Numerical Simulation of Graphene Growth by Chemical Vapor Deposition Based on Tesla Valve Structure

Chemical vapor deposition (CVD) has become an important method for growing graphene on copper substrates in order to obtain graphene samples of high quality and density. This paper mainly focuses on the fluid flow and transmission phenomenon in the reactor under different process operating conditions and reactor structures. Two macroscopic physical parameters that are established as important for CVD growth are temperature and pressure. Based on the special structure of a miniature T45-R Tesla valve acting as a CVD reactor structure, this study uses numerical simulation to determine the effect of the pressure field inside a Tesla valve on graphene synthesis and temperature variation on the graphene surface deposition rate. This macroscopic numerical modeling was compared to the existing straight tube model and found to improve the graphene surface deposition rate by two orders of magnitude when the 1290-1310 K reaction temperature range inside the Tesla valve was maintained and verified through the experiment. This study provides a reference basis for optimizing the reactor geometry design and the effects of changing the operating parameters on carbon deposition rates during a CVD reaction, and will furthermore benefit future research on the preparation of high-quality, large-area, and high-density graphene by CVD.

Automated summary

Chemical vapor deposition (CVD) is a key method for growing high-quality and high-density graphene on copper substrates. This study focuses on the fluid flow and transmission phenomena in the CVD reactor under different operating conditions and structures. By using numerical simulation, the effect of the pressure field inside a T45-R Tesla valve on graphene synthesis and the temperature variation on the graphene surface deposition rate were determined. The results showed a significant improvement in the graphene surface deposition rate when the reactor temperature was maintained within a specific range, as verified by experiments. This study provides important insights for optimizing reactor design and understanding the impact of operating parameters on carbon deposition rates during CVD.