Artificial Intelligence in Bio-Recovery of Noble Metals: A Sustainable Strategy for Circular Economy

Noble Metals (NMs) such as gold, silver, platinum, palladium and rhodium are essential for various technological applications. Their traditional methods of extraction are resource-intensive and environmentally invasive challenging their prospective utilisation. As global demand for these metals are increasing with simultaneous e-waste generation, eco-friendly and sustainable recovery approaches are the need of hour. Bio-recovery is a method of extraction of metals from waste through biosorption, bioaccumulation and bio reduction by utilizing microorganisms, algae and fungi. This offers an alternative green and cost-effective strategy allowing efficient and optimum recovery (up to 80-95%) of noble metals even at low concentrations with adsorption capacities ranging from ~50 mg g⁻¹ to ~170 mg g⁻¹. Further, the use of toxic chemicals or high energy inputs are minimized using this approach. This review explores the efficacy of various eukaryotes microalgae (C. vulgaris and S. obliquus), fungi (A. niger and P. chrysogenum), plants (B. juncea and E.crassipes), protozoa and invertebrates in the recovery mechanism of NMs from industrial waste, e-waste and contaminated environments. Despite notable progress, challenges remain in scalability, metal recovery efficiency, downstream processing and economic feasibility. Such bio-recovery process empowered with Artificial Intelligence (AI) and machine learning can complement the outcome by providing a cutting-edge, eco-friendly strategy for managing noble metal resources. This communication further highlights the different available approaches for recovery of various NMs and their amalgamation with AI tools and intelligent computing. AI tools such as machine learning, neural networks and bioinformatics platforms can optimize process parameters (pH, temperature and nutrient supply) predict microbial performance and automate real-time monitoring with high predictive accuracy (upto 90% accuracy) to maintain ideal conditions for recovery. Our review would provide strategic insights into understanding the efficiency and scalability of noble metal recovery through the combination of AI and green biotechnology thereby contributing towards the circular economy. Future progress will depend on interdisciplinary collaborations and continued innovation at the intersection of microbiology, engineering and artificial intelligence.