Sustainable nanohybrids for environmental remediation: Green synthesis, mechanistic design, AI-driven optimization, and circular economy perspectives.

Environmental pollution, driven by industrialization, urbanization, and intensive agriculture, has unleashed a cascade of hazardous contaminants, heavy metals, synthetic dyes, persistent organic pollutants, and emerging micropollutants, into air, water, and soil. These agents pose profound risks to ecosystems and human health due to their toxicity, bioaccumulation, and resilience to natural degradation. Conventional remediation methods, though partially effective, are often hindered by high costs, poor selectivity, secondary pollution, and excessive energy demands. In response, the development of sustainable, eco-friendly, high-performance materials offers a transformative alternative. This review provides a critical and systematic analysis of sustainable nanohybrids and green functional materials for remediating contaminated environments, with three distinctive contributions that distinguish it from existing literature: (i) quantitative structure-property-performance relationships linking material composition, morphology, and surface chemistry to remediation efficiency; (ii) integration of artificial intelligence and machine learning (AI/ML) as predictive design tools for material optimization; and (iii) a circular economy framework emphasizing waste valorization, renewable feedstocks, and end-of-life material management. The review examines green synthesis routes-biomimetic, plant-based, and low-energy fabrication-that minimize ecological footprints, while addressing ecotoxicological profiles, environmental compatibility, biodegradability, and safe disposal. A broad spectrum of applications is explored, including adsorption, photocatalysis, ion exchange, membrane filtration, and nano-bioremediation. Key materials, carbon-based nanostructures, metal-organic frameworks, biopolymers, green-synthesized nanoparticles, biosurfactants, and deep eutectic solvents, are analyzed in relation to their physicochemical properties (surface area, porosity, functional group tunability) and pollutant removal performance. The review provides comparative insights into sustainable versus traditional approaches, emphasizing environmental safety, operational feasibility, and regeneration potential. Challenges such as scalability, real-world stability, and long-term ecotoxicity are critically assessed alongside regulatory considerations. Importantly, this review establishes a comprehensive performance matrix comparing several material systems across ten dimensions, offering the first integrated framework that bridges experimental performance, mechanistic understanding, and data-driven predictive design. Ultimately, this review highlights the promise of green nanohybrids as next-generation remediation platforms and aims to guide future research toward scalable, non-toxic, multifunctional materials aligned with green chemistry and circular economy principles, paving the way for a cleaner, healthier environment.