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
Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis
- ジャーナル論文
- 著者
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Ryo Tamura (author) (この著者で検索)National Institute for Materials Science
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;Kenji Nagata (author) (この著者で検索);Keitaro Sodeyama (author) (この著者で検索);Kensaku Nakamura (author) (この著者で検索);Toshiki Tokuhira (author) (この著者で検索);Satoshi Shibata (author) (この著者で検索);Kazuki Hammura (author) (この著者で検索);Hiroki Sugisawa (author) (この著者で検索);Masaya Kawamura (author) (この著者で検索);Teruki Tsurimoto (author) (この著者で検索);Masanobu Naito (author) (この著者で検索)Masahiko Demura (author) (この著者で検索)National Institute for Materials Science
;
Takashi Nakanishi (author) (この著者で検索)National Institute for Materials Science
- キーワード
- Polypropylene, X-ray diffraction, Bayesian spectral deconvolution, Ising machine, Machine learning
- 刊行年月日
- 2024-12-31
- 更新時刻
- 2024-08-30 16:31:01 +0900
Statistical evaluation of phase fractions in a MoSiBTiC alloy by machine-learning-assisted segmentation of scanning electron microscopy images
- ジャーナル論文
- 著者
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;Chihana Kudo (author) (この著者で検索)Masahiko Demura (author) (この著者で検索)National Institute for Materials Science
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Akihiro Endo (author) (この著者で検索)National Institute for Materials Science
;
Kenji Nagata (author) (この著者で検索)National Institute for Materials Science
;
Kyosuke Yoshimi (author) (この著者で検索) - キーワード
- MoSiBTiC alloy, Scanning electron microscopy, Image segmentation, Machine learning, Bootstrap resampling, Fracture toughness
- 刊行年月日
- 2026-07-30
- 更新時刻
- 2026-09-16 10:47:16 +0900
Machine learning assisted nanobeam X-ray diffraction based analysis on hydride vapor-phase epitaxy GaN
- ジャーナル論文
- 著者
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;Zhendong Wu (author) (この著者で検索)Yusuke Hayashi (author) (この著者で検索)National Institute for Materials Science
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;Tetsuya Tohei (author) (この著者で検索);Kazushi Sumitani (author) (この著者で検索);Yasuhiko Imai (author) (この著者で検索);Shigeru Kimura (author) (この著者で検索)Akira Sakai (author) (この著者で検索)
- キーワード
- GaN, SPring-8, nanoXRD, Machine learning
- 刊行年月日
- 2025-08-01
- 更新時刻
- 2025-07-31 12:30:18 +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
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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
Data-driven analysis of hydrogen embrittlement in martensitic steels with interpretable machine learning
- ジャーナル論文
- 著者
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Houichi Kitano (author) (この著者で検索)
;
Yuuji Kimura (author) (この著者で検索)
;
Akinobu Shibata (author) (この著者で検索)
- キーワード
- Hydrogen embrittlement, Martensitic steel, Machine learning, hap (shapley additive explanations), Symbolic regression
- 刊行年月日
- 2026-04-23
- 更新時刻
- 2026-06-17 09:57:29 +0900