Lu, Ziheng

1. MatterGen: a generative model for inorganic materials design
   2023/12/06 by Claudio Zeni, Zeni, Claudio, Robert Pinsler +41 · 1 voice · 27 citations
   Computer Science · Engineering · Materials Science · Physics and Astronomy · #Machine Learning in Materials Science #Modular Robots and Swarm Intelligence #cond-mat.mtrl-sci #cs.AI
2. MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
   2024/05/08 by Han Yang, Yang, Han, Chenxi Hu +44 · 1 voice · 84 citations
   Materials Science · Physics and Astronomy · #Machine Learning in Materials Science #Nuclear Physics and Applications #cond-mat.mtrl-sci
3. Nature Language Model: Deciphering the Language of Nature for Scientific Discovery
   2025/02/11 by Yingce Xia, Xia, Yingce, Peiran Jin +95 · 1 voice · 17 citations
   Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Semantic Web and Ontologies #cs.AI #cs.LG
4. Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning
   2023/06/08 by Shuxin Zheng, Zheng, Shuxin, Jiyan He +33 · 2 citations
   Materials Science · Biochemistry, Genetics and Molecular Biology · Computer Science · #Machine Learning in Materials Science #Protein Structure and Dynamics #Computational Drug Discovery Methods
5. Probing the Limit of Heat Transfer in Inorganic Crystals with Deep Learning
   2025/03/14 by Li, Jielan, Zekun Chen, Chen, Zekun +42 · 4 citations
   Materials Science · #Advanced Thermoelectric Materials and Devices #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Thermal properties of materials
6. UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials
   2025/03/09 by Zhang, Gongbo, Li, Yanting, Luo, Renqian +31 · 3 citations
   #Artificial Intelligence (cs.AI) #Biological Physics (physics.bio-ph) #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Materials Science (cond-mat.mtrl-sci)
7. Overcoming the Size Limit of First Principles Molecular Dynamics Simulations with an In-Distribution Substructure Embedding Active Learner
   2023/11/14 by Lingyu Kong, Jielan Li, Kong, Lingyu +17 · 1 citation
   Computer Science · Engineering · Materials Science · #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Machine Learning and Algorithms #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Microfluidic and Capillary Electrophoresis Applications