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- In Copyright (16)
- Creative Commons BY-NC Attribution-NonCommercial 4.0 International (3)
- Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International (1)
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44 records found.
Supercon 2 Dataset
- Dataset
- Creator
-
Foppiano, Luca (author) (Search by this author)
- Keyword
- superconductors, machine learning, dataset, tdm, materials science
- Date published
- 2022-09-10
- Updated at
- 2022-10-18 10:11:01 +0900
Rapid discovery of new Eu2+-activated phosphors with a designed luminescence color using a data-driven approach
- Journal article
- Creator
-
Yukinori Koyama (author) (Search by this author)Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science
;
;Hidekazu Ikeno (author) (Search by this author)Osaka Metropolitan University;Masamichi Harada (author) (Search by this author)Research Center for Functional Materials, National Institute for Materials Science;Shiro Funahashi (author) (Search by this author)Research Center for Functional Materials, National Institute for Materials ScienceTakashi Takeda (author) (Search by this author)Research Center for Functional Materials, National Institute for Materials Science
;
Naoto Hirosaki (author) (Search by this author)Research Center for Functional Materials, National Institute for Materials Science - Keyword
- phosphor, materials design, machine learning, luminescence, emission spectrum, Eu2+
- Date published
- 2022-11-29
- Updated at
- 2024-01-05 22:11:23 +0900
Development of an AI-based acoustic disturbance-detection method for robotic arc welding processes
- Journal article
- Creator
-
Houichi Kitano (author) (Search by this author)National Institute for Materials Science
;
Masaki Kobayashi (author) (Search by this author)National Institute for Materials Science
;
Masahiko Demura (author) (Search by this author)National Institute for Materials Science
- Keyword
- Acoustic sensing, in-process monitoring, gas metal arc welding, disturbance detection, machine learning, explainable AI, smart manufacturing
- Date published
- 2026-12-31
- Updated at
- 2026-06-25 09:51:40 +0900
Acquiring and transferring comprehensive catalyst knowledge through integrated high-throughput experimentation and automatic feature engineering
- Journal article
- Creator
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;Ayu Fujiwara (author) (Search by this author)Graduate School of Advanced Science and Technology, Japan Advanced Institute of Science and Technology;Sunao Nakanowatari (author) (Search by this author)Graduate School of Advanced Science and Technology, Japan Advanced Institute of Science and Technology;Yohei Cho (author) (Search by this author)Graduate School of Advanced Science and Technology, Japan Advanced Institute of Science and TechnologyToshiaki Taniike (author) (Search by this author)Graduate School of Advanced Science and Technology, Japan Advanced Institute of Science and Technology
- Keyword
- Catalyst informatics, machine learning, high-throughput experimentation, descriptor, oxidative coupling of methane
- Date published
- 2025-12-31
- Updated at
- 2025-07-16 16:17:04 +0900
Essential structural and experimental descriptors for bulk and grain boundary conductivities of Li solid electrolytes
- Journal article
- Creator
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Yen-Ju Wu (author) (Search by this author)National Institute for Materials Science
;
;Takehiro Tanaka (author) (Search by this author);Tomoyuki Komori (author) (Search by this author);Mikiya Fujii (author) (Search by this author);Hiroshi Mizuno (author) (Search by this author)Satoshi Itoh (author) (Search by this author)
https://orcid.org/0000-0002-8139-582X
(unauthenticated)
National Institute for Materials Science
;
;Tadanobu Takada (author) (Search by this author)Erina Fujita (author) (Search by this author)National Institute for Materials Science
;
Yibin Xu (author) (Search by this author)National Institute for Materials Science
- Keyword
- Ionic conductivity, machine learning, grain boundary, ionic conductor, Li battery, grain size, descriptor
- Date published
- 2020-01-31
- Updated at
- 2024-01-05 22:11:22 +0900
Estimating the S-N Curve by Machine Learning Random Forest Method
- Journal article
- Creator
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Nobuo Nagashima (author) (Search by this author)National Institute for Materials Science
;
Masao Hayakawa (author) (Search by this author)National Institute for Materials Science
;
Hiroyuki Masuda (author) (Search by this author)National Institute for Materials Science
;
Kotobu Nagai (author) (Search by this author)National Institute for Materials Science
- 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
Automatic Extraction of Materials and Properties from Superconductors Scientific Literature
- Journal article
- Creator
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Foppiano Luca (author) (Search by this author)MaDIS, NIMS
;
Baptista de Castro, Pedro (author) (Search by this author)
https://orcid.org/0000-0001-8673-2840
(unauthenticated)
MANA, NIMS
;
Ortiz Suarez, Pedro (author) (Search by this author)
https://orcid.org/0000-0003-0343-8852
(unauthenticated)
Data and Web Science Group, University of Mannheim
;
Terashima, Kensei (author) (Search by this author)
;
Takano, Yoshihiko (author) (Search by this author)
;
Ishii, Masashi (author) (Search by this author)
https://orcid.org/0000-0002-7721-9735
(unauthenticated)
MaDIS, NIMS
- Keyword
- tdm, machine learning, materials science, superconductors, database
- Date published
- 2022-09-15
- Updated at
- 2022-10-16 01:44:51 +0900
Multi-Objective Optimization of Adhesive Joint Strength and Elastic Modulus of Adhesive Epoxy with Active Learning
- Journal article
- Creator
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Paripat Kraisornkachit (author) (Search by this author)
;
Masanobu Naito (author) (Search by this author)
;
Chao Kang (author) (Search by this author)
https://orcid.org/0000-0002-9567-0976
(unauthenticated)
;
Chiaki Sato (author) (Search by this author)
- 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
Multiobjective Solid Electrolyte Design of Tetragonal and Cubic Inverse-Perovskites for All-Solid-State Lithium-Ion Batteries by High-Throughput Density Functional Theory Calculations and AI-Driven Methods
- Journal article
- Creator
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JALEM Randy (author) (Search by this author)Research Center for Energy and Environmental Materials (GREEN)/Battery and Cell Materials Field/Interface Electrochemistry Group, National Institute for Materials Science
;
TATEYAMA Yoshitaka (author) (Search by this author)Research Center for Energy and Environmental Materials (GREEN)/Battery and Cell Materials Field/Interface Electrochemistry Group, National Institute for Materials Science
;
TAKADA Kazunori (author) (Search by this author)Research Center for Energy and Environmental Materials (GREEN)/Battery and Cell Materials Field/Solid-State Battery Group, National Institute for Materials Science
;
JANG Seonghoon (author) (Search by this author)Research Center for Energy and Environmental Materials (GREEN)/Battery and Cell Materials Field/Interface Electrochemistry Group, National Institute for Materials Science
- Keyword
- all solid state batteries, solid electrolytes, density functional theory, materials informatics, machine learning, novel materials search
- Date published
- 2023-09-07
- Updated at
- 2024-08-28 08:30:15 +0900
Automatic Identification and Normalisation of Physical Measurements in Scientific Literature
- Journal article
- Creator
-
FOPPIANO, Luca (author) (Search by this author)
;
ROMARY, Laurent (author) (Search by this author)
https://orcid.org/0000-0002-0756-0508
(unauthenticated)
;
ISHII, Masashi (author) (Search by this author)
;
TANIFUJI, Mikiko (author) (Search by this author)
- Keyword
- tdm, physical quantities, machine learning
- Date published
- 2019-09-23
- Updated at
- 2022-10-03 02:00:14 +0900