Dynamic simulation and modelling of chemical vapour deposition process

Abstract

This thesis mainly presents the use of CFD modelling to investigate and optimise the MOCVD processes in fabrication of II-VI compounds – cadmium telluride (CdTe) and zinc oxide (ZnO). It gives insight in detailed process modelling and proves the ability of using CFD modelling, which accounts for the interaction between hydrodynamics and chemical reactions in the reactor, to accurately predict the growth rate and thickness uniformity. The growth behaviour of CdTe was investigated in a custom-made inline MOCVD reactor by analysing the influence of the operating process parameters, which involves (a) deposition temperature, (b) operating pressure, (c) total flow rate, and (d) the partial pressure ratio of precursors on the performance of the thin film (i.e. thin film deposition rates, thickness uniformity and material utilisation) in steady flows. The deposition of ZnO was studied in a bespoke horizontal reactor. Flow behaviour, heat transfer and mass transfer involved in the MOCVD reactor were discussed under different process parameters, with the objective to improve MOCVD process control. A thermal field calculation was implemented in the CFD modelling of ZnO deposition. A series of experiments of coating ZnO layers were performed to validate the simulation results. In addition, the analytical model, with reasonable simplifications and approximations for ZnO deposition, were further performed to get an intuitive insight into the mechanism governing the growth rate and uniformity in MOCVD processes. A good agreement was achieved through theory analysis, numeral simulation and experiment. The analysis of the transport phenomena under different process parameters in this study can greatly contribute to optimising the MOCVD equipment and processes, and to achieving the ultimate goal of a better growth rate, uniformity and controllability on thin film with economic use of precursors.

Date of Award	8 Sept 2017
Original language	English
Awarding Institution	Univerisity of Nottingham
Supervisor	Xiaogang Yang (Supervisor) & Sean Rigby (Supervisor)