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ジャーナル論文(28)
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Machine learning (36)
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キーワード: Machine learning
全ての絞り込みを解除
36 件のレコードが見つかりました。
Process optimization on kesterite-based ceramics for enhancing their thermoelectric performances assisted by active machine learning approach: A tool for metal-sulfide ceramics development
ジャーナル論文
著者
Cédric Bourgès
(author) (
この著者で検索
)
https://orcid.org/0000-0001-9056-0420
National Institute for Materials Science
Cédric Bourgès
;
Guillaume Lambard
(author) (
この著者で検索
)
https://orcid.org/0000-0003-0275-4079
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Guillaume Lambard
;
Naoki Sato
(author) (
この著者で検索
)
https://orcid.org/0000-0002-6429-0591
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Naoki Sato
;
Makoto Tachibana
(author) (
この著者で検索
)
https://orcid.org/0000-0002-5907-5563
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Makoto Tachibana
;
Satoshi Ishii
(author) (
この著者で検索
)
https://orcid.org/0000-0003-0731-8428
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Satoshi Ishii
;
Takao Mori
(author) (
この著者で検索
)
https://orcid.org/0000-0003-2682-1846
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Takao Mori
キーワード
Kesterite
,
Machine learning
,
Process
,
Thermoelectric
,
Ceramic
刊行年月日
2024-08-29
更新時刻
2024-09-20 16:30:30 +0900
自律材料探索による磁性材料開発
ジャーナル論文
著者
岩崎 悠真
(author) (
この著者で検索
)
https://orcid.org/0000-0002-7117-277X
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
岩崎 悠真
キーワード
Machine learning
,
Materials Informatics
刊行年月日
2025-06-10
更新時刻
2025-12-12 08:30:25 +0900
Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis
ジャーナル論文
著者
Ryo Tamura
(author) (
この著者で検索
)
https://orcid.org/0000-0002-0349-358X
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Ryo Tamura
;
Kenji Nagata
(author) (
この著者で検索
)
Kenji Nagata
;
Keitaro Sodeyama
(author) (
この著者で検索
)
Keitaro Sodeyama
;
Kensaku Nakamura
(author) (
この著者で検索
)
Kensaku Nakamura
;
Toshiki Tokuhira
(author) (
この著者で検索
)
Toshiki Tokuhira
;
Satoshi Shibata
(author) (
この著者で検索
)
Satoshi Shibata
;
Kazuki Hammura
(author) (
この著者で検索
)
Kazuki Hammura
;
Hiroki Sugisawa
(author) (
この著者で検索
)
Hiroki Sugisawa
;
Masaya Kawamura
(author) (
この著者で検索
)
Masaya Kawamura
;
Teruki Tsurimoto
(author) (
この著者で検索
)
Teruki Tsurimoto
;
Masanobu Naito
(author) (
この著者で検索
)
Masanobu Naito
;
Masahiko Demura
(author) (
この著者で検索
)
https://orcid.org/0000-0002-7308-3041
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Masahiko Demura
;
Takashi Nakanishi
(author) (
この著者で検索
)
https://orcid.org/0000-0002-8744-782X
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Takashi Nakanishi
キーワード
Polypropylene
,
X-ray diffraction
,
Bayesian spectral deconvolution
,
Ising machine
,
Machine learning
刊行年月日
2024-12-31
更新時刻
2024-08-30 16:31:01 +0900
Advances in Carbon Nanotubes: Synthesis, Properties, and Cutting-Edge Applications
ジャーナル論文
著者
Guohai Chen
(author) (
この著者で検索
)
https://orcid.org/0000-0001-8481-0972
(unauthenticated)
Guohai Chen
;
Dai-Ming Tang
(author) (
この著者で検索
)
https://orcid.org/0000-0001-7136-7481
NIMS Researchers Directory SAMURAI
