【8/21開催】北川グループセミナー：Jose L Mendoz教授

このたび、北川グループはセミナーを以下の通り開催いたします。
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Jose L Mendoz教授
Department of Chemical Engineering & Material Science, Michigan State University

- Machine Learning meets First Principles and Big Data: The case of coordination polymers, Metal–Organic Frameworks and Covalent–Organic Frameworks -

Computational algorithms are now powerful enough that they can predict many poperties of materials, chemical and processes before they are synthesized/performed. By implementing and developing new approaches to calculate materials and chemical properties in supercomputers, we have predicted hundreds of thousands materials for energy capture, conversion and storage (e.g. batteries and catalysts).
The computations predicted several new materials which were later made and tested in the lab. The creation of our large amount of materials in-silico. We have implemented different machine learning methods to find further (materials or reaction) design principles. Some of the applications of the design principles of materials has been used towards developing an alternative way to generate and store energy (e.g. next generation Li-batteries, H₂ storage), prediction of materials with new properties (mechanic and electronic) and chemical reactions paths (CO₂ reduction, Artificial Photosynthesis).