Researchers from China University of Petroleum (East China), in collaboration with international partners, have reported a ...
Discover how a new machine learning method can help scientists predict which MOF structures are good candidates for advanced ...
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 ...
More information: Y. Hashimoto et al, A materials map integrating experimental and computational data via graph-based machine learning for enhanced materials discovery, APL Machine Learning (2025).
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 ...
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 ...
Researchers from China University of Petroleum (East China), in collaboration with international partners, have reported a comprehensive review of ...
A collaborative team of researchers led by Lehigh University is pioneering new artificial intelligence (AI) techniques to revolutionize materials science. Their project, titled “Harnessing Nonnegative ...
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 ...
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