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論文・データセット
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The history of DICE and NIMS Digital Library(1)
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ジャーナル論文(85)
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machine learning (12)
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88 件のレコードが見つかりました。
Design and fabrication of a low-cost 3D-printed pH sensor positioning robot for laboratory automation
ジャーナル論文
著者
Shinnosuke Yorozuya
(author) (
この著者で検索
)
Hokkaido University a Department of Chemistry
Shinnosuke Yorozuya
;
Mikael Kuwahara
(author) (
この著者で検索
)
Mikael Kuwahara
;
Koki Sakamoto
(author) (
この著者で検索
)
Koki Sakamoto
;
Keisuke Takahashi
(author) (
この著者で検索
)
Keisuke Takahashi
;
Lauren Takahashi
(author) (
この著者で検索
)
Lauren Takahashi
キーワード
Robotics
,
3D printed
,
open source
刊行年月日
2026-07-06
更新時刻
2026-07-08 17:01:28 +0900
Machine learning prediction of Young's modulus in multi component titanium based biomedical alloys using extended thermodynamic descriptors
ジャーナル論文
著者
Hassan Ahmad
(author) (
この著者で検索
)
Pakistan Institute of Engineering and Applied Sciences (PIEAS) Department of Metallurgy and Materials Engineering
Hassan Ahmad
;
Muhammad Haider
(author) (
この著者で検索
)
Muhammad Haider
;
Zafar Iqbal
(author) (
この著者で検索
)
Zafar Iqbal
;
Muhammad Zarif
(author) (
この著者で検索
)
Muhammad Zarif
;
Syed Mujtaba Ul Hassan
(author) (
この著者で検索
)
Syed Mujtaba Ul Hassan
キーワード
Titanium alloys
,
machine learning
,
biomedical alloys
,
Young’s modulus prediction
刊行年月日
2026-12-31
更新時刻
2026-07-08 16:58:38 +0900
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
Yukinori Koyama
(author) (
この著者で検索
)
https://orcid.org/0000-0002-7090-4430
NIMS Researchers Directory SAMURAI
Yukinori Koyama
;
Ryusei Hayasaka
(author) (
この著者で検索
)
Ryusei Hayasaka
;
Yuta Matsushima
(author) (
この著者で検索
)
https://orcid.org/0000-0001-5826-1551
(unauthenticated)
Yuta Matsushima
;
Takayuki Nakanishi
(author) (
この著者で検索
)
https://orcid.org/0000-0003-3412-2842
NIMS Researchers Directory SAMURAI
Takayuki Nakanishi
;
Takashi Takeda
(author) (
この著者で検索
)
https://orcid.org/0000-0003-2510-4562
NIMS Researchers Directory SAMURAI
Takashi Takeda
;
Naoto Hirosaki
(author) (
この著者で検索
)
Naoto Hirosaki
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
Orchestration of heterogeneous experimental machines via ROS2 for automated bulk intermetallic synthesis
ジャーナル論文
著者
Wei-Sheng Wang
(author) (
この著者で検索
)
National Institute for Materials Science
Wei-Sheng Wang
;
Kensei Terashima
(author) (
この著者で検索
)
https://orcid.org/0000-0003-0375-3043
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Kensei Terashima
;
Yoshihiko Takano
(author) (
この著者で検索
)
https://orcid.org/0000-0002-1541-6928
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Yoshihiko Takano
キーワード
Automated synthesis
,
Arc melting
,
Bulk intermetallic materials
,
Orchestration of robots
刊行年月日
2026-12-31
更新時刻
2026-07-07 13:37:42 +0900
AI agents for automating materials research: a case study of crystal plasticity simulations
ジャーナル論文
著者
Jiyi Yang
(author) (
この著者で検索
)
https://orcid.org/0009-0003-0213-1258
(unauthenticated)
National Institute for Materials Science
Jiyi Yang
;
Yoshinao Kobayashi
(author) (
この著者で検索
)
Yoshinao Kobayashi
;
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
キーワード
Multi-agent LLM
,
Crystal plasticity simulation
,
Automated simulation
刊行年月日
2026-12-31
更新時刻
2026-07-03 10:01:23 +0900
Development of an AI-based acoustic disturbance-detection method for robotic arc welding processes
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
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Houichi Kitano
;
Masaki Kobayashi
(author) (
この著者で検索
)
https://orcid.org/0000-0002-5161-2600
