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Chemical Science, volume 15, issue 31, pages 12200-12233

Automation and machine learning augmented by large language models in a catalysis study

Yuming Su ^{1, 2}

Xue Wang ¹

Yuanxiang Ye ³

Yibo Xie ³

Yujing Xu ¹

Yibin Jiang ²

Cheng Wang ^{1, 2}

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iChem, State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China |

Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361005, P. R. China |

Institute of Artificial Intelligence, Xiamen University, Xiamen 361005, P. R. China |

Publication type: Journal Article

Publication date: 2024-06-26

Royal Society of Chemistry (RSC)

Journal: Chemical Science

scimago Q1

wos Q1

SJR: 2.333

CiteScore: 14.4

Impact factor: 7.6

ISSN: 20416520, 20416539

DOI: 10.1039/d3sc07012c

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Abstract

AI and automation are revolutionizing catalyst discovery, shifting from manual methods to high-throughput digital approaches, enhanced by large language models.

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Publisher

Royal Society of Chemistry (RSC)

Journal

Chemical Science

scimago Q1

wos Q1

SJR

2.333

CiteScore

14.4

Impact factor

7.6

ISSN

20416520 (Print)

20416539 (Electronic)

Automation and machine learning augmented by large language models in a catalysis study

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