Synthesis and applications of graphene and graphene-based nanocomposites: Conventional to artificial intelligence approaches

• Published in: Frontiers in environmental chemistry Vol. 3
• Main Authors: Tariq, Waheed, Ali, Faizan, Arslan, Chaudhry, Nasir, Abdul, Gillani, Syed Hamza, Rehman, Abdul
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 31.08.2022
• Subjects: agricultural applications; AI modeling; energy; environmental remediation; graphene; nanocomposites
• ISSN: 2673-4486; 2673-4486
• DOI: 10.3389/fenvc.2022.890408

Recent advances in graphene research have enabled the utilization of its nanocomposites for numerous energy-based and environmental applications. Recently, the advancement in graphene-based polymer nanocomposites has received much attention with special emphasis on synthesis and application. Graphene-based nanocomposites show astonishing electrical, mechanical, chemical, and thermal characteristics. Graphene nanocomposites (GNCs) are synthesized using a variety of methods, including covalent and non-covalent methods, a chemical-based deposition approach, hydrothermal growth, electrophoresis deposition, and physical deposition. Chemical methods are the most viable route for producing graphene in small quantities at low temperatures. The technique can also produce graphene films on a variety of substrate materials. The use of artificial intelligence (AI) for the synthesis of AI-created nanoparticles has recently received a lot of attention. These nanocomposite materials have excellent applications in the environmental, energy, and agricultural sectors. Due to high carrier mobility, graphene-based materials enhance the photocatalytic performance of semiconductor materials. Similarly, these materials have high potential for pollutant removal, especially heavy metals, due to their high surface area. This article highlights the synthesis of graphene-based nanocomposites with special reference to harnessing the power of modern AI tools to better understand GNC material properties and the way this knowledge can be used for its better applications in the development of a sustainable future.