Dai-Ming Tang
キーワード
Carbon Nanotubes
,
Synthesis
,
Properties
,
Machine learning
刊行年月日
2025-10-20
更新時刻
2025-12-13 08:30:03 +0900
Machine Learning Approach for Evaluation of Nanodefects and Magnetic Anisotropy in FePt Granular Films
ジャーナル論文
著者
E. Dengina
(author) (
この著者で検索
)
National Institute for Materials Science
E. Dengina
;
A. Bolyachkin
(author) (
この著者で検索
)
https://orcid.org/0000-0003-0420-1806
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
A. Bolyachkin
;
H. Sepehri-Amin
(author) (
この著者で検索
)
https://orcid.org/0000-0002-7856-7897
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
H. Sepehri-Amin
;
K. Hono
(author) (
この著者で検索
)
https://orcid.org/0000-0001-7367-0193
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
K. Hono
キーワード
Magnetic recording
,
Micromagnetic simulations
,
Machine learning
,
FePt media
刊行年月日
2022-05-13
更新時刻
2024-10-15 16:30:13 +0900
Data-driven analysis of hydrogen embrittlement in martensitic steels with interpretable machine learning
ジャーナル論文
著者
Houichi Kitano
(author) (
この著者で検索
)
https://orcid.org/0000-0002-0778-574X
NIMS Researchers Directory SAMURAI
Houichi Kitano
;
Yuuji Kimura
(author) (
この著者で検索
)
https://orcid.org/0000-0002-8907-0704
NIMS Researchers Directory SAMURAI
Yuuji Kimura
;
Akinobu Shibata
(author) (
この著者で検索
)
https://orcid.org/0000-0001-8577-6411
NIMS Researchers Directory SAMURAI
Akinobu Shibata
キーワード
Hydrogen embrittlement
,
Martensitic steel
,
Machine learning
,
hap (shapley additive explanations)
,
Symbolic regression
刊行年月日
2026-04-23
更新時刻
2026-06-17 09:57:29 +0900
Estimation of valence state and growth rate using principal component analysis of plasma emission in reactive sputtering deposition
ジャーナル論文
著者
Rintaro Minami
(author) (
この著者で検索
)
University of Tsukuba a Department of Applied Physics
Rintaro Minami
;
Eiji Kita
(author) (
この著者で検索
)
Eiji Kita
;
Chiharu Mitsumata
(author) (
この著者で検索
)
Chiharu Mitsumata
;
Hideto Yanagihara
(author) (
この著者で検索
)
Hideto Yanagihara
キーワード
Machine learning
,
principal component analysis (PCA)
,
reactive magnetron sputtering
,
plasma emission spectrum
,
Mössbauer spectroscopy
刊行年月日
2025-12-31
更新時刻
2025-09-10 16:30:38 +0900
Machine Learning to Predict Multicellular Dynamics Driven by Concentrated Polymer Brush-Modified Cellulose Nanofibers
プレゼンテーション
著者
Chiaki Yoshikawa
(author) (
この著者で検索
)
https://orcid.org/0000-0002-6589-387X
National Institute for Materials Science Research Center for Macromolecules and Biomaterials/Macromolecules Field/Polymer Surfaces and Devices Team
NIMS Researchers Directory SAMURAI
Chiaki Yoshikawa
;
Hiroshi Mamitsuka
(author) (
この著者で検索
)
Hiroshi Mamitsuka
キーワード
Machine learning
,
Multicellular dynamics
,
Concentrated polymer brush
,
Cellulose nanofiber
刊行年月日
更新時刻
2025-11-06 12:30:42 +0900
Phase-separation induced dislocation-network cellular structures in Ti-Zr-Nb-Mo-Ta high-entropy alloy processed by laser powder bed fusion
ジャーナル論文
著者
Han Chen
(author) (
この著者で検索
)
Han Chen
;
Daisuke Egusa
(author) (
この著者で検索
)
Daisuke Egusa
;
Zehao Li
(author) (
この著者で検索
)
National Institute for Materials Science
Zehao Li
;
Taisuke Sasaki
(author) (
この著者で検索
)
https://orcid.org/0000-0002-5952-7638
