Green Nanotechnology Meets Artificial Intelligence: Toward Smart and Sustainable Environmental Systems

Abstract

Green nanotechnology: Green nanotechnology is an emerging technology to curb serious environmental problems by ensuring a non-toxic perspective in designing, synthesis, and application of the nanomaterials. At the same time, Artificial Intelligence (AI) is a revolutionary technology that facilitates streamlining the processes, forecasting, and competent decision-making. This article discusses how green nanotechnology and AI will fuse and create intelligent sustainable environmental frameworks. Nanomaterials are found to be useful in pollution cleanup, energy conversion, and efficiency optimization; however, the work described in this paper can advance the use of nanomaterials in these areas using AI-driven forecasting, real-time input, and predictive modeling. A methodology in which literature was reviewed, case studies were analyzed, and simulations were performed using AI was used to study what opportunities these hybrid systems have. The results also show that AI could make experimental trial and error during the design of nanomaterials, increasing energy efficiency, and quickening the pace of remediation and cleaning up the environment, thus making their design and synthesis scalable, and sustainable. Nonetheless, the challenges of a high computation requirement, data paucity, ethical issues, and possible nanomaterial toxicity are yet to be addressed. Areas of future work and research should focus on explainable AI models in nanoscience, forming standardized databases on sustainable nanomaterials, and studying the potential of the overlap between AI and nanotechnology within the concept of a circular economy. This integration is a paradigm shift to smart, eco centric solutions in handling the environment.