Artificial intelligence for sustainable consumption and production in green chemistry

Machine intelligence or artificial intelligence (AI) helps in the transformation of green chemistry by improving the sustainable consumption and production. The present study specifically focuses on the green chemistry aspects as how AI technologies are used to enhance the chemical processing, utilization of environment friendly solvents, and even monitor the processing through real time techniques. Enhancements achieved in other areas include yield of the desired products in various reactions, decrease in amounts of waste produced, and improvement in energy consumption. Nevertheless, there are still some unexplored problems which are still relevant now included data quality problems, limitations on model interpretability, and AI interface with the current systems. AI technologies also face other challenges that are attributed to the economic nature, which includes high initial costs and challenges of proving viability of the investments. In the same aspect, standards and ethical issues should be observed when it comes for applying AI in chemical processes. Even more studies also point out about research opportunities to advance such as refining the underpinning data fusion techniques, to design the interpretable AI models, and to expand the potential applications considering the new fields such as biodegradable materials and renewable energy systems. Therefore, overcoming interdisciplinary collaborations and ethical issues will be vital to the development of AI for green chemistry. If these difficulties are to be met and AI’s potential harnessed, the chemical industry can go a long way toward making real improvements to a range of environmental and economic metrics.