キーワード: machine learning
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36 件のレコードが見つかりました。 31件目から36件目まで表示します。

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esi_clean.pdf
Multiobjective Solid Electrolyte Design of Tetragonal and Cubic Inverse-Perovskites for All-Solid-State Lithium-Ion Batteries by High-Throughput Density Functional Theory Calculations and AI-Driven Methods
ジャーナル論文
著者
JALEM Randy (author) (この著者で検索)
National Institute for Materials Science Research Center for Energy and Environmental Materials (GREEN)/Battery and Cell Materials Field/Interface Electrochemistry Group
ORCID SAMURAI ;
TATEYAMA Yoshitaka (author) (この著者で検索)
National Institute for Materials Science Research Center for Energy and Environmental Materials (GREEN)/Battery and Cell Materials Field/Interface Electrochemistry Group
ORCID SAMURAI ;
TAKADA Kazunori (author) (この著者で検索)
National Institute for Materials Science Research Center for Energy and Environmental Materials (GREEN)/Battery and Cell Materials Field/Solid-State Battery Group
ORCID SAMURAI ;
JANG Seonghoon (author) (この著者で検索)
National Institute for Materials Science Research Center for Energy and Environmental Materials (GREEN)/Battery and Cell Materials Field/Interface Electrochemistry Group
キーワード
all solid state batteries, solid electrolytes, density functional theory, materials informatics, machine learning, novel materials search
刊行年月日
2023-09-07
更新時刻
2024-08-28 08:30:15 +0900
manuscript.docx
Machine learning approach for the prediction of electron inelastic mean free paths
ジャーナル論文
著者
Xun Liu (author) (この著者で検索)
National Institute for Materials Science
;
Lihao Yang (author) (この著者で検索)
;
Zhufeng Hou (author) (この著者で検索)
;
Bo Da (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Kenji Nagata (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Hideki Yoshikawa (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Shigeo Tanuma (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yang Sun (author) (この著者で検索)
;
Zejun Ding (author) (この著者で検索)
キーワード
machine learning, inelastic mean free path
刊行年月日
2021-03-24
更新時刻
2024-01-05 22:13:49 +0900
Pitfalls in Artificial Intelligence_revised_clean_v2.docx
Pitfalls in Artificial Intelligence Powered Discovery Due to Electrocatalyst Evaluation Methodologies
ジャーナル論文
著者
Abraham Castro Garcia (author) (この著者で検索)
;
Ken Sakaushi (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
machine learning
刊行年月日
2025-09-04
更新時刻
2026-04-30 12:01:11 +0900
s41524-025-01851-8 (1).pdf
Networking autonomous material exploration systems through transfer learning
ジャーナル論文
著者
Naoki Yoshida (author) (この著者で検索)
;
Yutaro Iwabuchi (author) (この著者で検索)
;
Yasuhiko Igarashi (author) (この著者で検索)
;
Yuma Iwasaki (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
machine learning
刊行年月日
2025-12-09
更新時刻
2025-12-13 08:30:26 +0900
Varun Co-Fe Cu CIP-GMR AIP Advances (2024).pdf
Analysis of the effect of the Fermi surface matching at Co–Fe and Cu interface on giant magnetoresistance effect using a combinatorial technique
ジャーナル論文
著者
Varun Kumar Kushwaha (author) (この著者で検索)
National Institute for Materials Science
ORCID ;
Ryo Toyama (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yoshio Miura (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yuma Iwasaki (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yuya Sakuraba (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
spintronics, giant magnetoresistance, machine learning, Fermi surface, interfacial electronic band matching
刊行年月日
2024-12-01
更新時刻
2025-01-07 16:30:50 +0900
jmca2024_NaSulfideConductor_esi_rj.pdf
Computational discovery of stable Na-ion sulfide solid electrolytes with high conductivity at room temperature
ジャーナル論文
著者
Seong-Hoon Jang (author) (この著者で検索)
ORCID ;
Randy Jalem (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yoshitaka Tateyama (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
all solid state batteries, solid electrolytes, high-throughput first-principles calculation, computational materials search, machine learning, sodium ion conductors
刊行年月日
2024-08-05
更新時刻
2024-10-10 16:30:52 +0900
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