most citedMachine-learning interatomic potential for radiation damage and defects in tungsten

150 citations · 150 across the 1 of their papers we have counts for

collaborators

1 paper

physics.comp-ph2019★ 150 cited

Machine-learning interatomic potential for radiation damage and defects in tungsten

Jesper Byggmästar, Ali Hamedani, Kai Nordlund +1

We introduce a machine-learning interatomic potential for tungsten using the Gaussian Approximation Potential framework. We specifically focus on properties relevant for simulation…