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

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
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
Abstract_YenJu Wu.docx
Designing Thermal Insulating thin films with Data-Driven Innovation
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, thin film
刊行年月日
更新時刻
2025-03-12 16:30:31 +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
esi_clean.pdf
Multiobjective Solid Electrolyte Design of Tetragonal and Cubic Inverse-Perovskites for All-Solid-State Lithium-Ion Batteries by High-Throughput Density Functional Theory Calculations and AI-Driven Methods
ジャーナル論文
著者
JALEM Randy (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/Interface Electrochemistry Group
ORCID SAMURAI ;
TATEYAMA Yoshitaka (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/Interface Electrochemistry Group
ORCID SAMURAI ;
TAKADA Kazunori (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/Solid-State Battery Group
ORCID SAMURAI ;
JANG Seonghoon (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/Interface Electrochemistry Group
キーワード
all solid state batteries, solid electrolytes, density functional theory, materials informatics, machine learning, novel materials search
刊行年月日
2023-09-07
更新時刻
2024-08-28 08:30:15 +0900
Dataset
Supercon 2 Dataset
データセット
著者
ORCID
キーワード
superconductors, machine learning, dataset, tdm, materials science
刊行年月日
2022-09-10
更新時刻
2022-10-18 10:11:01 +0900
Advanced Science - 2025 - Si - Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy.pdf
Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning
ジャーナル論文
著者
Qianli Si (author) (この著者で検索)
National Institute for Materials Science
;
Shoichi Matsuda (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yasunobu Ando (author) (この著者で検索)
;
Toshiyuki Momma (author) (この著者で検索)
;
Yoshitaka Tateyama (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
lithium metal battery, machine learning
刊行年月日
2025-05-05
更新時刻
2025-09-09 12:30:20 +0900
AdvMater.25_37_e10239.pdf
Artificial Intelligence‐Driven Nanoarchitectonics for Smart Targeted Drug Delivery
ジャーナル論文
著者
Hayeon Bae (author) (この著者で検索)
;
Hyunsub Ji (author) (この著者で検索)
;
Konstantin Konstantinov (author) (この著者で検索)
;
Ronald Sluyter (author) (この著者で検索)
;
Katsuhiko Ariga (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yong Ho Kim (author) (この著者で検索)
;
Jung Ho Kim (author) (この著者で検索)
キーワード
artificial intelligence, in silico optimization, machine learning, nanocarrier design, nanomedicine, targeted drug delivery
刊行年月日
2025-08-07
更新時刻
2025-10-28 12:30:13 +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
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