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2017 Fiscal Year Final Research Report

Development of machine learning methods for materials informatics

Planned Research

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Project AreaExploration of nanostructure-property relationships for materials innovation
Project/Area Number 16H00736
Research Category

Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)

Allocation TypeSingle-year Grants
Review Section Science and Engineering
Research InstitutionThe University of Tokyo

Principal Investigator

Tsuda Koji  東京大学, 大学院新領域創成科学研究科, 教授 (90357517)

Co-Investigator(Kenkyū-buntansha) 志賀 元紀  岐阜大学, 工学部, 准教授 (20437263)
鹿島 久嗣  京都大学, 情報学研究科, 教授 (80545583)
Co-Investigator(Renkei-kenkyūsha) TAKEUCHI Ichiro  名古屋工業大学, 工学(系)研究科, 教授 (40335146)
Project Period (FY) 2016-04-01 – 2018-03-31
Keywordsマテリアルズインフォマティクス
Outline of Final Research Achievements

This research started from 2016 to boost the development of informatics methods in materials development. As a result of collaborations with other groups, we obtained the following achievements. (1) Statistical machine learning methods for spectrum analysis to discovering nanostructures. (2) Automatic design of materials using Monte Carlo tree search. (3) Discovery of stable compounds with recommendation algorithms.

Free Research Field

機械学習、バイオインフォマティクス

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Published: 2019-03-29  

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