2 papers
cond-mat.mtrl-sci2025
Self-Optimizing Machine Learning Potential Assisted Automated Workflow for Highly Efficient Complex Systems Material Design
Jiaxiang Li, Junwei Feng, Jie Luo +9
Machine learning interatomic potentials have revolutionized complex materials design by enabling rapid exploration of material configurational spaces via crystal structure predicti…
cond-mat.mes-hall2025
Two-Dimensional Graphene-like BeO Sheet: A Promising Deep-Ultraviolet Nonlinear Optical Materials System with Strong and Highly Tunable Second Harmonic Generation
Linlin Liu, Congwei Xie, Abudukadi Tudi +2
Two-dimensional (2D) materials with large band gaps and strong and tunable second-harmonic generation (SHG) coefficients play an important role in the miniaturization of deep-ultra…