2 citations · 4 across the 3 of their papers we have counts for
3 papers
physics.chem-ph2024
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…
physics.chem-ph2024★ 2 cited
Uni-ELF: A Multi-Level Representation Learning Framework for Electrolyte Formulation Design
Boshen Zeng, Sian Chen, Xinxin Liu +7
Advancements in lithium battery technology heavily rely on the design and engineering of electrolytes. However, current schemes for molecular design and recipe optimization of elec…
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…