Vacancy diffusion in transition metal diborides using diverse machine-learning potentials
Machine-learning interatomic potential (MLIP)--based molecular dynamics enables efficient exploration of mass-transport mechanisms in complex materials together with quantitative determination of diffusion coefficients at finite temperatures. Using an identical training dataset, we develop and assess three MLIPs formal...
David Holec, Thomas Rocke, James Kermode et al.
· AIP Publishing · 0 citations