キーワード: Machine learning
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22 件のレコードが見つかりました。 1件目から10件目まで表示します。

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Minami_20250723final_w_highlight.pdf
Estimation of valence state and growth rate using principal component analysis of plasma emission in reactive sputtering deposition
ジャーナル論文
著者
Rintaro Minami (author) (この著者で検索)
University of Tsukuba a Department of Applied Physics
;
Eiji Kita (author) (この著者で検索)
;
Chiharu Mitsumata (author) (この著者で検索)
;
Hideto Yanagihara (author) (この著者で検索)
キーワード
Machine learning, principal component analysis (PCA), reactive magnetron sputtering, plasma emission spectrum, Mössbauer spectroscopy
刊行年月日
2025-12-31
更新時刻
2025-09-10 16:30:38 +0900
Manuscript.pdf
In Situ Forming Supramolecular Nanofiber Hydrogel as a Biodegradable Liquid Embolic Agent for Postembolization Tissue Remodeling
ジャーナル論文
著者
Akihiro Nishiguchi (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Miho Ohta (author) (この著者で検索)
;
Debabrata Palai (author) (この著者で検索)
National Institute for Materials Science
ORCID ;
Shima Ito (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Kensaku Mori (author) (この著者で検索)
;
Ryotaro Akagi (author) (この著者で検索)
;
Christophe Bajan (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Guillaume Lambard (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Keitaro Sodeyama (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Tetsushi Taguchi (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
Hydrogel, Embolic agent, Machine learning
刊行年月日
2024-11-07
更新時刻
2025-02-26 16:30:29 +0900
main.pdf
Data-driven analysis of hydrogen embrittlement in martensitic steels with interpretable machine learning
ジャーナル論文
著者
ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI
キーワード
Hydrogen embrittlement, Martensitic steel, Machine learning, hap (shapley additive explanations), Symbolic regression
刊行年月日
2026-04-23
更新時刻
2026-06-17 09:57:29 +0900
Extraction of physicochemical laws by symbolic regression using a Bayesian information criterion.pdf
Extraction of physicochemical laws by symbolic regression using a Bayesian information criterion
ジャーナル論文
著者
Naoki Yamane (author) (この著者で検索)
Tsukuba University
;
Kan Hatakeyama-Sato (author) (この著者で検索)
東京工業大学
;
Yuma Iwasaki (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 Materials Design Group
ORCID SAMURAI ;
Yasuhiko Igarashi (author) (この著者で検索)
Tsukuba University
キーワード
Machine learning
刊行年月日
2024-12-31
更新時刻
2024-11-14 16:30:30 +0900
s41524-025-01757-5 (2).pdf
High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning
ジャーナル論文
著者
ORCID SAMURAI ; ORCID SAMURAI ; ORCID ; ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI
キーワード
Machine learning, High-throughput, Combinatorial, Anomalous Hall effect
刊行年月日
2025-09-03
更新時刻
2025-12-26 13:11:05 +0900
Autonomous search for materials with high Curie temperature using ab initio calculations and machine learning (1).pdf
Autonomous search for materials with high Curie temperature using ab initio calculations and machine learning
ジャーナル論文
著者
ORCID SAMURAI
キーワード
Machine learning, Autonomous, Curie temperature, ab initio
刊行年月日
2024-12-31
更新時刻
2024-10-04 08:30:28 +0900
s41524-025-01828-7.pdf
Autonomous closed-loop exploration of composition-spread films for the anomalous Hall effect
ジャーナル論文
著者
ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI
キーワード
Machine learning, Autonomous, Combinatorial, Anomalous Hall effect
刊行年月日
2025-11-19
更新時刻
2025-12-25 17:32:06 +0900
2024_Exploring new useful phosphors by combining experiments with machine learning.pdf
Exploring new useful phosphors by combining experiments with machine learning
ジャーナル論文
著者
ORCID SAMURAI ; ORCID SAMURAI ;
Hidekazu Ikeno (author) (この著者で検索)
; ORCID SAMURAI ; ORCID SAMURAI
キーワード
Phosphor, High-throughput experiment, Machine learning, Local structure, Europium
刊行年月日
2024-12-31
更新時刻
2024-12-05 16:30:28 +0900
DataSummary_Extrusion_Manuscript_20210728.xlsx
Process parameters and magnetic properties (coercivity, remanence, squareness, maximum energy product) of data-driven fabrication of Nd-Fe-B anisotropic magnets by direct hot extrusion.
データセット
著者
ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI
キーワード
Maximum energy product, Coercivity, Squareness, Machine learning, Remanence, Process, Bayesian Optimization, Hot extrusion, Active learning, Nd-Fe-B magnet
刊行年月日
2021-10-11
更新時刻
2022-10-03 02:01:08 +0900
Fujii-DigitalDiscovery2025.pdf
A straightforward gradient-based approach for designing superconductors with high critical temperature: exploiting domain knowledge via adaptive constraints
ジャーナル論文
著者
Akihiro Fujii (author) (この著者で検索)
;
Anh Khoa Augustin Lu (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Koji Shimizu (author) (この著者で検索)
;
Satoshi Watanabe (author) (この著者で検索)
National Institute for Materials Science
ORCID
キーワード
Gradient-based optimization, Superconductor, Domain knowledge integration, Materials discovery, Critical temperature, Machine learning
刊行年月日
2025-10-29
更新時刻
2026-05-18 14:53:14 +0900
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