キーワード: machine learning

43 件のレコードが見つかりました。

AdvMater.25_37_e10239.pdf
Artificial Intelligence‐Driven Nanoarchitectonics for Smart Targeted Drug Delivery
ジャーナル論文
著者
Hayeon Bae (author) (この著者で検索)
;
Hyunsub Ji (author) (この著者で検索)
;
Konstantin Konstantinov (author) (この著者で検索)
;
Ronald Sluyter (author) (この著者で検索)
;
Katsuhiko Ariga (author) (この著者で検索)
ORCID SAMURAI ;
Yong Ho Kim (author) (この著者で検索)
;
Jung Ho Kim (author) (この著者で検索)
キーワード
artificial intelligence, in silico optimization, machine learning, nanocarrier design, nanomedicine, targeted drug delivery
刊行年月日
2025-08-07
更新時刻
2025-10-28 12:30:13 +0900

Supplementary information.pdf
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
;
Muhammad Haider (author) (この著者で検索)
;
Zafar Iqbal (author) (この著者で検索)
;
Muhammad Zarif (author) (この著者で検索)
;
Syed Mujtaba Ul Hassan (author) (この著者で検索)
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

Abstract_YenJu Wu.docx
Designing Thermal Insulating thin films with Data-Driven Innovation
プレゼンテーション
著者
Yen-Ju Wu (author) (この著者で検索)
National Institute for Materials Science Center for Basic Research on Materials/Data-driven Materials Research Field/Data-driven Inorganic Materials Group
ORCID SAMURAI ;
Yibin Xu (author) (この著者で検索)
National Institute for Materials Science Center for Basic Research on Materials/Data-driven Materials Research Field/Data-driven Inorganic Materials Group
ORCID SAMURAI
キーワード
Interfacial thermal resistance, machine learning, thermal insulator, thin film
刊行年月日
更新時刻
2025-03-12 16:30:31 +0900

Acquiring and transferring comprehensive catalyst knowledge through integrated high-throughput experimentation and automatic feature engineering.pdf
Acquiring and transferring comprehensive catalyst knowledge through integrated high-throughput experimentation and automatic feature engineering
ジャーナル論文
著者
Ayu Fujiwara (author) (この著者で検索)
Japan Advanced Institute of Science and Technology Graduate School of Advanced Science and Technology
;
Sunao Nakanowatari (author) (この著者で検索)
Japan Advanced Institute of Science and Technology Graduate School of Advanced Science and Technology
;
Yohei Cho (author) (この著者で検索)
Japan Advanced Institute of Science and Technology Graduate School of Advanced Science and Technology
;
Toshiaki Taniike (author) (この著者で検索)
Japan Advanced Institute of Science and Technology Graduate School of Advanced Science and Technology
キーワード
Catalyst informatics, machine learning, high-throughput experimentation, descriptor, oxidative coupling of methane
刊行年月日
2025-12-31
更新時刻
2025-07-16 16:17:04 +0900

2604_supp_info.pdf
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
;
Kazutoshi Takahashi (author) (この著者で検索)
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

Understanding strain localization in metallic materials  a review of high-resolution digital image correlation and related techniques.pdf
Understanding strain localization in metallic materials: a review of high-resolution digital image correlation and related techniques
ジャーナル論文
著者
ORCID SAMURAI ;
T. E.J. Edwards (author) (この著者で検索)
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J. Quinta da Fonseca (author) (この著者で検索)
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J. -C. Stinville (author) (この著者で検索)
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D. Texier (author) (この著者で検索)
;
T. Vermeij (author) (この著者で検索)
キーワード
High-resolution digital image correlation, strain localization, crystal plasticity, data merging, metallic materials, machine learning
刊行年月日
2026-12-31
更新時刻
2026-03-13 08:30:04 +0900

ジャーナル論文
A design methodology of crystal growth furnace and process aided by two-step optimization using machine learning models and genetic algorithm
ジャーナル論文
著者
Hiroyuki Tanaka (author) (この著者で検索)
Nagoya University a Graduate School of Engineering
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Kentaro Kutsukake (author) (この著者で検索)
;
Kota Asakura (author) (この著者で検索)
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Takuto Kojima (author) (この著者で検索)
;
Xin Liu (author) (この著者で検索)
;
Noritaka Usami (author) (この著者で検索)
キーワード
Optimization, machine learning, genetic algorithm, crystal growth, process informatics
刊行年月日
2025-12-31
更新時刻
2026-02-27 12:30:07 +0900

20241223Nagamura_著者最終稿.pdf
機械学習高速自動スペクトル解析ソフト“EMPeaks”について
ジャーナル論文
著者
永村 直佳 (author) (この著者で検索)
ORCID SAMURAI ;
安藤 康伸 (author) (この著者で検索)
キーワード
spectroscopy, peak fitting, data analysis, machine learning
刊行年月日
2024-10-10
更新時刻
2025-01-10 16:31:04 +0900

STAM.pdf
Essential structural and experimental descriptors for bulk and grain boundary conductivities of Li solid electrolytes
ジャーナル論文
著者
Yen-Ju Wu (author) (この著者で検索)
ORCID SAMURAI ;
Takehiro Tanaka (author) (この著者で検索)
;
Tomoyuki Komori (author) (この著者で検索)
;
Mikiya Fujii (author) (この著者で検索)
;
Hiroshi Mizuno (author) (この著者で検索)
;
Satoshi Itoh (author) (この著者で検索)
National Institute for Materials Science
ORCID ;
Tadanobu Takada (author) (この著者で検索)
;
Erina Fujita (author) (この著者で検索)
ORCID SAMURAI ;
Yibin Xu (author) (この著者で検索)
ORCID SAMURAI
キーワード
Ionic conductivity, machine learning, grain boundary, ionic conductor, Li battery, grain size, descriptor
刊行年月日
2020-01-31
更新時刻
2024-01-05 22:11:22 +0900

Time-domain thermoreflectance technique using multiple delayed probe pulses for high-throughput data acquisition and analysis.pdf
Time-domain thermoreflectance technique using multiple delayed probe pulses for high-throughput data acquisition and analysis
ジャーナル論文
著者
Hiroto Arima (author) (この著者で検索)
National Institute of Advanced Industrial Science and Technology (AIST) National Metrology Institute of Japan (NMIJ)
;
Yuichiro Yamashita (author) (この著者で検索)
;
Takashi Yagi (author) (この著者で検索)
キーワード
Time-domain thermoreflectance, multiple delay, thin film, thermal effusivity, interfacial thermal resistance, machine learning
刊行年月日
2025-12-31
更新時刻
2025-07-16 16:14:58 +0900