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cond-mat.mtrl-sci2025
Heat transport in superionic materials via machine-learned molecular dynamics
Wenjiang Zhou, Benrui Tang, Zheyong Fan +3
Precise modeling and understanding of heat transport in the superionic phase are of great interest. Although simulations combining Green-Kubo (GK) molecular dynamics with machine-l…
cond-mat.mtrl-sci2025★ 22 cited
NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements
Ting Liang, Ke Xu, Eric Lindgren +16
While machine-learned interatomic potentials offer near-quantum-mechanical accuracy for atomistic simulations, many are material-specific or computationally intensive, limiting the…