A minimal Tersoff potential for diamond silicon with improved descriptions of elastic and phonon transport properties

TL;DR

This paper introduces a modified Tersoff potential for diamond silicon, fitted with quantum-informed data, significantly improving predictions of thermal conductivity, phonon dispersion, and elastic properties over previous models.

Contribution

A new Tersoff potential fitted with quantum data, implemented in an open source code, enhances simulation accuracy for diamond silicon's thermal and elastic properties.

Findings

Improved thermal conductivity and phonon dispersion predictions.

Quantum effects increase thermal conductivity estimates by about 10%.

Potential accurately reproduces elastic constants.

Abstract

Silicon is an important material and many empirical interatomic potentials have been developed for atomistic simulations of it. Among them, the Tersoff potential and its variants are the most popular ones. However, all the existing Tersoff-like potentials fail to reproduce the experimentally measured thermal conductivity of diamond silicon. Here we propose a modified Tersoff potential and develop an efficient open source code called GPUGA (graphics processing units genetic algorithm) based on the genetic algorithm and use it to fit the potential parameters against energy, virial and force data from quantum density functional theory calculations. This potential, which is implemented in the efficient open source GPUMD (graphics processing units molecular dynamics) code, gives significantly improved descriptions of the thermal conductivity and phonon dispersion of diamond silicon as compared to previous Tersoff potentials and at the same time well reproduces the elastic constants. Furthermore, we find that quantum effects on the thermal conductivity of diamond silicon at room temperature are non-negligible but small: using classical statistics underestimates the thermal conductivity by about 10\% as compared to using quantum statistics.