Research and optimization of ZnO-MOCVD process parameters using CFD and genetic algorithm

Abstract

Metal-organic chemical vapor deposition (MOCVD) is used to manufacture semiconductor materials. Process parameters such as the growth temperature, inlet flow rate, chamber pressure, and growth speed play major roles in the design and growth of thin films for a new chamber. Based on a newly developed MOCVD chamber, the effects of these parameters on the flow and thermal fields of a chamber were studied using the chemical-reaction-transport model of a DEZn and H2O grown ZnO film. Orthogonal experiments showed the effects of the parameters on the film uniformity and deposition rate. A response surface model was numerically simulated and mathematically modeled. Finally, a genetic optimization algorithm was used to optimize the process parameters and determine the optimal input process parameters for film uniformity. These results suggest a means of achieving outstanding uniform epitaxial growth and provide a theoretical basis for improvements in equipment.