most citedNEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements

19 citations

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3 papers

cond-mat.mtrl-sci2026★ 19 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…

cond-mat.mtrl-sci2026★ 1 cited

Benchmarking Chemically Scalable Machine-Learning Interatomic Potentials for Large-Scale Simulations of Multicomponent Alloys

Fei Shuang, Penghua Ying, Kai Liu +5

Machine learning interatomic potentials (MLIPs) with broad chemical flexibility are essential for atomistic simulations of compositionally complex alloys, but their deployment in l…

hep-ph2026

Interpretation of as a molecular state

Xiang Yu, Jin-Peng Zhang, Xu-Liang Chen +3

We investigate the mass and strong decay properties of the resonance using QCD sum rules, assuming it to be an S-wave molecular pentaquark state with $…