Artificial Intelligence in Chemistry: Current Trends and Future Directions

人气 计算机科学 数据科学 化学 纳米技术 材料科学 心理学 社会心理学
作者
Zachary J. Baum,Xiang Yu,Philippe Y. Ayala,Yanan Zhao,Steven P. Watkins,Qiongqiong Angela Zhou
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:61 (7): 3197-3212 被引量:187
标识
DOI:10.1021/acs.jcim.1c00619
摘要

The application of artificial intelligence (AI) to chemistry has grown tremendously in recent years. In this Review, we studied the growth and distribution of AI-related chemistry publications in the last two decades using the CAS Content Collection. The volume of both journal and patent publications have increased dramatically, especially since 2015. Study of the distribution of publications over various chemistry research areas revealed that analytical chemistry and biochemistry are integrating AI to the greatest extent and with the highest growth rates. We also investigated trends in interdisciplinary research and identified frequently occurring combinations of research areas in publications. Furthermore, topic analyses were conducted for journal and patent publications to illustrate emerging associations of AI with certain chemistry research topics. Notable publications in various chemistry disciplines were then evaluated and presented to highlight emerging use cases. Finally, the occurrence of different classes of substances and their roles in AI-related chemistry research were quantified, further detailing the popularity of AI adoption in the life sciences and analytical chemistry. In summary, this Review offers a broad overview of how AI has progressed in various fields of chemistry and aims to provide an understanding of its future directions.
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