ライセンス: In Copyright キーワード: machine learning

5 件のレコードが見つかりました。 1件目から5件目まで表示します。

2025秋季応用物理学会.pdf
Structure Prediction from Chemical Formula Using Periodic Descriptors
プレゼンテーション
著者
Yen-Ju Wu (author) (この著者で検索)
National Institute for Materials Science Center for Basic Research on Materials/Data-driven Materials Research Field/Data-driven Inorganic Materials Group
ORCID SAMURAI ;
Yibin Xu (author) (この著者で検索)
National Institute for Materials Science Center for Basic Research on Materials/Data-driven Materials Research Field/Data-driven Inorganic Materials Group
ORCID SAMURAI
キーワード
periodic descriptor, structure prediction, machine learning, template substitution
刊行年月日
更新時刻
2025-09-13 08:30:19 +0900

3-12-Revised Manuscript without Any Highlighting.docx
Machine-Learning-Driven Discovery of Mn4+-Doped Red-Emitting Fluorides with Short Excited-State Lifetime and High Efficiency for Mini Light-Emitting Diode Displays
ジャーナル論文
著者
Hong Ming (author) (この著者で検索)
ORCID ;
Yayun Zhou (author) (この著者で検索)
;
Maxim S. Molokeev (author) (この著者で検索)
ORCID ;
Chuang Zhang (author) (この著者で検索)
;
Lin Huang (author) (この著者で検索)
;
Yuanjing Wang (author) (この著者で検索)
; ORCID SAMURAI ;
Enhai Song (author) (この著者で検索)
ORCID ;
Qinyuan Zhang (author) (この著者で検索)
ORCID
キーワード
luminescent materials, machine learning
刊行年月日
2024-05-06
更新時刻
2025-04-03 08:30:20 +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)
ORCID SAMURAI ;
Yuma Iwasaki (author) (この著者で検索)
ORCID SAMURAI ;
Jun Uzuhashi (author) (この著者で検索)
ORCID SAMURAI ;
Yuta Sasaki (author) (この著者で検索)
ORCID SAMURAI ;
Masato Kotsugi (author) (この著者で検索)
;
Yukiko K. Takahashi (author) (この著者で検索)
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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