982 citations · 1.9k across the 22 of their papers we have counts for
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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…
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…
DPA-2: a large atomic model as a multi-task learner
Duo Zhang, Xinzijian Liu, Xiangyu Zhang +40
The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demo…
DeePMD-kit v2: A software package for Deep Potential models
Jinzhe Zeng, Duo Zhang, Denghui Lu +44
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. T…