キーワード: machine learning

6 件のレコードが見つかりました。

An interpretable linear model bridging data-driven analysis and chemical intuition for Eu2 -phosphor emissions.pdf
An interpretable linear model bridging data-driven analysis and chemical intuition for Eu 2+ -phosphor emissions
ジャーナル論文
著者
ORCID SAMURAI ;
Ryusei Hayasaka (author) (この著者で検索)
;
Yuta Matsushima (author) (この著者で検索)
ORCID ; ORCID SAMURAI ; ORCID SAMURAI ;
Naoto Hirosaki (author) (この著者で検索)
キーワード
materials informatics, phosphor, europium, machine learning, interpretability, linear model, composition-based feature
刊行年月日
2026-12-31
更新時刻
2026-07-07 14:31:04 +0900

ChemPlusChem25_90_e202500342.pdf
Machine Learning—Guided Design of Biomass‐Based Porous Carbon for Aqueous Symmetric Supercapacitors
ジャーナル論文
著者
Manickam Minakshi (author) (この著者で検索)
ORCID ;
Apsana Sharma (author) (この著者で検索)
;
Ferdous Sohel (author) (この著者で検索)
;
Almantas Pivrikas (author) (この著者で検索)
ORCID ;
Pragati A. Shinde (author) (この著者で検索)
ORCID ; ORCID SAMURAI ; ORCID SAMURAI
キーワード
biomass, carbon, dopant, energy, machine learning, storage
刊行年月日
2025-10-09
更新時刻
2025-10-21 16:06:10 +0900

d2ma00881e.pdf
Rapid discovery of new Eu2+-activated phosphors with a designed luminescence color using a data-driven approach
ジャーナル論文
著者
Yukinori Koyama (author) (この著者で検索)
National Institute for Materials Science Research and Services Division of Materials Data and Integrated System
ORCID SAMURAI ;
Hidekazu Ikeno (author) (この著者で検索)
Osaka Metropolitan University
;
Masamichi Harada (author) (この著者で検索)
National Institute for Materials Science Research Center for Functional Materials
;
Shiro Funahashi (author) (この著者で検索)
National Institute for Materials Science Research Center for Functional Materials
;
Takashi Takeda (author) (この著者で検索)
National Institute for Materials Science Research Center for Functional Materials
ORCID SAMURAI ;
Naoto Hirosaki (author) (この著者で検索)
National Institute for Materials Science Research Center for Functional Materials
キーワード
phosphor, materials design, machine learning, luminescence, emission spectrum, Eu2+
刊行年月日
2022-11-29
更新時刻
2024-01-05 22:11:23 +0900

Advanced Science - 2023 - Uryu - Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder.pdf
Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder Diffraction Patterns
ジャーナル論文
著者
Hirotaka Uryu (author) (この著者で検索)
;
Tsunetomo Yamada (author) (この著者で検索)
;
Koichi Kitahara (author) (この著者で検索)
;
Alok Singh (author) (この著者で検索)
ORCID SAMURAI ;
Yutaka Iwasaki (author) (この著者で検索)
ORCID SAMURAI ;
Kaoru Kimura (author) (この著者で検索)
National Institute for Materials Science
ORCID ;
Kanta Hiroki (author) (この著者で検索)
;
Naoki Miyao (author) (この著者で検索)
;
Asuka Ishikawa (author) (この著者で検索)
;
Ryuji Tamura (author) (この著者で検索)
;
Satoshi Ohhashi (author) (この著者で検索)
;
Chang Liu (author) (この著者で検索)
;
Ryo Yoshida (author) (この著者で検索)
キーワード
deep learning, x-ray powder diffraction, quasicrystal, phase identification, machine learning
刊行年月日
2023-11-14
更新時刻
2024-12-13 12:30:39 +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

Dataset
Supercon 2 Dataset
データセット
著者
ORCID
キーワード
superconductors, machine learning, dataset, tdm, materials science
刊行年月日
2022-09-10
更新時刻
2022-10-18 10:11:01 +0900

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