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Masaki Kobayashi
;
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
キーワード
Acoustic sensing
,
in-process monitoring
,
gas metal arc welding
,
disturbance detection
,
machine learning
,
explainable AI
,
smart manufacturing
刊行年月日
2026-12-31
更新時刻
2026-06-25 09:51:40 +0900
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
Masaki Imamura
;
Kazutoshi Takahashi
(author) (
この著者で検索
)
Kazutoshi Takahashi
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
Replica-exchange Bayesian mixture regression reveals cluster-dependent XRD descriptors of tensile modulus in recycled polypropylene
ジャーナル論文
著者
Kazuki Hammura
(author) (
この著者で検索
)
Kazuki Hammura
;
Kiyotaka Hitomi
(author) (
この著者で検索
)
https://orcid.org/0009-0005-0736-0214
(unauthenticated)
National Institute for Materials Science
Kiyotaka Hitomi
;
Kenji Nagata
(author) (
この著者で検索
)
https://orcid.org/0000-0001-9894-4461
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Kenji Nagata
;
Masanobu Naito
(author) (
この著者で検索
)
https://orcid.org/0000-0001-7198-819X
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Masanobu Naito
キーワード
Recycled polypropylene
,
X-ray diffraction
,
Bayesian mixture regression
,
Bayesian peak deconvolution
,
structure–property relationship
刊行年月日
2026-12-31
更新時刻
2026-05-18 08:49:04 +0900
Data-driven approach for rapid prediction of strength scatter in brittle ceramics using deep learning and swarm optimization
ジャーナル論文
著者
Taiyo Maeda
(author) (
この著者で検索
)
Graduate School of Yokohama National University
Taiyo Maeda
;
Muhammad Aiman bin Musa
(author) (
この著者で検索
)
Graduate School of Yokohama National University
Muhammad Aiman bin Musa
;
Toshio Osada
(author) (
この著者で検索
)
https://orcid.org/0000-0003-1539-9264
National Institute for Materials Science Research Center for Structural Materials/Materials Manufacturing Field/High-Reliability Heat-Resistant Materials Group
NIMS Researchers Directory SAMURAI
Toshio Osada
;
Shingo Ozaki
(author) (
この著者で検索
)
Faculty of Engineering, Yokohama National University
Shingo Ozaki
キーワード
Ceramics
,
Fracture statistics
,
Defect distribusion
,
Multilayer perceptron
,
Inverse analysis
刊行年月日
2026-12-31
更新時刻
2026-04-22 16:01:04 +0900
Comparison of FePt high-density magnetic recording media development between large language models and experimental experts: do LLMs recommend fluoride as a segregant?
ジャーナル論文
著者
Masashi Ishii
(author) (
この著者で検索
)
https://orcid.org/0000-0003-0357-2832
NIMS Researchers Directory SAMURAI
Masashi Ishii
;
Yasufumi Watanabe
(author) (
この著者で検索
)
Yasufumi Watanabe
;
Ippei Suzuki
(author) (
この著者で検索
)
https://orcid.org/0000-0002-8932-8226
(unauthenticated)
Ippei Suzuki
;
Yukiko K. Takahashi
(author) (
この著者で検索
)
https://orcid.org/0000-0001-9197-7236
NIMS Researchers Directory SAMURAI
Yukiko K. Takahashi
キーワード
large language model
,
exploratory generation
,
FePt nanogranular film
,
fluoride segregant
,
LaF3
,
AlF3
刊行年月日
2026-12-31
更新時刻
2026-04-21 13:35:17 +0900
キーワード
machine learning
(12)
Machine learning
(8)
Materials informatics
(5)
materials informatics
(5)
RDF
(4)
database
(4)
generative AI
(4)
Autonomous
(3)
PoLyInfo
(3)
data curation
(3)
ontology
(3)
CALPHAD
(2)
Elastic-plastic material
(2)
Hastelloy X
(2)
SEM
(2)
SPARQL
(2)
ShEx
(2)
SrTiO3
(2)
TDM
(2)
X-ray diffraction
(2)
ab initio
(2)
additive manufacturing
(2)
data model
(2)
density functional theory
(2)
finite element method
(2)
gigacycle fatigue
(2)
instrumented indentation test
(2)
large language model
(2)
material database
(2)
response surface
(2)
schema
(2)
stress-induced ferroelectricity
(2)
structural materials
(2)
superconductors
(2)
database
(1)
machine learning
(1)
microstructures
(1)
persistent homology
(1)
100,000h
(1)
