The monograph is devoted to a comprehensive analysis of the implementation of artificial intelligence (AI) in various fields of chemistry. The work considers modern directions of AI application for the discovery of new drugs, development of innovative materials, prediction of chemical reactions, automation of laboratory experiments, spectroscopy and analytical chemistry. The benefits of using deep learning, machine learning algorithms, and generative models, as well as the challenges associated with data quality, ethics, and model interpretability, are analyzed in detail. Particular attention is paid to the evolution of AI in chemistry, the current state of research, and predictions for integration with other technologies, including robotics and quantum computing. The monograph aims to facilitate interdisciplinary dialog between chemists, computer scientists, and industry representatives for the effective implementation of AI in chemical research.
Hаlyna Hrytsuliak (Wed,) studied this question.