4 papers
Data-model Coevolution as the Architectural Principle for AI-Native Materials Databases
Fengyu Xie, Ruoyu Wang, Taoyuze Lv +3
AI-native approaches are reshaping computational materials discovery into iterative data-model coevolution cycles. However, most existing materials databases remain fundamentally d…
Uncovering coupled ionic-polaronic dynamics and interfacial enhancement in LiFePO
Fengyu Xie, Yuxiang Gao, Ruoyu Wang +1
Understanding and controlling coupled ionic-polaronic dynamics is crucial for optimizing electrochemical performance in battery materials. However, studying such coupled dynamics r…
Pre-training, fine-tuning, and distillation (PFD): Automatically generating machine learning force fields from universal models
Ruoyu Wang, Yuxiang Gao, Hongyu Wu +1
Universal force fields generalizable across the periodic table represent a new trend in computational materials science. However, the applications of universal force fields in mate…
A Pre-trained Deep Potential Model for Sulfide Solid Electrolytes with Broad Coverage and High Accuracy
Ruoyu Wang, Mingyu Guo, Yuxiang Gao +7
Solid electrolytes with fast ion transport are one of the key challenges for solid state lithium metal batteries. To improve ion conductivity, chemical doping has been the most eff…