The current research status and prospects of AI in chemical science

Abstract

This paper primarily examines the utilization and obstacles of AI in the domain of chemistry. Machine learning facilitates the advancement of chemical research at every level through the use of AI. AI has significantly contributed to enhancing the efficiency of chemical experiments and manufacturing, as well as reducing costs, throughout the many phases of chemical study, application, and production. Its impact is particularly notable in the development of new materials and the discovery of drugs. Nevertheless, the implementation of AI in the domain of chemistry encounters numerous obstacles, including inadequate data quality, limited model interpretability, and data privacy concerns. To address these issues, it is imperative for the scientific and technological community to foster multidisciplinary collaboration, develop a more comprehensive and practical AI framework, and investigate more secure data security technologies. In the future, as AI continues to advance, the relationship between AI and chemical research will become more dependable and intimate. This will lead to increased efficiency, safety, and cost-effectiveness in chemical research, ushering in a new era in the field of chemistry.