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Journal article(29)
Conference paper(1)
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machine learning (31)
phosphor (3)
tdm (3)
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Keyword: machine learning
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31 records found.
Estimating the S-N Curve by Machine Learning Random Forest Method
Journal article
Creator
Nobuo Nagashima
(author) (
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https://orcid.org/0000-0003-3588-980X
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Nobuo Nagashima
;
Masao Hayakawa
(author) (
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)
https://orcid.org/0000-0001-5143-8350
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Masao Hayakawa
;
Hiroyuki Masuda
(author) (
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)
https://orcid.org/0000-0003-2847-1616
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Hiroyuki Masuda
;
Kotobu Nagai
(author) (
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)
National Institute for Materials Science
Kotobu Nagai
Keyword
fatigue
,
high-cycle fatigue
,
data-sheet
,
machine learning
,
random forest method
Date published
2024-04-01
Updated at
2024-12-27 16:30:58 +0900
Unveiling the principle descriptor for predicting the electron inelastic mean free path based on a machine learning framework
Journal article
Creator
Xun Liu
(author) (
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)
National Institute for Materials Science
Xun Liu
;
Zhufeng Hou
(author) (
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)
Zhufeng Hou
;
Dabao Lu
(author) (
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)
Dabao Lu
;
Bo Da
(author) (
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)
https://orcid.org/0000-0002-0785-8662
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Bo Da
;
Hideki Yoshikawa
(author) (
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)
https://orcid.org/0000-0002-7389-8865
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Hideki Yoshikawa
;
Shigeo Tanuma
(author) (
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)
https://orcid.org/0000-0003-2628-9941
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Shigeo Tanuma
;
Yang Sun
(author) (
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)
Yang Sun
;
Zejun Ding
(author) (
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)
Zejun Ding
Keyword
machine learning
,
inelastic mean free path
,
LASSO
Date published
2019-12-31
Updated at
2024-09-05 16:30:30 +0900
Predicting the surface roughness of an electrodeposited copper film using a machine learning technique
Journal article
Creator
Ryo Tamura
(author) (
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)
https://orcid.org/0000-0002-0349-358X
Center for Basic Research on Materials/Data-driven Materials Research Field/Data-driven Algorithm Team, National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Ryo Tamura
;
Ryuichi Inaba
(author) (
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MITSUBISHI MATERIALS CORPORATION
Ryuichi Inaba
;
Mami Watanabe
(author) (
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)
MITSUBISHI MATERIALS CORPORATION
Mami Watanabe
;
Yutaro Mori
(author) (
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)
MITSUBISHI MATERIALS CORPORATION
Yutaro Mori
;
Makoto Urushihara
(author) (
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)
MITSUBISHI MATERIALS CORPORATION
Makoto Urushihara
;
Kenji Yamaguchi
(author) (
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)
MITSUBISHI MATERIALS CORPORATION
Kenji Yamaguchi
;
Shoichi Matsuda
(author) (
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)
https://orcid.org/0000-0002-0640-3404
Research Center for Energy and Environmental Materials (GREEN)/Battery and Cell Materials Field/Automated Electrochemical Experiments Team, National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Shoichi Matsuda
Keyword
electrodeposited copper film
,
surface roughness
,
machine learning
Date published
2024-12-31
Updated at
2024-10-31 16:30:15 +0900
Accelerating Materials Discovery of Novel Europium(II)-Activated Phosphors through Machine Learning Classification of Europium Valences
Journal article
Creator
Yukinori Koyama
(author) (
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)
https://orcid.org/0000-0002-7090-4430
NIMS Researchers Directory SAMURAI
Yukinori Koyama
;
Yukako Kohriki
(author) (
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)
https://orcid.org/0000-0002-6858-1273
NIMS Researchers Directory SAMURAI
Yukako Kohriki
;
Masamichi Harada
(author) (
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)
https://orcid.org/0000-0002-7321-0733
