キーワード: machine learning

31 件のレコードが見つかりました。 1件目から10件目まで表示します。

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

Atomic descriptors generated from coordination polyhedra in crystal structures.pdf
Atomic descriptors generated from coordination polyhedra in crystal structures
ジャーナル論文
著者
Yuki Inada (author) (この著者で検索)
;
Yukari Katsura (author) (この著者で検索)
ORCID SAMURAI ;
Masaya Kumagai (author) (この著者で検索)
;
Kaoru Kimura (author) (この著者で検索)
キーワード
Materials informatics, machine learning, atomic descriptors, coordination polyhedra, formation energy prediction, band gap prediction
刊行年月日
2021-01-01
更新時刻
2024-11-21 16:35:29 +0900

2025秋季応用物理学会.pdf
Structure Prediction from Chemical Formula Using Periodic Descriptors
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
periodic descriptor, structure prediction, machine learning, template substitution
刊行年月日
更新時刻
2025-09-13 08:30:19 +0900

s41524-025-01671-w.pdf
Discovery of liquid crystalline polymers with high thermal conductivity using machine learning
ジャーナル論文
著者
Hayato Maeda (author) (この著者で検索)
ORCID ;
Stephen Wu (author) (この著者で検索)
ORCID ;
Rika Marui (author) (この著者で検索)
ORCID ;
Erina Yoshida (author) (この著者で検索)
;
Kan Hatakeyama-Sato (author) (この著者で検索)
;
Yuta Nabae (author) (この著者で検索)
;
Shiori Nakagawa (author) (この著者で検索)
;
Meguya Ryu (author) (この著者で検索)
;
Ryohei Ishige (author) (この著者で検索)
;
Yoh Noguchi (author) (この著者で検索)
;
Yoshihiro Hayashi (author) (この著者で検索)
ORCID ; ORCID SAMURAI ; ORCID SAMURAI ;
Felix Jiang (author) (この著者で検索)
;
Xuan Thang Vu (author) (この著者で検索)
;
Sven Ingebrandt (author) (この著者で検索)
ORCID ;
Masatoshi Tokita (author) (この著者で検索)
;
Junko Morikawa (author) (この著者で検索)
ORCID ;
Ryo Yoshida (author) (この著者で検索)
ORCID ;
Teruaki Hayakawa (author) (この著者で検索)
キーワード
liquid crystalline polymer, thermal conductivity, machine learning, PoLyInfo
刊行年月日
2025-07-02
更新時刻
2025-08-19 12:30:21 +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

Manuscript.pdf
Graph Network-Based Simulation of Multicellular Dynamics Driven by Concentrated Polymer Brush-Modified Cellulose Nanofibers
ジャーナル論文
著者
Chiaki Yoshikawa (author) (この著者で検索)
ORCID SAMURAI ;
Duc Anh Nguyen (author) (この著者で検索)
;
Tadashi Nakaji-Hirabayashi (author) (この著者で検索)
;
Ichigaku Takigawa (author) (この著者で検索)
;
Hiroshi Mamitsuka (author) (この著者で検索)
キーワード
cellulose nanofiber, concentrated polymer brush, hMSC, self-assembly, machine learning
刊行年月日
2024-04-08
更新時刻
2024-08-27 08:30:31 +0900

3-12-Revised Manuscript without Any Highlighting.docx
Machine-Learning-Driven Discovery of Mn4+-Doped Red-Emitting Fluorides with Short Excited-State Lifetime and High Efficiency for Mini Light-Emitting Diode Displays
ジャーナル論文
著者
Hong Ming (author) (この著者で検索)
ORCID ;
Yayun Zhou (author) (この著者で検索)
;
Maxim S. Molokeev (author) (この著者で検索)
ORCID ;
Chuang Zhang (author) (この著者で検索)
;
Lin Huang (author) (この著者で検索)
;
Yuanjing Wang (author) (この著者で検索)
; ORCID SAMURAI ;
Enhai Song (author) (この著者で検索)
ORCID ;
Qinyuan Zhang (author) (この著者で検索)
ORCID
キーワード
luminescent materials, machine learning
刊行年月日
2024-05-06
更新時刻
2025-04-03 08:30:20 +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

jmca2024_NaSulfideConductor_esi_rj.pdf
Computational discovery of stable Na-ion sulfide solid electrolytes with high conductivity at room temperature
ジャーナル論文
著者
Seong-Hoon Jang (author) (この著者で検索)
ORCID ;
Randy Jalem (author) (この著者で検索)
ORCID SAMURAI ;
Yoshitaka Tateyama (author) (この著者で検索)
ORCID SAMURAI
キーワード
all solid state batteries, solid electrolytes, high-throughput first-principles calculation, computational materials search, machine learning, sodium ion conductors
刊行年月日
2024-08-05
更新時刻
2024-10-10 16:30:52 +0900

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

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