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Resource type
Journal article(3)
Keyword
Machine learning (3)
Anomalous Hall effect (1)
Automated synthesis (1)
Bayesian optimization (1)
Combinatorial (1)
Fragment descriptor (1)
High-throughput (1)
MSS (1)
Olfactory sensor (1)
Retention time prediction (1)
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Creative Commons BY Attribution 4.0 International (2)
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Keyword: Machine learning
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3 records found.
Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography
Journal article
Creator
Sitanan Sartyoungkul
(author) (
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Sitanan Sartyoungkul
;
Balasubramaniyan Sakthivel
(author) (
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)
Balasubramaniyan Sakthivel
;
Pavel Sidorov
(author) (
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)
https://orcid.org/0000-0001-6462-702X
(unauthenticated)
Pavel Sidorov
;
Yuuya Nagata
(author) (
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)
https://orcid.org/0000-0001-5926-5845
(unauthenticated)
Yuuya Nagata
Keyword
Automated synthesis
,
Fragment descriptor
,
Machine learning
,
Retention time prediction
,
Supercritical fluid chromatography
Date published
2025-11-26
Updated at
2025-12-24 15:05:55 +0900
Automated odor-blending with one-pot Bayesian optimization
Journal article
Creator
Yota Fukui
(author) (
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)
Yota Fukui
;
Kosuke Minami
(author) (
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https://orcid.org/0000-0003-4145-1118
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Kosuke Minami
;
Kota Shiba
(author) (
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https://orcid.org/0000-0001-7775-0318
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Kota Shiba
;
Genki Yoshikawa
(author) (
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https://orcid.org/0000-0002-9136-8964
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Genki Yoshikawa
;
Koji Tsuda
(author) (
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https://orcid.org/0000-0002-4288-1606
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Koji Tsuda
;
Ryo Tamura
(author) (
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)
https://orcid.org/0000-0002-0349-358X
National Institute for Materials Science
NIMS Researchers Directory SAMURAI
Ryo Tamura
Keyword
Machine learning
,
MSS
,
Bayesian optimization
,
Olfactory sensor
Date published
2024-04-16
Updated at
2024-06-10 12:30:19 +0900
High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning
Journal article
Creator
Ryo Toyama
(author) (
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)
https://orcid.org/0000-0002-7398-5803
NIMS Researchers Directory SAMURAI
Ryo Toyama
;
Yuma Iwasaki
(author) (
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)
https://orcid.org/0000-0002-7117-277X
NIMS Researchers Directory SAMURAI
Yuma Iwasaki
;
Prabhanjan D. Kulkarni
(author) (
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https://orcid.org/0000-0002-4605-5256
Prabhanjan D. Kulkarni
;
Hirofumi Suto
(author) (
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https://orcid.org/0000-0003-4387-5862
NIMS Researchers Directory SAMURAI
Hirofumi Suto
;
Tomoya Nakatani
(author) (
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)
https://orcid.org/0000-0001-9590-216X
NIMS Researchers Directory SAMURAI
Tomoya Nakatani
;
Yuya Sakuraba
(author) (
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)
https://orcid.org/0000-0003-4618-9550
NIMS Researchers Directory SAMURAI
Yuya Sakuraba
Keyword
Machine learning
,
High-throughput
,
Combinatorial
,
Anomalous Hall effect
Date published
2025-09-03
Updated at
2025-12-26 13:11:05 +0900
Keyword
Machine learning
(3)
Anomalous Hall effect
(1)
Automated synthesis
(1)
Bayesian optimization
(1)
Combinatorial
(1)
Fragment descriptor
(1)
High-throughput
(1)
MSS
(1)
Olfactory sensor
(1)
Retention time prediction
(1)
Supercritical fluid chromatography
(1)
RDE metadata def
RDE invoice schema
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