Cross-material synergies of carbon nanomaterials, MOFs, and COFs: innovative approaches for sustainable environmental remediation and resource recovery

Abstract

Sustainable environmental remediation and resource recovery are critical to addressing pollution, resource depletion, and ecosystem degradation. This review introduces the new concept of cross-material synergies, integrating carbon nanomaterials (CNMs), Metal-Organic Frameworks (MOFs), and Covalent Organic Frameworks (COFs) into multi-functional composite systems. By leveraging their complementary properties, these materials overcome key challenges such as structural instability, poor selectivity, and scalability limitations. Cross-material composites—including MOF@COF hybrids and CNM-MOF integrations—enhance adsorption performance, stability, and reusability compared to their individual components. Our review demonstrate how these hybrid systems improve pollutant removal, catalytic degradation, and resource recovery, aligning with sustainability goals. Their ability to transform waste into valuable materials supports circular economy principles and key Sustainable Development Goals (SDGs), including SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action). Furthermore, the review highlights strategies for optimising material performance, ensuring industrial scalability, and minimising environmental impact through Safe and Sustainable by Design (SSbD) approaches. Unlike previous reviews that focus on individual materials, this work provides a holistic roadmap for designing and deploying cross-material composites for real-world applications. By bridging fundamental research with industrial implementation, these systems present a transformative step toward sustainable material science, with far-reaching implications for environmental remediation and resource recovery. Future research should focus on enhancing synthesis efficiency, ensuring long-term material stability, and addressing economic feasibility for large-scale deployment.