, we develop a machine-learning (ML) model to predict the formation energy of an arbitrary geometrically complex configuration of a self-interstitial atom dislocation loop. Trained on atomistic simulation data, the ML model achieves high predictive accuracy across a broad range of configurations, with a typical error in the 1% range. Second, from the ML model, we evaluate the density of configurational microstates as a function of loop's formation energy and derive analytical expressions valid in tractable limiting cases. Using statistical mechanics, we derive the configurational free energy, the average energy, and the thermodynamic entropy of a dislocation loop as a function of temperature. Third, we simulate the dynamics of self-climb of dislocation loops with various geometries and evaluate their diffusion coefficients and effective activation energies. Our analysis shows that there is a single universal parameter describing the morphological irregularity of loop configurations in its ground state. This parameter determines the thermodynamic properties of a loop as well as its dynamics, and simulations illustrate how the properties and mobility of a configurationally complex loop vary as functions of the irregularity parameter.