キーワード: Machine learning
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9 件のレコードが見つかりました。 1件目から9件目まで表示します。

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manuscript.docx
Machine Learning Approach for Evaluation of Nanodefects and Magnetic Anisotropy in FePt Granular Films
ジャーナル論文
著者
E. Dengina (author) (この著者で検索)
National Institute for Materials Science
;
A. Bolyachkin (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
H. Sepehri-Amin (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
K. Hono (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
Magnetic recording, Micromagnetic simulations, Machine learning, FePt media
刊行年月日
2022-05-13
更新時刻
2024-10-15 16:30:13 +0900
1-s2.0-S135964542400692X-main.pdf
Process optimization on kesterite-based ceramics for enhancing their thermoelectric performances assisted by active machine learning approach: A tool for metal-sulfide ceramics development
ジャーナル論文
著者
Cédric Bourgès (author) (この著者で検索)
National Institute for Materials Science
ORCID ;
Guillaume Lambard (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Naoki Sato (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Makoto Tachibana (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Satoshi Ishii (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Takao Mori (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
Kesterite, Machine learning, Process, Thermoelectric, Ceramic
刊行年月日
2024-08-29
更新時刻
2024-09-20 16:30:30 +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
lin-et-al-2025-determination-of-stable-proton-configurations-by-black-box-optimization-using-an-ising-machine.pdf
Determination of Stable Proton Configurations by Black-Box Optimization Using an Ising Machine
ジャーナル論文
著者
Jianbo Lin (author) (この著者で検索)
;
Tomofumi Tada (author) (この著者で検索)
ORCID ;
Ai Koizumi (author) (この著者で検索)
;
Masato Sumita (author) (この著者で検索)
ORCID ; ORCID SAMURAI ; ORCID SAMURAI
キーワード
Machine learning, Ising machine, Proton configuration
刊行年月日
2025-02-06
更新時刻
2025-05-23 08:30:18 +0900
Autonomous search for half-metallic materials with B2 structure.pdf
Autonomous search for half-metallic materials with B 2 structure
ジャーナル論文
著者
ORCID SAMURAI ; ORCID SAMURAI ;
Takahiro Yamazaki (author) (この著者で検索)
ORCID ;
Yasuhiko Igarashi (author) (この著者で検索)
ORCID ;
Masato Kotsugi (author) (この著者で検索)
ORCID ; ORCID SAMURAI
キーワード
Machine learning, Autonomous, ab initio, Half metal
刊行年月日
2024-12-31
更新時刻
2024-10-04 08:30:32 +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
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
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
Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis.pdf
Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis
ジャーナル論文
著者
Ryo Tamura (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)
;
Keitaro Sodeyama (author) (この著者で検索)
;
Kensaku Nakamura (author) (この著者で検索)
;
Toshiki Tokuhira (author) (この著者で検索)
;
Satoshi Shibata (author) (この著者で検索)
;
Kazuki Hammura (author) (この著者で検索)
;
Hiroki Sugisawa (author) (この著者で検索)
;
Masaya Kawamura (author) (この著者で検索)
;
Teruki Tsurimoto (author) (この著者で検索)
;
Masanobu Naito (author) (この著者で検索)
;
Masahiko Demura (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Takashi Nakanishi (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
Polypropylene, X-ray diffraction, Bayesian spectral deconvolution, Ising machine, Machine learning
刊行年月日
2024-12-31
更新時刻
2024-08-30 16:31:01 +0900
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