MDR: NIMS Materials Data Repository

Keyword: Machine learning

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38 records found.

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In Situ Forming Supramolecular Nanofiber Hydrogel as a Biodegradable Liquid Embolic Agent for Postembolization Tissue Remodeling

Journal article
Creator: Akihiro Nishiguchi (author) (Search by this author)

https://orcid.org/0000-0002-3160-6385

National Institute for Materials Science

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Miho Ohta (author) (Search by this author)

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Debabrata Palai (author) (Search by this author)

https://orcid.org/0000-0003-1192-6143

National Institute for Materials Science

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Shima Ito (author) (Search by this author)

https://orcid.org/0000-0002-3233-617X

National Institute for Materials Science

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Kensaku Mori (author) (Search by this author)

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Ryotaro Akagi (author) (Search by this author)

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Christophe Bajan (author) (Search by this author)

https://orcid.org/0009-0008-1433-9618

National Institute for Materials Science

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Guillaume Lambard (author) (Search by this author)

https://orcid.org/0000-0003-0275-4079

National Institute for Materials Science

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Keitaro Sodeyama (author) (Search by this author)

https://orcid.org/0000-0002-9228-0729

National Institute for Materials Science

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Tetsushi Taguchi (author) (Search by this author)

https://orcid.org/0000-0003-2541-2530

National Institute for Materials Science

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Keyword: Hydrogel, Embolic agent, Machine learning
Date published: 2024-11-07
Updated at: 2025-02-26 16:30:29 +0900

Estimation of valence state and growth rate using principal component analysis of plasma emission in reactive sputtering deposition

Journal article
Creator: Rintaro Minami (author) (Search by this author)

a Department of Applied Physics, University of Tsukuba

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Eiji Kita (author) (Search by this author)

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Chiharu Mitsumata (author) (Search by this author)

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Hideto Yanagihara (author) (Search by this author)
Keyword: Machine learning, principal component analysis (PCA), reactive magnetron sputtering, plasma emission spectrum, Mössbauer spectroscopy
Date published: 2025-12-31
Updated at: 2025-09-10 16:30:38 +0900

Data-driven optimization of FePt heat-assisted magnetic recording media accelerated by deep learning TEM image segmentation

Journal article
Creator: N. Kulesh (author) (Search by this author)

https://orcid.org/0000-0001-7046-2671

National Institute for Materials Science

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A. Bolyachkin (author) (Search by this author)

https://orcid.org/0000-0003-0420-1806

National Institute for Materials Science

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I. Suzuki (author) (Search by this author)

https://orcid.org/0000-0002-8932-8226 (unauthenticated)

National Institute for Materials Science

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Y.K. Takahashi (author) (Search by this author)

https://orcid.org/0000-0001-9197-7236

National Institute for Materials Science

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H. Sepehri-Amin (author) (Search by this author)

https://orcid.org/0000-0002-7856-7897

National Institute for Materials Science

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K. Hono (author) (Search by this author)

https://orcid.org/0000-0001-7367-0193

National Institute for Materials Science

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Keyword: Heat-assisted magnetic recording (HAMR), FePt, Deep learning, Machine learning, Image segmentation
Date published: 2023-05-27
Updated at: 2025-05-27 08:30:20 +0900

A straightforward gradient-based approach for designing superconductors with high critical temperature: exploiting domain knowledge via adaptive constraints

Journal article
Creator: Akihiro Fujii (author) (Search by this author)

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Anh Khoa Augustin Lu (author) (Search by this author)

https://orcid.org/0000-0003-4702-0933

National Institute for Materials Science

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Koji Shimizu (author) (Search by this author)

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Satoshi Watanabe (author) (Search by this author)

https://orcid.org/0000-0002-8069-6938 (unauthenticated)

National Institute for Materials Science
Keyword: Gradient-based optimization, Superconductor, Domain knowledge integration, Materials discovery, Critical temperature, Machine learning
Date published: 2025-10-29
Updated at: 2026-05-18 14:53:14 +0900

Automated odor-blending with one-pot Bayesian optimization

Journal article
Creator: Yota Fukui (author) (Search by this author)

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Kosuke Minami (author) (Search by this author)

https://orcid.org/0000-0003-4145-1118

National Institute for Materials Science

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Kota Shiba (author) (Search by this author)

https://orcid.org/0000-0001-7775-0318

National Institute for Materials Science

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Genki Yoshikawa (author) (Search by this author)

https://orcid.org/0000-0002-9136-8964

National Institute for Materials Science

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Koji Tsuda (author) (Search by this author)

https://orcid.org/0000-0002-4288-1606

National Institute for Materials Science

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Ryo Tamura (author) (Search by this author)

https://orcid.org/0000-0002-0349-358X

National Institute for Materials Science

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Keyword: Machine learning, MSS, Bayesian optimization, Olfactory sensor
Date published: 2024-04-16
Updated at: 2024-06-10 12:30:19 +0900

Data-driven analysis of hydrogen embrittlement in martensitic steels with interpretable machine learning

Journal article
Creator: Houichi Kitano (author) (Search by this author)

https://orcid.org/0000-0002-0778-574X

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Yuuji Kimura (author) (Search by this author)

https://orcid.org/0000-0002-8907-0704

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Akinobu Shibata (author) (Search by this author)

https://orcid.org/0000-0001-8577-6411

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Keyword: Hydrogen embrittlement, Martensitic steel, Machine learning, hap (shapley additive explanations), Symbolic regression
Date published: 2026-04-23
Updated at: 2026-06-17 09:57:29 +0900

High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning

Journal article
Creator: Ryo Toyama (author) (Search by this author)

https://orcid.org/0000-0002-7398-5803

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Yuma Iwasaki (author) (Search by this author)

https://orcid.org/0000-0002-7117-277X

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Prabhanjan D. Kulkarni (author) (Search by this author)

https://orcid.org/0000-0002-4605-5256

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Hirofumi Suto (author) (Search by this author)

https://orcid.org/0000-0003-4387-5862

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Tomoya Nakatani (author) (Search by this author)

https://orcid.org/0000-0001-9590-216X

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Yuya Sakuraba (author) (Search by this author)

https://orcid.org/0000-0003-4618-9550

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Keyword: Machine learning, High-throughput, Combinatorial, Anomalous Hall effect
Date published: 2025-09-03
Updated at: 2025-12-26 13:11:05 +0900

Machine Learning to Predict Multicellular Dynamics Driven by Concentrated Polymer Brush-Modified Cellulose Nanofibers

Conference presentation
Creator: Chiaki Yoshikawa (author) (Search by this author)

https://orcid.org/0000-0002-6589-387X

Research Center for Macromolecules and Biomaterials/Macromolecules Field/Polymer Surfaces and Devices Team, National Institute for Materials Science

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Hiroshi Mamitsuka (author) (Search by this author)
Keyword: Machine learning, Multicellular dynamics, Concentrated polymer brush, Cellulose nanofiber
Date published
Updated at: 2025-11-06 12:30:42 +0900