Authors : Shyamalkant K. Biswas

Volume/Issue : Volume 11 - 2026, Issue 3 - March

Google Scholar : https://tinyurl.com/3bpdshfn

Scribd : https://tinyurl.com/tw6rkj32

DOI : https://doi.org/10.38124/ijisrt/26mar158

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Artificial Intelligence (AI) is rapidly transforming chemical sciences by enabling data-driven molecular discovery, reaction prediction, and process optimization. Simultaneously, global sustainability challenges such as climate change, pollution, and energy scarcity require innovative chemical solutions with minimal environmental impact. The integration of AI with chemistry offers a powerful framework for achieving sustainable development through green molecular design, energy-efficient catalysis, optimized industrial processes, and enhanced environmental monitoring. This review critically examines recent advances in AI-driven chemistry and evaluates their role in promoting future sustainability, while highlighting challenges related to data quality, interpretability, energy consumption, and ethical governance [1–5].

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