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ジャーナル論文(26)
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Machine learning (32)
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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。
Autonomous search for materials with high Curie temperature using
ab initio
calculations and machine learning
ジャーナル論文
著者
Yuma Iwasaki
(author) (
この著者で検索
)
https://orcid.org/0000-0002-7117-277X
NIMS Researchers Directory SAMURAI
Yuma Iwasaki
キーワード
Machine learning
,
Autonomous
,
Curie temperature
,
ab initio
刊行年月日
2024-12-31
更新時刻
2024-10-04 08:30:28 +0900
Determination of Stable Proton Configurations by Black-Box Optimization Using an Ising Machine
ジャーナル論文
著者
Jianbo Lin
(author) (
この著者で検索
)
Jianbo Lin
;
Tomofumi Tada
(author) (
この著者で検索
)
https://orcid.org/0000-0003-3093-3779
(unauthenticated)
Tomofumi Tada
;
Ai Koizumi
(author) (
この著者で検索
)
Ai Koizumi
;
Masato Sumita
(author) (
この著者で検索
)
https://orcid.org/0000-0002-3506-1028
(unauthenticated)
Masato Sumita
;
Koji Tsuda
(author) (
この著者で検索
)
https://orcid.org/0000-0002-4288-1606
NIMS Researchers Directory SAMURAI
Koji Tsuda
;
Ryo Tamura
(author) (
この著者で検索
)
https://orcid.org/0000-0002-0349-358X
NIMS Researchers Directory SAMURAI
Ryo Tamura
キーワード
Machine learning
,
Ising machine
,
Proton configuration
刊行年月日
2025-02-06
更新時刻
2025-05-23 08:30:18 +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
In Situ Forming Supramolecular Nanofiber Hydrogel as a Biodegradable Liquid Embolic Agent for Postembolization Tissue Remodeling
ジャーナル論文
著者
Akihiro Nishiguchi
(author) (
この著者で検索
)
https://orcid.org/0000-0002-3160-6385
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Akihiro Nishiguchi
;
Miho Ohta
(author) (
この著者で検索
)
Miho Ohta
;
Debabrata Palai
(author) (
この著者で検索
)
https://orcid.org/0000-0003-1192-6143
National Institute for Materials Science
Debabrata Palai
;
Shima Ito
(author) (
この著者で検索
)
https://orcid.org/0000-0002-3233-617X
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Shima Ito
;
Kensaku Mori
(author) (
この著者で検索
)
Kensaku Mori
;
Ryotaro Akagi
(author) (
この著者で検索
)
Ryotaro Akagi
;
Christophe Bajan
(author) (
この著者で検索
)
https://orcid.org/0009-0008-1433-9618
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Christophe Bajan
;
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
;
Keitaro Sodeyama
(author) (
この著者で検索
)
https://orcid.org/0000-0002-9228-0729
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Keitaro Sodeyama
;
Tetsushi Taguchi
(author) (
この著者で検索
)
https://orcid.org/0000-0003-2541-2530
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Tetsushi Taguchi
キーワード
Hydrogel
,
Embolic agent
,
Machine learning
刊行年月日
2024-11-07
更新時刻
2025-02-26 16:30:29 +0900
Toward the Atomic-Level Analysis of Ground-State Electronic Structures of Solid Materials via Prediction from Core-Loss Spectra: A Computational Study in Si
ジャーナル論文
著者
Izumi Takahara
(author) (
この著者で検索
)
Izumi Takahara
;
Fumihiko Uesugi
(author) (
この著者で検索
)
https://orcid.org/0000-0003-3346-4218
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Fumihiko Uesugi
;
Koji Kimoto
(author) (
この著者で検索
)
https://orcid.org/0000-0002-3927-0492
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Koji Kimoto
;
Kiyou Shibata
(author) (
この著者で検索
)
Kiyou Shibata
;
Teruyasu Mizoguchi
(author) (
この著者で検索
)
Teruyasu Mizoguchi
キーワード
Machine learning
,
ELNES
,
XANES
,
PDOS
刊行年月日
2024-08-15
更新時刻
2024-10-02 12:30:19 +0900
Improving efficiency of autonomous material search via transfer learning from nontarget properties
ジャーナル論文
著者
Jaekyun Hwang
(author) (
この著者で検索
)
National Institute for Materials Science
Jaekyun Hwang
;
Yuma Iwasaki
(author) (
この著者で検索
)
https://orcid.org/0000-0002-7117-277X
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Yuma Iwasaki
キーワード
Machine learning
刊行年月日
2023-12-31
更新時刻
2024-01-05 22:11:31 +0900
