ライセンス: In Copyright キーワード: machine learning
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4 件のレコードが見つかりました。 1件目から4件目まで表示します。

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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
manuscript.docx
Accelerating Materials Discovery of Novel Europium(II)-Activated Phosphors through Machine Learning Classification of Europium Valences
ジャーナル論文
著者
ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI
キーワード
phosphor, machine learning, europium, oxidation state
刊行年月日
2024-12-10
更新時刻
2025-11-25 08:30:03 +0900
2025 ogawa APL final.pdf
Er-driven magnetic tunability in FePt thin films investigated via high-throughput experiments and microstructure analysis for future HAMR media
ジャーナル論文
著者
Daisuke Ogawa (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 ;
Jun Uzuhashi (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yuta Sasaki (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Masato Kotsugi (author) (この著者で検索)
;
Yukiko K. Takahashi (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
heat-assisted magnetic recording, FePt, combinatorial, high throughput, machine learning, rare-earth doping
刊行年月日
2025-06-23
更新時刻
2025-07-11 08:30:48 +0900
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
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