ファイル種別: application/pdf キーワード: machine learning
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41 件のレコードが見つかりました。

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
Predicting the surface roughness of an electrodeposited copper film using a machine learning technique.pdf
Predicting the surface roughness of an electrodeposited copper film using a machine learning technique
ジャーナル論文
著者
Ryo Tamura (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 Algorithm Team
ORCID SAMURAI ;
Ryuichi Inaba (author) (この著者で検索)
MITSUBISHI MATERIALS CORPORATION
;
Mami Watanabe (author) (この著者で検索)
MITSUBISHI MATERIALS CORPORATION
;
Yutaro Mori (author) (この著者で検索)
MITSUBISHI MATERIALS CORPORATION
;
Makoto Urushihara (author) (この著者で検索)
MITSUBISHI MATERIALS CORPORATION
;
Kenji Yamaguchi (author) (この著者で検索)
MITSUBISHI MATERIALS CORPORATION
;
Shoichi Matsuda (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/Automated Electrochemical Experiments Team
ORCID SAMURAI
キーワード
electrodeposited copper film, surface roughness, machine learning
刊行年月日
2024-12-31
更新時刻
2024-10-31 16:30:15 +0900
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
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
Supplementary information.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
Understanding strain localization in metallic materials a review of high-resolution digital image correlation and related techniques.pdf
Understanding strain localization in metallic materials: a review of high-resolution digital image correlation and related techniques
ジャーナル論文
著者
ORCID SAMURAI ;
T. E.J. Edwards (author) (この著者で検索)
;
J. Quinta da Fonseca (author) (この著者で検索)
;
J. -C. Stinville (author) (この著者で検索)
;
D. Texier (author) (この著者で検索)
;
T. Vermeij (author) (この著者で検索)
キーワード
High-resolution digital image correlation, strain localization, crystal plasticity, data merging, metallic materials, machine learning
刊行年月日
2026-12-31
更新時刻
2026-03-13 08:30:04 +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
41524_2019_203_MOESM1_ESM.avi
Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm
ジャーナル論文
著者
Stephen Wu (author) (この著者で検索)
;
Yukiko Kondo (author) (この著者で検索)
;
Masa-aki Kakimoto (author) (この著者で検索)
;
Bin Yang (author) (この著者で検索)
;
Hironao Yamada (author) (この著者で検索)
; ORCID SAMURAI ;
Guillaume Lambard (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Kenta Hongo (author) (この著者で検索)
; ORCID SAMURAI ;
Junichiro Shiomi (author) (この著者で検索)
;
Christoph Schick (author) (この著者で検索)
;
Junko Morikawa (author) (この著者で検索)
;
Ryo Yoshida (author) (この著者で検索)
キーワード
machine learning, polymer, thermal conductivity, molecular design
刊行年月日
2019-06-21
更新時刻
2024-11-21 16:31:23 +0900
_最終稿版_機械学習による光電子収量分光PYSスペクトルの自動閾値予測200629.pdf
Automatic Threshold Prediction of Photoelectron Yield Spectroscopy (PYS) by Machine Learning
ジャーナル論文
著者
ORCID SAMURAI ;
YOSHITAKE, Michiko (author) (この著者で検索)
; ORCID SAMURAI ; ORCID SAMURAI
キーワード
threshold, machine learning, photoelectron yield spectroscopy
刊行年月日
2020-06-10
更新時刻
2024-01-05 22:12:44 +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