Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry

Rizvi Syed Aal E Ali; Jiaolong Meng; Muhammad Ehtisham Ibraheem Khan; Xuefeng Jiang

Artificial Intelligence Chemistry (Jun 2024)

Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry

Rizvi Syed Aal E Ali,
Jiaolong Meng,
Muhammad Ehtisham Ibraheem Khan,
Xuefeng Jiang

Affiliations

Rizvi Syed Aal E Ali: State Key Laboratory of Molecular & Process Engineering, School of Chemistry and Molecular Engineering, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China
Jiaolong Meng: State Key Laboratory of Molecular & Process Engineering, School of Chemistry and Molecular Engineering, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China
Muhammad Ehtisham Ibraheem Khan: State Key Laboratory of Molecular & Process Engineering, School of Chemistry and Molecular Engineering, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China; Green Chemistry Group, School of Sciences and Technology, Chemistry Division, University of Camerino ChIP Research Center, Via Madonna delle Carceri, 62032 Camerino, MC, Italy
Xuefeng Jiang: State Key Laboratory of Molecular & Process Engineering, School of Chemistry and Molecular Engineering, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China; State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China; State Key Laboratory of Organometallic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China; Corresponding author at: State Key Laboratory of Molecular & Process Engineering, School of Chemistry and Molecular Engineering, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China.

Journal volume & issue: Vol. 2, no. 1
p. 100049

Abstract

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Artificial intelligence (AI) is driving a revolution in chemistry, reshaping the landscape of molecular design. This review explores AI’s pivotal roles in the field of organic synthesis applications. AI accurately predicts reaction outcomes, controls chemical selectivity, simplifies synthesis planning, accelerates catalyst discovery, and fuels material innovation and so on. It seamlessly integrates data-driven algorithms with chemical intuition to redefine molecular design. As AI chemistry advances, it promises accelerated research, sustainability, and innovative solutions to chemistry’s pressing challenges. The fusion of AI and chemistry is poised to shape the field’s future profoundly, offering new horizons in precision and efficiency. This review encapsulates the transformation of AI in chemistry, marking a pivotal moment where algorithms and data converge to revolutionize the world of molecules.

Published in Artificial Intelligence Chemistry

ISSN: 2949-7477 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Science: Chemistry; Science: Mathematics: Instruments and machines: Electronic computers. Computer science
Website: https://www.sciencedirect.com/journal/artificial-intelligence-chemistry

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