activity
20232025
most citedA Spin-dependent Machine Learning Framework for Transition Metal Oxide Battery Cathode Materials

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.EP2025

Consistent Modeling of Non-equilibrium Dust Sublimation and the Interactions with Dust Evolution in the Inner Regions of Protoplanetary Disks

Sheng Xu, Lile Wang, Luis C. Ho +2

The inner regions of protoplanetary disks are host to the sublimation of dust grains, a process traditionally modeled using equilibrium thermodynamics. We demonstrate through ab-in…

cond-mat.mtrl-sci2025

Observing Nucleation and Crystallization of Rocksalt LiF from Molten State through Molecular Dynamics Simulations with Refined Machine-Learned Force Field

Boyuan Xu, Liyi Bai, Shenzhen Xu +1

Lithium fluoride (LiF) is a critical component for stabilizing lithium metal anode and high-voltage cathodes towards the next-generation high-energy-density lithium batteries. Rece…

cond-mat.mtrl-sci2024

Observing Li Nucleation at Li Metal-Solid Electrolyte Interface in All-Solid-State Batteries

Yun An, Taiping Hu, Quanquan Pang +1

Benefiting from the significantly improved energy density and safety, all-solid-state lithium batteries (ASSLBs) are considered one of the most promising next-generation energy tec…

cond-mat.mtrl-sci2024★ 1 cited

Observation of dendrite formation at Li metal-electrolyte interface: A machine-learning enhanced constant potential framework

Taiping Hu, Haichao Huang, Guobing Zhou +8

Uncontrollable dendrites growth during electrochemical cycles leads to low Coulombic efficiency and critical safety issues in Li metal batteries. Hence, a comprehensive understandi…

cond-mat.mtrl-sci2023★ 2 cited

A Spin-dependent Machine Learning Framework for Transition Metal Oxide Battery Cathode Materials

Taiping Hu, Teng Yang, Jianchuan Liu +9

Owing to the trade-off between the accuracy and efficiency, machine-learning-potentials (MLPs) have been widely applied in the battery materials science, enabling atomic-level dyna…