Date of Award

2022

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Mechanical, Automotive, and Materials Engineering

Keywords

Graphene, Microwave plasma reactor, Nanotechnology, Numerical model, Soot

Supervisor

N.Eaves

Supervisor

H.Hu

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Graphene is a novel nanomaterial capable of revolutionizing technology in many sectors but is difficult to produce on a useful scale. To improve our understanding of graphene formation, a computational model has been developed to simulate graphene synthesis in a scalable microwave plasma reactor. Unlike earlier graphene growth models, this one uses a sectional method to solve the population balance model. A sensitivity analysis was performed to assess the impact of the individual process rates. The rates were adjusted by multiplying and dividing the base rates by a factor of 2. The process rates that were adjusted in this way were graphene inception, graphene surface growth, amorphous particle inception, amorphous particle surface growth, restructuring pre-exponential factor, and restructuring activation energy. The most important quantities affected by changing these rates were the mass of graphitic particles, mass of amorphous particles, the number of graphitic layers, and the volume diameter of the amorphous particles. This analysis was carried out for both ethanol and toluene as precursors. It was found that the results were most sensitive to changes in the graphene surface growth rate and were least influenced by the soot inception rate.

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