Weiyi Xia, Masahiro Sakurai, Balamurugan Balasubramanian, Timothy Liao, Renhai Wang, Chao Zhang, Huaijun Sun, Kai-Ming Ho, James R. Chelikowsky, David J. Sellmyer, Cai-Zhuang Wang Proceedings of the ...
Machine learning tools can accelerate all stages of materials discovery, from initial screening to process development. Whether the goal is to identify new applications for known materials or to ...
Researchers from China University of Petroleum (East China), in collaboration with international partners, have reported a ...
Join us to learn about how to use cutting edge GPU infrastructure to solve real world material discovery problems with AI and unsupervised machine learning. Our lab in the Department of Materials ...
Discover how a new machine learning method can help scientists predict which MOF structures are good candidates for advanced ...
Key TakeawaysThe Materials Project is the most-cited resource for materials data and analysis tools in materials science.The ...
Researchers from China University of Petroleum (East China), in collaboration with international partners, have reported a comprehensive review of ...
A recent study published in Small highlights how machine learning (ML) is reshaping the search for sustainable energy materials. Researchers introduced OptiMate, a graph attention network designed to ...
For his research in machine learning-based electron density prediction, Michigan Tech researcher Susanta Ghosh has been recognized with one of the National Science Foundation's highest honors. The NSF ...
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