NIMS Researchers Directory SAMURAI
Masamichi Harada
;
Naoto Hirosaki
(author) (
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)
https://orcid.org/0000-0001-9218-9557
NIMS Researchers Directory SAMURAI
Naoto Hirosaki
;
Takashi Takeda
(author) (
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)
https://orcid.org/0000-0003-2510-4562
NIMS Researchers Directory SAMURAI
Takashi Takeda
Keyword
phosphor
,
machine learning
,
europium
,
oxidation state
Date published
2024-12-10
Updated at
2025-11-25 08:30:03 +0900
Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder Diffraction Patterns
Journal article
Creator
Hirotaka Uryu
(author) (
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Hirotaka Uryu
;
Tsunetomo Yamada
(author) (
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)
Tsunetomo Yamada
;
Koichi Kitahara
(author) (
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)
Koichi Kitahara
;
Alok Singh
(author) (
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)
https://orcid.org/0000-0001-5515-8305
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Alok Singh
;
Yutaka Iwasaki
(author) (
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)
https://orcid.org/0000-0002-7317-4939
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Yutaka Iwasaki
;
Kaoru Kimura
(author) (
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https://orcid.org/0000-0001-5050-4256
National Institute for Materials Science
Kaoru Kimura
;
Kanta Hiroki
(author) (
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)
Kanta Hiroki
;
Naoki Miyao
(author) (
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Naoki Miyao
;
Asuka Ishikawa
(author) (
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Asuka Ishikawa
;
Ryuji Tamura
(author) (
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)
Ryuji Tamura
;
Satoshi Ohhashi
(author) (
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)
Satoshi Ohhashi
;
Chang Liu
(author) (
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)
Chang Liu
;
Ryo Yoshida
(author) (
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)
Ryo Yoshida
Keyword
deep learning
,
x-ray powder diffraction
,
quasicrystal
,
phase identification
,
machine learning
Date published
2023-11-14
Updated at
2024-12-13 12:30:39 +0900
Computational discovery of stable Na-ion sulfide solid electrolytes with high conductivity at room temperature
Journal article
Creator
Seong-Hoon Jang
(author) (
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)
https://orcid.org/0000-0001-6026-636X
(unauthenticated)
Seong-Hoon Jang
;
Randy Jalem
(author) (
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)
https://orcid.org/0000-0001-9505-771X
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Randy Jalem
;
Yoshitaka Tateyama
(author) (
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https://orcid.org/0000-0002-5532-6134
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Yoshitaka Tateyama
Keyword
all solid state batteries
,
solid electrolytes
,
high-throughput first-principles calculation
,
computational materials search
,
machine learning
,
sodium ion conductors
Date published
2024-08-05
Updated at
2024-10-10 16:30:52 +0900
Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm
Journal article
Creator
Stephen Wu
(author) (
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Stephen Wu
;
Yukiko Kondo
(author) (
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)
Yukiko Kondo
;
Masa-aki Kakimoto
(author) (
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Masa-aki Kakimoto
;
Bin Yang
(author) (
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Bin Yang
;
Hironao Yamada
(author) (
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Hironao Yamada
;
Isao Kuwajima
(author) (
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https://orcid.org/0000-0002-5994-3834
NIMS Researchers Directory SAMURAI
Isao Kuwajima
;
Guillaume Lambard
(author) (
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)
https://orcid.org/0000-0003-0275-4079
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Guillaume Lambard
;
Kenta Hongo
(author) (
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Kenta Hongo
;
Yibin Xu
(author) (
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https://orcid.org/0000-0001-8600-8748
NIMS Researchers Directory SAMURAI
Yibin Xu
;
Junichiro Shiomi
(author) (
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Junichiro Shiomi
;
Christoph Schick
(author) (
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Christoph Schick
;
Junko Morikawa
(author) (
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Junko Morikawa
;
Ryo Yoshida
(author) (
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Ryo Yoshida
Keyword
machine learning
,
polymer
