oaioai:example.org:rutgers-lib:45362

Simulation and optimization of the GaN MOCVD process

Abstract

A detailed mathematical model for the growth of gallium nitride (GaN) in metalorganic chemical vapor deposition (MOCVD) process is developed, and the complete chemical mechanism is introduced, which has 17 gas phase and 23 surface species participating in 17 gas phase and 52 surface reactions. Based on an experimental study on the flow and thermal transport processes in the system, and available experimental data in the literature, validation study is conducted to ensure its accuracy. After that, the entire model is applied to perform steady state numerical simulation of the GaN MOCVD process in both 2D impinging reactor and 3D rotating disk reactor. The flow, temperature and concentration profiles are predicted, and the dependence of the growth rate and uniformity of the deposited layers on operating conditions, such as reactor operating pressure, susceptor temperature, inlet velocity, rotational speed, and concentration ratio of the precursors, is investigated to gain greater insight into the reactor performance and characteristics. The transient behavior of the GaN deposition process is numerically investigated. The 2D impinging reactor is considered to examine the time-dependent transport in the MOCVD process, including the steady-state deposition process, and the system start-up and shut-down. The temperature field and the deposition rate are studied as functions of time, as well as the precursor mass fraction at certain times. This work also provides inputs on the effects of changing operating conditions and the duration of starting and shut down effects. Two design variables, inlet velocity and inlet precursor concentration ratio, which have a significant effect on the deposition rate and uniformity of the film are identified. Inlet precursor concentration ratio is defined as the ratio of the volume flow rate of ammonia to the volume flow rate of trimethylgallium. Response surfaces for deposition rate and uniformity as a function of inlet velocity and inlet precursor concentration are developed by Compromise Response Surface Method (CRSM). The response surfaces are used to generate the Pareto frontier for the conflicting objectives of optimal deposition rate and uniformity. The trade-off between deposition rate and uniformity is captured by the Pareto frontier.Ph.D.Includes bibliographical referencesby Jiandong Men

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oaioai:example.org:rutgers-lib:45362Last time updated on 7/9/2019

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