Role of Artificial Intelligence in Green Analytical Technique

Abstract

Green analytical chemistry (GAC) has been accelerated by the growing necessity to mitigate environmental degradation and other health hazards posed by conventional analytical processes. The discipline is aimed at minimizing chemical waste and energy consumption and reliance on dangerous substances. The present review explains the usage of Artificial Intelligence (AI) in collaboration with GAC to enhance its sustainability, precision, and efficiency in its analytical operations. The article describes the twelve postulates of GAC, dwells upon the developments in the green chromatography, green spectroscopy, and green extraction techniques, new approaches to gauging of greenness, including GAPI, and the Analytical Eco-Scale. The AI innovation is more concentrated in such aspects as optimization of methods, automation, minimization of waste, and environmental observation. In green analytical chemistry, the application of AI presents a new direction of sustainable operations despite the drawbacks such as high costs, regulatory issues, and data availability. A combination of green principles and digital intelligence is not only enhancing the ability to make analyses but also uniting the chemical sciences in the process of building a greener, safer, and smarter world.