A unified variational model for grain boundary dynamics incorporating microscopic structure

TL;DR

This paper introduces a comprehensive variational model that unifies various microscopic mechanisms of grain boundary dynamics, applicable to both low and high angle boundaries, enhancing understanding and computational efficiency.

Contribution

The paper presents a novel unified variational framework that incorporates microscopic line defect mechanisms for grain boundary motion, unifying previous models and enabling scalable analysis.

Findings

Successfully recovers existing models under different conditions.

Provides a more efficient description of grain boundary network behaviors.

Lays a foundation for rigorous mathematical analysis and numerical methods.

Abstract

Recent experiments, atomistic simulations, and theoretical predictions have identified various new types of grain boundary motions that are controlled by the dynamics of underlying microstructure of line defects (dislocations or disconnections), to which the classical motion by mean curvature model does not apply. Different continuum models have been developed by upscaling from discrete line defect dynamics models under different settings (dislocations or disconnections, low angle grain boundaries or high angle grain boundaries, etc.), to account for the specific detailed natures of the microscopic dynamics mechanisms, and these continuum models are not in the variational form. In this paper, we propose a unified variational framework to account for all the underlying line defect mechanisms for the dynamics of both low and high angle grain boundaries and the associated grain rotations. The variational formulation is based on the developed constraints of the dynamic Frank-Bilby equations that govern the microscopic line defect structures. The proposed variational framework is able to recover the available models for different motions under different conditions. The unified variational framework is more efficient to describe the collective behaviors of grain boundary networks at larger length scales. It also provides a mathematically tractable basis for rigorous analysis of these partial differential equation models and for the development of efficient numerical methods.