Abstract

Materials informatics (the search for new materials and design of new materials using machine learning and deep learning) technology is beginning to be introduced in chemical research and development. On the other hand, the handling of structural information and analysis know-how differ depending on which area of chemistry, organic or inorganic, is involved, and there are different methods appropriate for each situation. This book systematically organizes a number of noteworthy research results, including the fundamentals of deep learning, detailed points to keep in mind when actually using deep learning in chemical research, specific ways of handling data in organic and inorganic chemistry, and various deep learning methods and application examples to help understand their specific use. This book is edited for beginners of deep learning and those who aim to conduct specific applied research, so that they can explore various possibilities from the data.

Author’s Information

Kimito Funatsu: Japanese chemist. Doctor of Science. Professor emeritus at the University of Tokyo. Applied chemist specializing in cheminformatics and data-driven chemistry.