Fundamentals of Computational Design in Nanomaterials

NanomaterialsNanomaterials (NMs) have drawn a lot of interest in materials science and engineering due to their unique properties and diverse range of applications. Computational designComputational Design (CD) approaches are crucial for understanding and optimizing the properties of NMs, as they offer valuable insights that improve experimental procedures. An overview of the core ideas and techniques used in CD for NMs is provided in this chapter. Some of the key computational approaches we discuss are Monte Carlo (MonC) simulationsMaterial Simulation, density functional theoryDensity functional theory (DenFT), coarse-grained modellingCoarse grained modeling (CGM), molecular dynamics simulationsMolecular dynamics simulations (MolDS), and machine learningMachine learning (MAL) techniques. These methods can help researchers focus their experimental synthesis and characterization efforts, predict how NMs would behave in certain scenarios, and look into the mechanical, electrical, and structural properties of NMs. The field's future goals and challenges are also discussed, with an emphasis on how interdisciplinary collaboration and on-going innovation are required to address difficult NMs design problems. This study is a significant resource for researchers and practitioners interested in learning more about the exciting topic of CD in NMs since it provides insights into the methodology, applications, and potential effect of this field.