3 papers
cond-mat.mtrl-sci2026
Atomistic Machine Learning with Irreducible Cartesian Natural Tensors
Qun Chen, A. S. L. Subrahmanyam Pattamatta, Boyu Wang +2
Atomistic machine learning is a powerful tool for accurate and efficient investigation of material behavior at the atomic scale. While attempts have been made to construct models d…
cond-mat.mtrl-sci2026
Strain-Dependent Ionic Transport in Li3YCl6 Solid Electrolytes
Wei-Fan Huang, Jin Dai, Jiahui Pan +1
Solid-state batteries require electrolytes that sustain high ionic conductivity under the mechanical environment of a functioning cell. Lattice strain, arising from stack pressure,…
cond-mat.mtrl-sci2025
Cartesian atomic moment machine learning interatomic potentials
Mingjian Wen, Wei-Fan Huang, Jin Dai +1
Machine learning interatomic potentials (MLIPs) have substantially advanced atomistic simulations in materials science and chemistry by balancing accuracy and computational efficie…