,
thermal conductivity
,
molecular design
Date published
2019-06-21
Updated at
2024-11-21 16:31:23 +0900
Multi-Objective Optimization of Adhesive Joint Strength and Elastic Modulus of Adhesive Epoxy with Active Learning
Journal article
Creator
Paripat Kraisornkachit
(author) (
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https://orcid.org/0000-0002-0796-3665
NIMS Researchers Directory SAMURAI
Paripat Kraisornkachit
;
Masanobu Naito
(author) (
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https://orcid.org/0000-0001-7198-819X
NIMS Researchers Directory SAMURAI
Masanobu Naito
;
Chao Kang
(author) (
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)
https://orcid.org/0000-0002-9567-0976
(unauthenticated)
Chao Kang
;
Chiaki Sato
(author) (
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)
Chiaki Sato
Keyword
experimental testing
,
multi-objective optimization
,
epoxy
,
adhesive
,
elastic modulus
,
machine learning
,
active learning
Date published
2024-06-12
Updated at
2025-01-07 08:30:26 +0900
Time-domain thermoreflectance technique using multiple delayed probe pulses for high-throughput data acquisition and analysis
Journal article
Creator
Hiroto Arima
(author) (
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National Metrology Institute of Japan (NMIJ), National Institute of Advanced Industrial Science and Technology (AIST)
Hiroto Arima
;
Yuichiro Yamashita
(author) (
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)
Yuichiro Yamashita
;
Takashi Yagi
(author) (
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)
Takashi Yagi
Keyword
Time-domain thermoreflectance
,
multiple delay
,
thin film
,
thermal effusivity
,
interfacial thermal resistance
,
machine learning
Date published
2025-12-31
Updated at
2025-07-16 16:14:58 +0900
Machine Learning as a “Catalyst” for Advancements in Carbon Nanotube Research
Journal article
Creator
Guohai Chen
(author) (
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)
https://orcid.org/0000-0001-8481-0972
(unauthenticated)
Guohai Chen
;
Dai-Ming Tang
(author) (
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)
https://orcid.org/0000-0001-7136-7481
NIMS Researchers Directory SAMURAI
Dai-Ming Tang
Keyword
machine learning
,
carbon nanotube
,
in situ TEM
,
growth mechanism
Date published
2024-10-22
Updated at
2024-12-24 13:58:23 +0900
Keyword
machine learning
(31)
phosphor
(3)
tdm
(3)
europium
(2)
inelastic mean free path
(2)
superconductors
(2)
thermal conductivity
(2)
Eu2+
(1)
FePt
(1)
Graph neural network
(1)
Interfacial thermal resistance
(1)
LASSO
(1)
PoLyInfo
(1)
Time-domain thermoreflectance
(1)
active learning
(1)
adhesive
(1)
all solid state batteries
(1)
artificial intelligence
(1)
biomass
(1)
carbon
(1)
carbon nanotube
(1)
cellulose nanofiber
(1)
combinatorial
(1)
composition-based feature
(1)
computational materials search
(1)
concentrated polymer brush
(1)
data-sheet
(1)
database
(1)
dataset
(1)
deep learning
(1)
density-functional theory
(1)
dielectrics
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dopant
(1)
elastic modulus
(1)
electrocatalysis
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(1)
electrochemical interfaces
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electrodeposited copper film
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electronegativity
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electronics
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emission spectrum
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energy
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epoxy
(1)
experimental testing
(1)
fatigue
(1)
first principles calculations
(1)
growth mechanism
(1)
hMSC
(1)
heat-assisted magnetic recording
(1)
high temperature oxidation
(1)
high throughput
(1)
high-cycle fatigue
(1)
high-temperature superconductivity
(1)
high-throughput first-principles calculation
(1)
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(1)
in situ TEM
(1)
interfacial thermal resistance
(1)
interpretability
(1)
linear model
(1)
liquid crystalline polymer
(1)
lithium metal battery
(1)
luminescence
(1)
luminescent materials
(1)
materials design
(1)
materials informatics
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materials science
(1)
materials science
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molecular design
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polymer
(1)
quantum materials
(1)
quasicrystal
(1)
random forest method
(1)
rare-earth doping
(1)
self-assembly
(1)
sodium ion conductors
(1)
solid electrolytes
(1)
storage
(1)
surface roughness
(1)
targeted drug delivery
(1)
thermal effusivity
(1)
thermal management
(1)
thin film
(1)
x-ray powder diffraction
(1)
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