collaborators

5 papers

physics.acc-ph2026

Fully coherent short wavelength free-electron laser driven by a single sub-microjoule seed

Lanpeng Ni, Zheng Qi, Xingtao Wang +33

High-repetition-rate, fully coherent extreme-ultraviolet (EUV) and X-ray free-electron lasers (FELs) are essential for advanced time-resolved ultrafast spectroscopies. While extern…

cond-mat.mtrl-sci2026

An AI-ready fine-tuning framework for accurate machine-learning interatomic potentials in solid-solid battery interfaces

Xiaoqing Liu, Xinyu Yu, Yangshuai Wang +6

Atomistic modeling of solid-solid battery interfaces is essential for understanding electro-chemo-mechanical coupling, but the complex interfacial chemistry and heterogeneous envir…

physics.comp-ph2025

Beyond Adam: Disentangling Optimizer Effects in the Fine-Tuning of Atomistic Foundation Models

Xiaoqing Liu, Yangshuai Wang, Teng Zhao

Atomistic foundation models constitute a paradigm shift in computational materials science by providing universal machine-learned interatomic potentials with broad transferability…

physics.comp-ph2025

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications

Xiaoqing Liu, Kehan Zeng, Zedong Luo +3

Universal machine-learned interatomic potentials (U-MLIPs) have demonstrated broad applicability across diverse atomistic systems but often require fine-tuning to achieve task-spec…

physics.comp-ph2025

A Study on the Fine-Tuning Performance of Universal Machine-Learned Interatomic Potentials (U-MLIPs)

Xiaoqing Liu, Kehan Zeng, Yangshuai Wang +1

Universal machine-learned interatomic potentials (U-MLIPs) have demonstrated effectiveness across diverse atomistic systems but often require fine-tuning for task-specific accuracy…