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Taisuke Sasaki
;
Ryosuke Ozasa
(author) (
この著者で検索
)
Ryosuke Ozasa
;
Takuya Ishimoto
(author) (
この著者で検索
)
Takuya Ishimoto
;
Masayuki Okugawa
(author) (
この著者で検索
)
Masayuki Okugawa
;
Yuichiro Koizumi
(author) (
この著者で検索
)
Yuichiro Koizumi
;
Takayoshi Nakano
(author) (
この著者で検索
)
Takayoshi Nakano
;
Eiji Abe
(author) (
この著者で検索
)
Eiji Abe
キーワード
High-entropy alloy
,
Laser powder bed fusion
,
Cellular structure
,
Phase separation
,
Dislocation-network
,
Electron microscopy
,
Machine learning
刊行年月日
2025-03-12
更新時刻
2025-04-08 13:16:16 +0900
Active learning for predicting the enthalpy of mixing in binary liquids based on ab initio molecular dynamics
ジャーナル論文
著者
Quentin Bizot
(author) (
この著者で検索
)
https://orcid.org/0000-0002-4314-2266
(unauthenticated)
Quentin Bizot
;
Ryo Tamura
(author) (
この著者で検索
)
https://orcid.org/0000-0002-0349-358X
NIMS Researchers Directory SAMURAI
Ryo Tamura
;
Guillaume Deffrennes
(author) (
この著者で検索
)
https://orcid.org/0000-0002-3752-2537
(unauthenticated)
Guillaume Deffrennes
キーワード
CALPHAD
,
Machine learning
刊行年月日
2026-02-07
更新時刻
2026-04-01 13:44:57 +0900
キーワード
Machine learning
(36)
Autonomous
(4)
Anomalous Hall effect
(2)
Ceramic
(2)
Combinatorial
(2)
Crystal structure
(2)
Ising machine
(2)
Kesterite
(2)
Process
(2)
Thermoelectric
(2)
ab initio
(2)
AI-Driven Glass Design
(1)
Alloys
(1)
Automated synthesis
(1)
Bayesian optimization
(1)
Bayesian spectral deconvolution
(1)
Breath analysis
(1)
CALPHAD
(1)
Carbon Nanotubes
(1)
Cellular structure
(1)
Cellulose nanofiber
(1)
Concentrated polymer brush
(1)
Creep
(1)
Critical temperature
(1)
Crystal forms
(1)
Crystal phenomena
(1)
Curie temperature
(1)
Deep learning
(1)
Dislocation-network
(1)
Domain knowledge integration
(1)
ELNES
(1)
Electron microscopy
(1)
Electronic nose (e-nose)
(1)
Elements
(1)
Embolic agent
(1)
FePt
(1)
FePt media
(1)
Fragment descriptor
(1)
Gradient-based optimization
(1)
Half metal
(1)
Hard magnetic materials
(1)
Heat-assisted magnetic recording (HAMR)
(1)
High-entropy alloy
(1)
High-throughput
(1)
Hydrogel
(1)
Hydrogen embrittlement
(1)
Image segmentation
(1)
Laser powder bed fusion
(1)
Lung cancer
(1)
MSS
(1)
Magnetic recodring
(1)
Magnetic recording
(1)
Magnetocaloric materials
(1)
Martensitic steel
(1)
Materials
(1)
Materials Informatics
(1)
Materials design
(1)
Materials discovery
(1)
Membrane-type Surface stress Sensor (MSS)
(1)
Micromagnetic simulations
(1)
Multicellular dynamics
(1)
Mössbauer spectroscopy
(1)
Nd-Fe-B magnets
(1)
Olfactory sensor
(1)
Optimal experiment design
(1)
PDOS
(1)
Performance pridiction
(1)
Phase separation
(1)
Polypropylene
(1)
Properties
(1)
Proton configuration
(1)
Reactivity
(1)
Retention time prediction
(1)
SmFe12-based alloys
(1)
Structural Materials
(1)
Superconductor
(1)
Supercritical fluid chromatography
(1)
Symbolic regression
(1)
Synthesis
(1)
X-ray diffraction
(1)
XANES
(1)
ab-initio
(1)
active learning
(1)
adhesive
(1)
autonomous materials search
(1)
hap (shapley additive explanations)
(1)
plasma emission spectrum
(1)
principal component analysis (PCA)
(1)
reactive magnetron sputtering
(1)
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