Chemical vapor deposition of 2D materials: A review of modeling, simulation, and machine learning studies
Sayan Bhowmik, Ananth Govind Rajan
Abstract
). Herein, we survey the vast literature regarding modeling and simulation of the CVD growth of 2D materials and their heterostructures. We also focus on newer materials, such as silicene, phosphorene, and borophene. We discuss how density functional theory, kinetic Monte Carlo, and reactive molecular dynamics simulations can shed light on the thermodynamics and kinetics of vapor-phase synthesis. We explain how machine learning can be used to develop insights into growth mechanisms and outcomes, as well as outline the open knowledge gaps in the literature. Our work provides consolidated theoretical insights into the CVD growth of 2D materials and presents opportunities for further understanding and improving such processes.