2 citations · 4 across the 3 of their papers we have counts for
3 papers
Fast and accurate machine-learned interatomic potentials for large-scale simulations of Cu, Al and Ni
Aslak Fellman, Jesper Byggmästar, Fredric Granberg +2
Machine learning (ML) has become widely used in the development of interatomic potentials for molecular dynamics simulations. However, most ML potentials are still much slower than…
Atomistic Study of Irradiation-Induced Plastic and Lattice Strain in Tungsten
Jintong Wu, Daniel R. Mason, Fredric Granberg
We demonstrate a practical way to perform decomposition of the elasto-plastic deformation directly from atomistic simulation snapshots. Through molecular dynamics simulations on a…
An empirical potential for simulating hydrogen isotope retention in highly irradiated tungsten
Daniel R. Mason, Duc Nguyen-Manh, Victor W. Lindblad +2
We describe the parameterization of a tungsten-hydrogen empirical potential designed for use with large-scale molecular dynamics simulations of highly irradiated tungsten containin…