Methodology and Application of Information Technology for Carbon-Based Nano-Composites

Recent developments of carbon-based nanomaterials research have made it possible to use them for a wide range of environmental, material development, and energy-related applications. Graphene, CNT, quantum dots, nano-diamond, and graphene oxide are examples of carbon-based nanomaterials. The development of nanocomposites has drawn a lot of attention lately, with synthesis and application receiving. Recently, there has been a lot of interest in the synthesis of AI-created nanoparticles using artificial intelligence. This work focuses on the synthesis of carbon-based nanocomposites and application of current AI tools to better understand the properties of carbon derivative material, and this information can be applied to the development and application of materials for solution of society's problem. To explain the synthetic and derivation process, adaptive neuro-fuzzy inference systems and ANN may be efficient. Derivations of the nanomaterials are the output of the models, which have various inputs such as catalyst dosage, particle size, concentration, content, exposure time.