Achieving Empirical Potential Efficiency with DFT Accuracy: A Neuroevolution Potential for the $\alpha$-Fe--C--H System

TL;DR

This paper introduces a neuroevolution potential (NEP) for the $ ext{Fe--C--H}$ system that combines DFT accuracy with the efficiency of empirical potentials, enabling large-scale simulations of hydrogen effects in steel.

Contribution

The development of a novel NEP for $ ext{Fe--C--H}$ that achieves DFT-level accuracy with high computational efficiency, suitable for large-scale atomistic simulations.

Findings

NEP matches DFT accuracy across various scenarios.

Simulation speeds are comparable or faster than bond order potentials.

Enables practical large-scale hydrogen embrittlement studies.

Abstract

A neuroevolution potential (NEP) for the ternary $\alpha$-Fe--C--H system was developed based on a database generated from spin-polarized density functional theory (DFT) calculations, achieving empirical potential efficiency with DFT accuracy. At the same power consumption, simulation speeds using NEP are comparable to, or even faster than, those with bond order potentials. The NEP achieves DFT-level accuracy across a wide range of scenarios commonly encountered in studies of $\alpha$-Fe- and $\alpha$-Fe--C under hydrogen environments. The NEP enables large-scale atomistic simulations with DFT-level accuracy at the cost of empirical potentials, offering a practical tool to study hydrogen embrittlement in steel.