Diffusion in a $d$-dimensional rough potential

TL;DR

This paper introduces an analytical model for diffusion in high-dimensional noisy solids, validated against simulations, addressing a longstanding challenge in understanding microstructure evolution in materials.

Contribution

The authors develop a novel analytical approach for diffusivity in multi-dimensional noisy solids, extending previous 1D models and validated by kinetic Monte Carlo simulations.

Findings

Analytical model agrees with simulations in low-noise limit

Percolation pathways explain deviations from the model

Extension to arbitrary dimensions addresses a long-standing challenge

Abstract

The prediction of diffusion in solids is necessary to understand the microstructure evolution in materials out of equilibrium. Although one can reasonably predict diffusive transport coefficients using atomistic methods, these approaches can be very computationally expensive. In this work, we develop an analytical model for the diffusivity in a noisy solid solution in an arbitrary number of dimensions using a mean first passage time analysis. These analytical results are then compared with kinetic Monte Carlo (KMC) simulations, which are in good agreement with the simulation data in the low-noise limit. We argue that the difference is expected from percolation pathways that increase the diffusivity in the KMC analysis but are not captured by the model. This generalization to arbitrary dimensions has been elusive to the community since Zwanzig [PNAS, 85, 2029 (1988)] published his seminal work on 1-dimensional systems.