キーワード: machine learning
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35 件のレコードが見つかりました。

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
d2ma00881e.pdf
Rapid discovery of new Eu2+-activated phosphors with a designed luminescence color using a data-driven approach
ジャーナル論文
著者
Yukinori Koyama (author) (この著者で検索)
National Institute for Materials Science Research and Services Division of Materials Data and Integrated System
ORCID SAMURAI ;
Hidekazu Ikeno (author) (この著者で検索)
Osaka Metropolitan University
;
Masamichi Harada (author) (この著者で検索)
National Institute for Materials Science Research Center for Functional Materials
;
Shiro Funahashi (author) (この著者で検索)
National Institute for Materials Science Research Center for Functional Materials
;
Takashi Takeda (author) (この著者で検索)
National Institute for Materials Science Research Center for Functional Materials
ORCID SAMURAI ;
Naoto Hirosaki (author) (この著者で検索)
National Institute for Materials Science Research Center for Functional Materials
キーワード
phosphor, materials design, machine learning, luminescence, emission spectrum, Eu2+
刊行年月日
2022-11-29
更新時刻
2024-01-05 22:11:23 +0900
jpsj.94.031005.pdf
Self-Energy Spectroscopy and Artificial Neural Network
ジャーナル論文
著者
ORCID SAMURAI
キーワード
machine learning, quantum materials, photoemission spectroscopy, high-temperature superconductivity
刊行年月日
2025-03-15
更新時刻
2025-02-27 12:30:42 +0900
s41524-025-01671-w.pdf
Discovery of liquid crystalline polymers with high thermal conductivity using machine learning
ジャーナル論文
著者
Hayato Maeda (author) (この著者で検索)
ORCID ;
Stephen Wu (author) (この著者で検索)
ORCID ;
Rika Marui (author) (この著者で検索)
ORCID ;
Erina Yoshida (author) (この著者で検索)
;
Kan Hatakeyama-Sato (author) (この著者で検索)
;
Yuta Nabae (author) (この著者で検索)
;
Shiori Nakagawa (author) (この著者で検索)
;
Meguya Ryu (author) (この著者で検索)
;
Ryohei Ishige (author) (この著者で検索)
;
Yoh Noguchi (author) (この著者で検索)
;
Yoshihiro Hayashi (author) (この著者で検索)
ORCID ; ORCID SAMURAI ; ORCID SAMURAI ;
Felix Jiang (author) (この著者で検索)
;
Xuan Thang Vu (author) (この著者で検索)
;
Sven Ingebrandt (author) (この著者で検索)
ORCID ;
Masatoshi Tokita (author) (この著者で検索)
;
Junko Morikawa (author) (この著者で検索)
ORCID ;
Ryo Yoshida (author) (この著者で検索)
ORCID ;
Teruaki Hayakawa (author) (この著者で検索)
キーワード
liquid crystalline polymer, thermal conductivity, machine learning, PoLyInfo
刊行年月日
2025-07-02
更新時刻
2025-08-19 12:30:21 +0900
shrine20230330-1595-1im5f61.pdf
Unveiling the principle descriptor for predicting the electron inelastic mean free path based on a machine learning framework
ジャーナル論文
著者
Xun Liu (author) (この著者で検索)
National Institute for Materials Science
;
Zhufeng Hou (author) (この著者で検索)
;
Dabao Lu (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 ;
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, LASSO
刊行年月日
2019-12-31
更新時刻
2024-09-05 16:30:30 +0900
Manuscript.pdf
Graph Network-Based Simulation of Multicellular Dynamics Driven by Concentrated Polymer Brush-Modified Cellulose Nanofibers
ジャーナル論文
著者
Chiaki Yoshikawa (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Duc Anh Nguyen (author) (この著者で検索)
;
Tadashi Nakaji-Hirabayashi (author) (この著者で検索)
;
Ichigaku Takigawa (author) (この著者で検索)
;
Hiroshi Mamitsuka (author) (この著者で検索)
キーワード
cellulose nanofiber, concentrated polymer brush, hMSC, self-assembly, machine learning
刊行年月日
2024-04-08
更新時刻
2024-08-27 08:30:31 +0900
Advanced Science - 2023 - Uryu - Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder.pdf
Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder Diffraction Patterns
ジャーナル論文
著者
Hirotaka Uryu (author) (この著者で検索)
;
Tsunetomo Yamada (author) (この著者で検索)
;
Koichi Kitahara (author) (この著者で検索)
;
Alok Singh (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yutaka Iwasaki (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Kaoru Kimura (author) (この著者で検索)
National Institute for Materials Science
ORCID ;
Kanta Hiroki (author) (この著者で検索)
;
Naoki Miyao (author) (この著者で検索)
;
Asuka Ishikawa (author) (この著者で検索)
;
Ryuji Tamura (author) (この著者で検索)
;
Satoshi Ohhashi (author) (この著者で検索)
;
Chang Liu (author) (この著者で検索)
;
Ryo Yoshida (author) (この著者で検索)
キーワード
deep learning, x-ray powder diffraction, quasicrystal, phase identification, machine learning
刊行年月日
2023-11-14
更新時刻
2024-12-13 12:30:39 +0900
nanomaterials-3261714-Revision_T.pdf
Machine Learning as a “Catalyst” for Advancements in Carbon Nanotube Research
ジャーナル論文
著者
Guohai Chen (author) (この著者で検索)
ORCID ; ORCID SAMURAI
キーワード
machine learning, carbon nanotube, in situ TEM, growth mechanism
刊行年月日
2024-10-22
更新時刻
2024-12-24 13:58:23 +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
An interpretable linear model bridging data-driven analysis and chemical intuition for Eu2 -phosphor emissions.pdf
An interpretable linear model bridging data-driven analysis and chemical intuition for Eu 2+ -phosphor emissions
ジャーナル論文
著者
ORCID SAMURAI ;
Ryusei Hayasaka (author) (この著者で検索)
;
Yuta Matsushima (author) (この著者で検索)
ORCID ; ORCID SAMURAI ; ORCID SAMURAI ;
Naoto Hirosaki (author) (この著者で検索)
キーワード
materials informatics, phosphor, europium, machine learning, interpretability, linear model, composition-based feature
刊行年月日
2026-12-31
更新時刻
2026-07-07 14:31:04 +0900