206 citations · 771 across the 22 of their papers we have counts for
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cond-mat.mtrl-sci2021
Synergistic coupling in ab initio-machine learning simulations of dislocations
Petr Grigorev, Alexandra M. Goryaeva, Mihai-Cosmin Marinica +2
Ab initio simulations of dislocations are essential to build quantitative models of material strength, but the required system sizes are often at or beyond the limit of existing me…
cond-mat.mtrl-sci2021★ 56 cited
Quantum-accurate magneto-elastic predictions with classical spin-lattice dynamics
Svetoslav Nikolov, Mitchell A. Wood, Attila Cangi +5
A data-driven framework is presented for building magneto-elastic machine-learning interatomic potentials (ML-IAPs) for large-scale spin-lattice dynamics simulations. The magneto-e…