Indeed, the numbers of both journal and patent publications increased with time, showing similar rapidly growing trends after 2015. Figure 1A and 1B shows the volume of these publications and their volume normalized by the overall number of journal publications or patents by year, respectively. From this search, roughly 70 000 journal publications and 17 500 patents from the CAS Content Collection were identified to be related to AI. The resulting search string is provided in the Supporting Information. In addition, matches on particularly problematic phrases, such as “brain” and “nerve” were excluded from consideration. The search query required screening of each term to minimize false positives due to polysemy a maximum of a 2% false positive rate was allowed for each OR-delimited phrase, as determined by random screenings of 50–100 documents performed by CAS experts. To this end, the CAS Content Collection was searched to identify AI-related publications from 2000 to 2020 based on various AI terms in their title, keywords, abstract text, and CAS expert-curated concepts. A quantitative analysis helps to understand just how fast chemistry publications using artificial intelligence are increasing relative to the increase in total chemistry publications. With the rapid growth in global research activity, scientific publication volume has steadily increased over the past 20 years. We hope that this Review can serve as a useful resource for those who would like to understand global trends in AI-oriented research efforts in chemistry. Finally, we look at the types of chemical substances most frequently involved in the AI-related literature, highlighting the distribution of AI-related publications among various classes of substances and their roles. We then provide lists of notable AI-related journal and patent publications in a variety of research areas. We first examine the growth and distribution of AI-related publications in chemistry, which includes the annual growth of publication volume and the distribution of publications among countries, organizations, and research areas, followed by a topic analysis revealing the evolution of frequently used concepts related to AI in chemistry. Expert-curated CAS content is suitable for quantitative analysis of publications against variables, such as time, country, research area, and substance details. The CAS Content Collection, as one of the largest collections of scientific databases in the world, has many unique features and annotations added during data curation. (16) There are more than 1000 global scientists specialized in various scientific domains curating, analyzing, and connecting data from published sources at CAS. The CAS Content Collection covers publications in 50 000 scientific journals from around the world in a wide range of disciplines, 62 patent authorities, and 2 defensive publications (Research Disclosures and IP.com). This Review uses the CAS Content Collection to contextualize the current AI landscape, classifying and quantifying chemistry publications related to AI from the years 2000–2020. 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.Īlthough significant publicity has been given to AI and its application in chemistry, perspective on its use and development in chemistry is not obvious from the massive volume of available information. 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. Notable publications in various chemistry disciplines were then evaluated and presented to highlight emerging use cases. Furthermore, topic analyses were conducted for journal and patent publications to illustrate emerging associations of AI with certain chemistry research topics. We also investigated trends in interdisciplinary research and identified frequently occurring combinations of research areas in publications. 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. The volume of both journal and patent publications have increased dramatically, especially since 2015. 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 application of artificial intelligence (AI) to chemistry has grown tremendously in recent years.
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