Ab initio quality study of the graphite-diamond phase coexistence

TL;DR

This paper develops a neural-network-based interatomic potential for carbon that accurately models both graphite and diamond phases, enabling efficient ab initio-quality molecular dynamics simulations of their coexistence thermodynamics.

Contribution

It introduces a novel neural-network potential that combines ab initio accuracy with efficiency, allowing for first-principles-level thermodynamic studies of graphite-diamond coexistence.

Findings

Good agreement with experimental coexistence curves

Nuclear quantum effects are crucial for accuracy

First molecular dynamics study at ab initio quality

Abstract

An interatomic potential for the diamond and graphite phases of carbon has been created using a neural-network (NN) representation of the ab initio potential energy surface. The NN potential combines the accuracy of a first-principle description of both phases with the efficiency of empirical force fields and allows one to perform, for the first time, a molecular dynamics study, of ab initio quality, of the thermodynamics of graphite-diamond coexistence. Good agreement between the experimental and calculated coexistence curves is achieved if nuclear quantum effects are included in the simulation.