キーワード: machine learning
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34 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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Dielectric tensor of perovskite oxides at finite temperature using equivariant graph neural network potentials.pdf
Dielectric tensor of perovskite oxides at finite temperature using equivariant graph neural network potentials
ジャーナル論文
著者
Alex Kutana (author) (この著者で検索)
Nagoya University
;
Koki Yoshimochi (author) (この著者で検索)
;
Ryoji Asahi (author) (この著者で検索)
キーワード
Graph neural network, machine learning, dielectrics, perovskite oxides, phase transitions
刊行年月日
2025-12-31
更新時刻
2025-07-18 10:24:15 +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
ChemPlusChem25_90_e202500342.pdf
Machine Learning—Guided Design of Biomass‐Based Porous Carbon for Aqueous Symmetric Supercapacitors
ジャーナル論文
著者
Manickam Minakshi (author) (この著者で検索)
ORCID ;
Apsana Sharma (author) (この著者で検索)
;
Ferdous Sohel (author) (この著者で検索)
;
Almantas Pivrikas (author) (この著者で検索)
ORCID ;
Pragati A. Shinde (author) (この著者で検索)
ORCID ; ORCID SAMURAI ; ORCID SAMURAI
キーワード
biomass, carbon, dopant, energy, machine learning, storage
刊行年月日
2025-10-09
更新時刻
2025-10-21 16:06:10 +0900
2604_supp_info.pdf
Non-negative matrix factorization analysis of spatially-resolved photoemission spectra for epitaxially grown graphene on SiC
ジャーナル論文
著者
Masaki Imamura (author) (この著者で検索)
Saga University Synchrotron Light Application Center
;
Kazutoshi Takahashi (author) (この著者で検索)
キーワード
Photoemission spectroscopy, non-negative matrix factorization, graphene, machine learning, data-driven analysis
刊行年月日
2026-06-19
更新時刻
2026-06-24 15:38:41 +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
Manuscript_clean.pdf
Machine learning prediction of Young's modulus in multi component titanium based biomedical alloys using extended thermodynamic descriptors
ジャーナル論文
著者
Hassan Ahmad (author) (この著者で検索)
Pakistan Institute of Engineering and Applied Sciences (PIEAS) Department of Metallurgy and Materials Engineering
;
Muhammad Haider (author) (この著者で検索)
;
Zafar Iqbal (author) (この著者で検索)
;
Muhammad Zarif (author) (この著者で検索)
;
Syed Mujtaba Ul Hassan (author) (この著者で検索)
キーワード
Titanium alloys, machine learning, biomedical alloys, Young’s modulus prediction
刊行年月日
2026-12-31
更新時刻
2026-07-08 16:58:38 +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
Abstract for 7th Academic Collaboration Seminar.pdf
Data-driven approaches for designing thermal insulating materials
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
Interfacial thermal resistance, machine learning, thermal insulator, data-driven technique
刊行年月日
更新時刻
2024-12-25 16:30:37 +0900
Acquiring and transferring comprehensive catalyst knowledge through integrated high-throughput experimentation and automatic feature engineering.pdf
Acquiring and transferring comprehensive catalyst knowledge through integrated high-throughput experimentation and automatic feature engineering
ジャーナル論文
著者
Ayu Fujiwara (author) (この著者で検索)
Japan Advanced Institute of Science and Technology Graduate School of Advanced Science and Technology
;
Sunao Nakanowatari (author) (この著者で検索)
Japan Advanced Institute of Science and Technology Graduate School of Advanced Science and Technology
;
Yohei Cho (author) (この著者で検索)
Japan Advanced Institute of Science and Technology Graduate School of Advanced Science and Technology
;
Toshiaki Taniike (author) (この著者で検索)
Japan Advanced Institute of Science and Technology Graduate School of Advanced Science and Technology
キーワード
Catalyst informatics, machine learning, high-throughput experimentation, descriptor, oxidative coupling of methane
刊行年月日
2025-12-31
更新時刻
2025-07-16 16:17:04 +0900
STAMMethods4(2024)2326305.pdf
Alloys innovation through machine learning: a statistical literature review
ジャーナル論文
著者
Alireza Valizadeh (author) (この著者で検索)
;
Ryoji Sahara (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Maaouia Souissi (author) (この著者で検索)
キーワード
Alloy development, machine learning, data-driven research, materials informatics, Materials Genome Initiative, Materials databases
刊行年月日
2024-12-31
更新時刻
2024-06-25 12:30:16 +0900
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