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

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
Time-domain thermoreflectance technique using multiple delayed probe pulses for high-throughput data acquisition and analysis.pdf
Time-domain thermoreflectance technique using multiple delayed probe pulses for high-throughput data acquisition and analysis
ジャーナル論文
著者
Hiroto Arima (author) (この著者で検索)
National Institute of Advanced Industrial Science and Technology (AIST) National Metrology Institute of Japan (NMIJ)
;
Yuichiro Yamashita (author) (この著者で検索)
;
Takashi Yagi (author) (この著者で検索)
キーワード
Time-domain thermoreflectance, multiple delay, thin film, thermal effusivity, interfacial thermal resistance, machine learning
刊行年月日
2025-12-31
更新時刻
2025-07-16 16:14:58 +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
jmca2024_NaSulfideConductor_esi_rj.pdf
Computational discovery of stable Na-ion sulfide solid electrolytes with high conductivity at room temperature
ジャーナル論文
著者
Seong-Hoon Jang (author) (この著者で検索)
ORCID ;
Randy Jalem (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yoshitaka Tateyama (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
all solid state batteries, solid electrolytes, high-throughput first-principles calculation, computational materials search, machine learning, sodium ion conductors
刊行年月日
2024-08-05
更新時刻
2024-10-10 16:30:52 +0900
Automatic_extraction_of_materials_and_properties_from_superconductors_scientific_literature-v1.pdf
Automatic Extraction of Materials and Properties from Superconductors Scientific Literature
ジャーナル論文
著者
Foppiano Luca (author) (この著者で検索)
NIMS MaDIS
ORCID ;
Baptista de Castro, Pedro (author) (この著者で検索)
NIMS MANA
ORCID ;
Ortiz Suarez, Pedro (author) (この著者で検索)
University of Mannheim Data and Web Science Group
ORCID ; ORCID SAMURAI ; ORCID SAMURAI ;
Ishii, Masashi (author) (この著者で検索)
NIMS MaDIS
ORCID
キーワード
tdm, machine learning, materials science, superconductors, database
刊行年月日
2022-09-15
更新時刻
2022-10-16 01:44:51 +0900
materials-17-02866.pdf
Multi-Objective Optimization of Adhesive Joint Strength and Elastic Modulus of Adhesive Epoxy with Active Learning
ジャーナル論文
著者
ORCID SAMURAI ; ORCID SAMURAI ;
Chao Kang (author) (この著者で検索)
ORCID ;
Chiaki Sato (author) (この著者で検索)
キーワード
experimental testing, multi-objective optimization, epoxy, adhesive, elastic modulus, machine learning, active learning
刊行年月日
2024-06-12
更新時刻
2025-01-07 08:30:26 +0900
manuscript.docx
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
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
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
Estimation the S-N Curve by Machine Learning Random Forest Method_Mater. Trans. 65(2024)428-433.pdf
Estimating the S-N Curve by Machine Learning Random Forest Method
ジャーナル論文
著者
Nobuo Nagashima (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Masao Hayakawa (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Hiroyuki Masuda (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Kotobu Nagai (author) (この著者で検索)
National Institute for Materials Science
キーワード
fatigue, high-cycle fatigue, data-sheet, machine learning, random forest method
刊行年月日
2024-04-01
更新時刻
2024-12-27 16:30:58 +0900