105 citations · 341 across the 16 of their papers we have counts for
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cond-mat.mtrl-sci2024★ 1 cited
High-dose long-time defect evolution in tungsten studied by atomistically informed Object Kinetic Monte Carlo simulations
Jintong Wu, Juan-Pablo Balbuena, Zhiwei Hu +4
Irradiation of materials in nuclear test reactors and power plants is known to alter the properties of the material. The irradiation event happening at pico- or nanosecond time sca…
cond-mat.mtrl-sci2024★ 2 cited
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…