36 citations · 37 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2025★ 1 cited
Universal Machine Learning Interatomic Potentials are Ready for Solid Ion Conductors
Hongwei Du, Jian Hui, Lanting Zhang +1
With the rapid development of energy storage technology, high-performance solid-state electrolytes (SSEs) have become critical for next-generation lithium-ion batteries. These mate…
cond-mat.mtrl-sci2025★ 36 cited
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules
Hongwei Du, Jiamin Wang, Jian Hui +2
Generative models generate vast numbers of hypothetical materials, necessitating fast, accurate models for property prediction. Graph Neural Networks (GNNs) excel in this domain bu…