P3: Multiscale Modeling of Chemical Vapor Deposition

Chemical vapor deposition (CVD) is widely used to deposit important 2D and 3D materials for coatings, corrosion resistance, and electronics applications. However, in most cases, the deposited films are not perfect but exhibit defects (e.g. hydrogen defects in SiN or vacancies in graphene), which dramatically affect materials properties. As the most promising method for high quality, large area graphene synthesis, CVD has drawn enormous attention. Optimization of this chemical process will enable control over crucial properties, such as graphene quality and domain size, which is needed for many future high-end applications. This requires the development of a detailed atomistic understanding of the underlying processes guiding the growth mechanism. In particular there is a need to understand the mechanism behind graphene nucleation and growth during CVD and its dependence on the synthetic parameters: temperature, CVD pressure, catalyst type, facet and phase, feedstock type, and the presence of chemical etchants, to name only a few.
In order to optimize the CVD process it is important to describe and control the defect distribution, which requires the combination of simulation methods for the deposition phase (classical – long timescale), the surface reaction and subsequent surface rearrangement (classical – short timescale).

Providing a library of surface reaction mechanisms on a model substrate, e.g. copper, where adsorption energies and transition states will be calculated at the DFT level is the first challenge of this project. The CVD process on surfaces is rather complex with many reaction pathways possible. This prohibits a complete description of all reaction mechanisms at the DFT level. Therefore, the next challenge would be identifying those transition states that are becoming relevant during the kinetic Monte Carlo (KMC) modeling. KMC implementation considering the provided list and desired mechanism will be the last important challenge of the project.

The aim of this project is to develop a DFT-based on-the-fly kinetic Monte Carlo (OtFkMC) workflow that allows to model the process of chemical vapor deposition (CVD) of graphene precursors like methane on metal substrates. The method will be applied to study the synthesis of graphene and carbon nanotubes with a special focus on the ability of controlling the defect density of the materials.

Schematic drawing of catalyzed CVD. Mariana Kozlowska
P3: CVD of graphene using a catalyst with high carbon solubility.
Name Title Group Contact
PD Dr. Karin Fink, KIT INT (P3)

  Prof. Felix Studt, KIT IKFT (P3)