100,000h creep rupture strength
(1)
3D convolutional autoencoder
(1)
3D printed
(1)
AI
(1)
AI for materials engineering
(1)
AI for science
(1)
AI-ready
(1)
Acoustic sensing
(1)
Additive manufacturing
(1)
Advanced high-strength steel
(1)
Al-Nb-Ni
(1)
AlF3
(1)
Alloy design
(1)
Alloy development
(1)
Arc melting
(1)
Automated simulation
(1)
Automated synthesis
(1)
Bayesian estimation
(1)
Bayesian inference
(1)
Bayesian mixture regression
(1)
Bayesian optimization
(1)
Bayesian peak deconvolution
(1)
Bi0.46Sb1.54Te3
(1)
Bi2Te2.7Se0.3
(1)
BiTe system
(1)
Bound states in thecontinuum (BICs)
(1)
Bulk intermetallic materials
(1)
CCT
(1)
CFRP
(1)
Carbon steel
(1)
Causal inference
(1)
Cellular solids
(1)
Ceramics
(1)
Co-Fe system
(1)
Copper alloys
(1)
Creep rupture
(1)
Creep rupture strength
(1)
Creep strength enhanced ferritic steel
(1)
Crystal plasticity simulation
(1)
Curie temperature
(1)
DAG
(1)
DOI
(1)
Data-Driven
(1)
Data-driven science
(1)
Defect distribusion
(1)
Delaunay polyhedra
(1)
Density functional theory (DFT)
(1)
Electrical resistivity / conductivity
(1)
Exhaustive search
(1)
Expectation– conditional maximisation algorithm
(1)
Fatigue
(1)
Fatigue; structural materials; low- and high-cycle fatigue; boron steel; data sheet
(1)
FePt nanogranular film
(1)
Feature selection
(1)
Fracture statistics
(1)
GPU computing
(1)
Gibbs energy
(1)
Grade 91
(1)
Graph neural network
(1)
Growth-arrested state
(1)
Half metal
(1)
High spatial resolution
(1)
High-Q
(1)
High-throughput analysis
(1)
Indium oxide
(1)
Inherent creep strength
(1)
Inverse analysis
(1)
Jarzynski equality
(1)
LAQA
(1)
LLM
(1)
LSTM
(1)
LaF3
(1)
Label-free classification
(1)
LangGraph
(1)
Large language models
(1)
Larson–miller parameter
(1)
MEMS
(1)
Magnetism
(1)
Material informatics
(1)
Material process
(1)
Materials Genome Initiative
(1)
Materials data analysis
(1)
Materials databases
(1)
Maximum a posteriori estimation
(1)
Mechanical properties
(1)
Microstructure
(1)
Minimum creep rate
(1)
Model selection
(1)
Multi-agent LLM
(1)
Multi-objective topology optimization
(1)
Multichannel spin detection
(1)
Multicomponent
(1)
Multilayer perceptron
(1)
Mössbauer spectroscopy
(1)
NER
(1)
NIMO
(1)
NIMS-OS
(1)
NLP
(1)
Nanomembrane
(1)
Neural network
(1)
Neuroscience
(1)
Nickel-based superalloy
(1)
Optimization
(1)
Orchestration of robots
(1)
Peak fitting
(1)
Phase-field method
(1)
Phase-field modeling
(1)
Photoemission spectroscopy
(1)
Photonic–plasmonic hybrid BICs
(1)
Plasmonic
(1)
Polymer chemistry
(1)
Protein design
(1)
Quantitative phase microscopy
(1)
RDE
(1)
Recycled polypropylene
(1)
Reference composition
(1)
Region splitting analysis
(1)
Research Data Express
(1)
Robotics
(1)
SQS
(1)
Self-driving laboratories
(1)
SmFe12
(1)
Soft X-ray microscope
(1)
Solar cells
(1)
Solid electrolyte
(1)
Space group
(1)
Spectral decomposition
(1)
Spin-polarized electronic state
(1)
Spin-resolved photoemission microscopy
(1)
Strain evaluation method;
(1)
SuperCon
(1)
T-Learner
(1)
TDA
(1)
Thermoelectric
(1)
Time-temperature parameter
(1)
Titanium alloys
(1)
Ultrathin metasurface
(1)
X-ray CT
(1)
X-ray absorption fine structure
(1)
X-ray photoelectron spectroscopy
(1)
Young’s modulus prediction
(1)
ab-initio
(1)
active learning
(1)
air bridge
(1)
aluminium alloy
(1)
artificial intelligence
(1)
atomic descriptors
(1)
automated analysis
(1)
automated data extraction
(1)
automated knowledge extraction
(1)
autonomous materials search
(1)
band gap prediction
(1)
bayesian inference
(1)
bayesian optimisation
(1)
benchmark
(1)
biomedical alloys
(1)
birefringence image
(1)
blackbox optimization
(1)
bond angle
(1)
cBN sintered compacts
(1)
cantilever
(1)
RDEメタデータ定義
RDE送り状
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