Prediction and optimization of epoxy adhesive strength from a small dataset through active learning
ジャーナル論文
著者
Lambard, Guillaume
(author) (
この著者で検索
)
https://orcid.org/0000-0003-0275-4079
NIMS Researchers Directory SAMURAI
Lambard, Guillaume
;
Naito, Masanobu
(author) (
この著者で検索
)
https://orcid.org/0000-0001-7198-819X
NIMS Researchers Directory SAMURAI
Naito, Masanobu
;
Samitsu, Sadaki
(author) (
この著者で検索
)
https://orcid.org/0000-0002-4139-1656
NIMS Researchers Directory SAMURAI
Samitsu, Sadaki
;
Pruksawan, Sirawit
(author) (
この著者で検索
)
https://orcid.org/0000-0002-9380-1872
(unauthenticated)
Pruksawan, Sirawit
;
Sodeyama, Keitaro
(author) (
この著者で検索
)
https://orcid.org/0000-0002-9228-0729
NIMS Researchers Directory SAMURAI
Sodeyama, Keitaro
キーワード
active learning
,
Machine learning
,
adhesive
刊行年月日
2019-12-31
更新時刻
2024-01-05 22:11:50 +0900
Exploring new useful phosphors by combining experiments with machine learning
ジャーナル論文
著者
Takashi Takeda
(author) (
この著者で検索
)
https://orcid.org/0000-0003-2510-4562
NIMS Researchers Directory SAMURAI
Takashi Takeda
;
Yukinori Koyama
(author) (
この著者で検索
)
https://orcid.org/0000-0002-7090-4430
NIMS Researchers Directory SAMURAI
Yukinori Koyama
;
Hidekazu Ikeno
(author) (
この著者で検索
)
Hidekazu Ikeno
;
Satoru Matsuishi
(author) (
この著者で検索
)
https://orcid.org/0000-0001-8905-0255
NIMS Researchers Directory SAMURAI
Satoru Matsuishi
;
Naoto Hirosaki
(author) (
この著者で検索
)
https://orcid.org/0000-0001-9218-9557
NIMS Researchers Directory SAMURAI
Naoto Hirosaki
キーワード
Phosphor
,
High-throughput experiment
,
Machine learning
,
Local structure
,
Europium
刊行年月日
2024-12-31
更新時刻
2024-12-05 16:30:28 +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
High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning
ジャーナル論文
著者
Ryo Toyama
(author) (
この著者で検索
)
https://orcid.org/0000-0002-7398-5803
NIMS Researchers Directory SAMURAI
Ryo Toyama
;
Yuma Iwasaki
(author) (
この著者で検索
)
https://orcid.org/0000-0002-7117-277X
NIMS Researchers Directory SAMURAI
Yuma Iwasaki
;
Prabhanjan D. Kulkarni
(author) (
この著者で検索
)
https://orcid.org/0000-0002-4605-5256
Prabhanjan D. Kulkarni
;
Hirofumi Suto
(author) (
この著者で検索
)
https://orcid.org/0000-0003-4387-5862
NIMS Researchers Directory SAMURAI
Hirofumi Suto
;
Tomoya Nakatani
(author) (
この著者で検索
)
https://orcid.org/0000-0001-9590-216X
NIMS Researchers Directory SAMURAI
Tomoya Nakatani
;
Yuya Sakuraba
(author) (
この著者で検索
)
https://orcid.org/0000-0003-4618-9550
NIMS Researchers Directory SAMURAI
Yuya Sakuraba
キーワード
Machine learning
,
High-throughput
,
Combinatorial
,
Anomalous Hall effect
刊行年月日
2025-09-03
更新時刻
2025-12-26 13:11:05 +0900
キーワード
Machine learning
(32)
Autonomous
(3)
Anomalous Hall effect
(2)
Ceramic
(2)
Combinatorial
(2)
Ising machine
(2)
Kesterite
(2)
Process
(2)
Thermoelectric
(2)
ab initio
(2)
AI-Driven Glass Design
(1)
Automated synthesis
(1)
Bayesian optimization
(1)
Bayesian spectral deconvolution
(1)
Breath analysis
(1)
CALPHAD
(1)
Carbon Nanotubes
(1)
Creep
(1)
Critical temperature
(1)
Crystal structure
(1)
Curie temperature
(1)
Deep learning
(1)
Domain knowledge integration
(1)
ELNES
(1)
Electronic nose (e-nose)
(1)
Elements
(1)
Embolic agent
(1)
Europium
(1)
FePt
(1)
FePt media
(1)
Fragment descriptor
(1)
Gradient-based optimization
(1)
Half metal
(1)
Heat-assisted magnetic recording (HAMR)
(1)
High-throughput
(1)
High-throughput experiment
(1)
Hydrogel
(1)
Hydrogen embrittlement
(1)
Image segmentation
(1)
Local structure
(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)
Mössbauer spectroscopy
(1)
Nd-Fe-B magnets
(1)
Olfactory sensor
(1)
Optimal experiment design
(1)
PDOS
(1)
Performance pridiction
(1)
Phosphor
(1)
Polypropylene
(1)
Properties
(1)
Proton configuration
(1)
Reactivity
(1)
Retention time prediction
(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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