Machine Learning to Predict Multicellular Dynamics Driven by Concentrated Polymer Brush-Modified Cellulose Nanofibers
- プレゼンテーション
- 著者
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Chiaki Yoshikawa (author) (この著者で検索)National Institute for Materials Science Research Center for Macromolecules and Biomaterials/Macromolecules Field/Polymer Surfaces and Devices Team
;
Hiroshi Mamitsuka (author) (この著者で検索) - キーワード
- Machine learning, Multicellular dynamics, Concentrated polymer brush, Cellulose nanofiber
- 刊行年月日
- 更新時刻
- 2025-11-06 12:30:42 +0900
Active learning for predicting the enthalpy of mixing in binary liquids based on ab initio molecular dynamics
- ジャーナル論文
- 著者
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Quentin Bizot (author) (この著者で検索)
https://orcid.org/0000-0002-4314-2266
(unauthenticated)
;
Ryo Tamura (author) (この著者で検索)
;
Guillaume Deffrennes (author) (この著者で検索)
https://orcid.org/0000-0002-3752-2537
(unauthenticated)
- キーワード
- CALPHAD, Machine learning
- 刊行年月日
- 2026-02-07
- 更新時刻
- 2026-04-01 13:44:57 +0900
Machine Learning Approach for Evaluation of Nanodefects and Magnetic Anisotropy in FePt Granular Films
- ジャーナル論文
- 著者
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;E. Dengina (author) (この著者で検索)National Institute for Materials ScienceA. Bolyachkin (author) (この著者で検索)National Institute for Materials Science
;
H. Sepehri-Amin (author) (この著者で検索)National Institute for Materials Science
;
K. Hono (author) (この著者で検索)National Institute for Materials Science
- キーワード
- Magnetic recording, Micromagnetic simulations, Machine learning, FePt media
- 刊行年月日
- 2022-05-13
- 更新時刻
- 2024-10-15 16:30:13 +0900
Efficient autonomous material search method combining ab initio calculations, autoencoder, and multi-objective Bayesian optimization
- ジャーナル論文
- 著者
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Yuma Iwasaki (author) (この著者で検索)
;
Hwang Jaekyun (author) (この著者で検索)
https://orcid.org/0000-0002-1792-0044
(unauthenticated)
;
Yuya Sakuraba (author) (この著者で検索)
;
Masato Kotsugi (author) (この著者で検索)
https://orcid.org/0000-0002-4841-1808
(unauthenticated)
;
Yasuhiko Igarashi (author) (この著者で検索)
https://orcid.org/0000-0003-1042-6657
(unauthenticated)
- キーワード
- autonomous materials search, ab-initio, Machine learning
- 刊行年月日
- 2022-12-31
- 更新時刻
- 2024-01-05 22:14:05 +0900
Improving efficiency of autonomous material search via transfer learning from nontarget properties
- ジャーナル論文
- 著者
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;Jaekyun Hwang (author) (この著者で検索)National Institute for Materials ScienceYuma Iwasaki (author) (この著者で検索)National Institute for Materials Science
- 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
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
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Akihiro Nishiguchi (author) (この著者で検索)National Institute for Materials Science
;
;Miho Ohta (author) (この著者で検索)Debabrata Palai (author) (この著者で検索)National Institute for Materials Science
;
Shima Ito (author) (この著者で検索)National Institute for Materials Science
;
;Kensaku Mori (author) (この著者で検索);Ryotaro Akagi (author) (この著者で検索)Christophe Bajan (author) (この著者で検索)National Institute for Materials Science
;
Guillaume Lambard (author) (この著者で検索)National Institute for Materials Science
;
Keitaro Sodeyama (author) (この著者で検索)National Institute for Materials Science
;
Tetsushi Taguchi (author) (この著者で検索)National Institute for Materials Science
- 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
Data-driven optimization of FePt heat-assisted magnetic recording media accelerated by deep learning TEM image segmentation
- ジャーナル論文
- 著者
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N. Kulesh (author) (この著者で検索)National Institute for Materials Science
;
A. Bolyachkin (author) (この著者で検索)National Institute for Materials Science
;
I. Suzuki (author) (この著者で検索)
https://orcid.org/0000-0002-8932-8226
(unauthenticated)
National Institute for Materials Science
;
Y.K. Takahashi (author) (この著者で検索)National Institute for Materials Science
;
H. Sepehri-Amin (author) (この著者で検索)National Institute for Materials Science
;
K. Hono (author) (この著者で検索)National Institute for Materials Science
- キーワード
- Heat-assisted magnetic recording (HAMR), FePt, Deep learning, Machine learning, Image segmentation
- 刊行年月日
- 2023-05-27
- 更新時刻
- 2025-05-27 08:30:20 +0900