3 papers
cond-mat.mtrl-sci2025
Equivariant Atomic and Lattice Modeling Using Geometric Deep Learning for Crystal Structure Optimization
Ziduo Yang, Yi-Ming Zhao, Xian Wang +3
Structure optimization, which yields the relaxed structure (minimum-energy state), is essential for reliable materials property calculations, yet traditional ab initio approaches s…
cond-mat.mtrl-sci2024
Scalable Crystal Structure Relaxation Using an Iteration-Free Deep Generative Model with Uncertainty Quantification
Ziduo Yang, Yi-Ming Zhao, Xian Wang +6
In computational molecular and materials science, determining equilibrium structures is the crucial first step for accurate subsequent property calculations. However, the recent di…
cs.CE2023
Lightweight equivariant model for efficient machine learning interatomic potentials
Ziduo Yang, Xian Wang, Yifan Li +3
In modern computational materials science, deep learning has shown the capability to predict interatomic potentials, thereby supporting and accelerating conventional simulations. H…