4 papers
Design principles for amorphous solid-state electrolytes
Qifan Yang, Xiao Fu, Xuhe Gong +5
Amorphous solid-state electrolytes (SSEs) offer unique advantages for next-generation batteries, but their rational design is hindered by an unclear structure-property relationship…
Accelerating Amorphous Alloy Discovery: Data-Driven Property Prediction via General-Purpose Machine Learning Interatomic Potential
Xuhe Gong, Hengbo Zhao, Xiao Fu +6
While traditional trial-and-error methods for designing amorphous alloys are costly and inefficient, machine learning approaches based solely on composition lack critical atomic st…
High-Throughput NEB for Li-Ion Conductor Discovery via Fine-Tuned CHGNet Potential
Jingchen Lian, Xiao Fu, Xuhe Gong +2
Solid-state electrolytes are essential in the development of all-solid-state batteries. While density functional theory (DFT)-based nudged elastic band (NEB) and ab initio molecula…
High-Entropy Solid Electrolytes Discovery: A Dual-Stage Machine Learning Framework Bridging Atomic Configurations and Ionic Transport Properties
Xiao Fu, Jing Xu, Qifan Yang +6
The rapid development of computational materials science powered by machine learning (ML) is gradually leading to solutions to several previously intractable scientific problems. O…