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The 31st Annual Meeting of MRS-J Program List: Poster

D:Challenges toward Materials Informatics 2.0

Entry No Presentation Date Award Presenteation
Dec. 14
16:00 - 17:00
Online 15:30～16:00　事前接続確認
16:00～17:00　発表コアタイム
2026   D-P14-002 Dec. 14  *D Grain boundary simulation of NASICON-type Li-ion conductor LiZr2(PO4)3 using machine learning and molecular dynamics simulations
 

Koki NAKANO1,2),Naoto TANIBATA1,3),Hayami TAKEDA1,3),Ryo KOBAYASHI1),Masanobu NAKAYAMA1,2,3)(1)Nagoya Institute of Technology,2)Frontier Research Institute for Materials Science (FRIMS),3)Unit of Elements Strategy Initiative for Catalysts & Batteries (ESICB))
2027   D-P14-003 Dec. 14  Search for high ionic conductivity composition of solid electrolyte using both experiments and Bayesian optimization
 

Hayami TAKEDA1,2),Maho HARADA1),Zijian YANG1),Koki NAKANO1,3),Naoto TANIBATA1,2),Masanobu NAKAYAMA1,2)(1)Nagoya Institute of Technology,2)Unit of Elements Strategy Initiative for Catalysts & Batteries,3)Frontier Research Institute for Materials Science,,Nagoya Institute of Technology)
2089   D-P14-004 Dec. 14  *M Drawing a materials map with autoencoder for Li ionic conductors
 

Yudai YAMAGUCHI1),Risa YASUDA1),Taruto ATSUMI1),Naoto TANIBATA1,2),Hayami TAKEDA1,2),Masanobu NAKAYAMA1,2)(1)Nagoya Institute of Technology,2)Unit of Elements Strategy Initiative for Catalysts & Batteries (ESICB))
Dec. 14
17:00 - 18:00
15:30～16:00　事前接続確認
17:00～18:00　発表番号前半のコアタイム
2362   D-P14-005 Dec. 14  Higher-order Structure-Property Relationships of Poly(L-lactide) using Graphical Models
 

Hiroteru KIKUTAKE1),Ken KOJIO1,2),Kei TERAYAMA3,4),Yoshifumi AMAMOTO1,2),Atsushi TAKAHARA1,2)(1)Graduate School of Engineering, Kyushu University,2)Institute for Materials Chemistry and Engineering, Kyushu University,3)Graduate School of Medical Life Science, Yokohama City University,4)RIKEN Center for Advanced Intelligence Project)
2454   D-P14-006 Dec. 14  Attempts towards databasing first-principles calculations of alloy nanoparticles
 

Yusuke NANBA1),Masashi ISHIZAWA1),Michihisa KOYAMA1,2)(1)Research Initiative for Supra-Materials, Shinshu University,2)Open Innovation Institute, Kyoto University)
2502   D-P14-007 Dec. 14  Prediction of Product Composition in Catalytic Reactions using Machine Learning with Physics-based Feature Engineering
 

Iori SHIMADA1),Shun YASUIKE2),Mitsumasa OSADA1),Hiroshi FUKUNAGA1),Michihisa KOYAMA3)(1)Faculty of Textile Science and Technology, Shinshu University,2)Graduate School of Science and Technology, Shinshu University,3)RISM, Shinshu University)