Phonon Optimized Potentials

TL;DR

This paper introduces a genetic algorithm-based method to optimize empirical interatomic potentials specifically for phonon transport, improving the accuracy of molecular dynamics simulations in modeling phonon-related properties.

Contribution

The paper presents a novel approach for deriving phonon optimized potentials (POPs) from ab initio data using genetic algorithms, enhancing phonon transport simulations.

Findings

Method effectively fits potentials to phonon properties

Improves agreement between MD simulations and experimental data

Enables more accurate atomistic modeling of phonon transport

Abstract

Molecular dynamics (MD) simulations have been extensively used to study phonons and gain insight, but direct comparisons to experimental data are often difficult, due to a lack of empirical interatomic potentials (EIPs) for different systems. As a result, this issue has become a major barrier to realizing the promise associated with advanced atomistic level modeling techniques. Here, we present a general method for specifically optimizing EIPs from ab initio inputs for the study of phonon transport properties, thereby resulting in phonon optimized potentials (POPs). The method uses a genetic algorithm (GA) to directly fit to the key properties that determine whether or not the atomic level dynamics and most notably the phonon transport are described properly.