3 papers
cond-mat.mtrl-sci2026
Bgolearn: a Unified Bayesian Optimization Framework for Accelerating Materials Discovery
Bin Cao, Jie Xiong, Jiaxuan Ma +11
Efficient exploration of vast compositional and processing spaces remains a major challenge in accelerated materials discovery. Bayesian optimization (BO) provides a principled app…
cond-mat.mtrl-sci2025
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
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…