キーワード: machine learning
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Machine learning approach for the prediction of electron inelastic mean free paths
ジャーナル論文
著者
Xun Liu (author) (この著者で検索)
National Institute for Materials Science
;
Lihao Yang (author) (この著者で検索)
;
Zhufeng Hou (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 ;
Kenji Nagata (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
刊行年月日
2021-03-24
更新時刻
2024-01-05 22:13:49 +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
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
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
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
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
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
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
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
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
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