Keywords

Chemical spray pyrolysis; mixed metal oxide; film growth; nanocomposite; gas sensors; computational fluid dynamics; modeling; film processing; zinc oxide; tin oxide; aerosol; multi component droplet

Abstract

The role of sensor technology is obvious in improvement and optimization of many industrial processes. The sensor films, which are considered the core of chemical sensors, have the capability to detect the presence and concentration of a specific chemical substance. Such sensor films achieve selectivity by detecting the interaction of the specific chemical substance with the sensor material through selective binding, adsorption and permeation of analyte. This research focuses on development and verification of a comprehensive mathematical model of mixed metal oxide thin film growth using spray pyrolysis technique (SPT). An experimental setup is used to synthesize mixed metal oxide films on a heated substrate. The films are analyzed using a variety of characterization tools. The results are used to validate the mathematical model. There are three main stages to achieve this goal: 1) A Lagrangian-Eulerian method is applied to develop a CFD model of atomizing multi-component solution. The model predicts droplet characteristics in flight, such as spatial distribution of droplet size and concentration. 2) Upon reaching the droplets on the substrate, a mathematical model of multi-phase transport and chemical reaction phenomena in a single droplet is developed and used to predict the deposition of thin film. The various stages of droplet morphology associated with surface energy and evaporation are predicted. 3) The processed films are characterized for morphology and chemical composition (SEM, XPS) and the data are used to validate the models as well as investigate the influence of process parameters on the structural characteristics of mixed metal oxide films. The structural characteristics are investigated of nano structured thin films comprising of ZnO, SnO2, ZnO+In2O3 and SnO2+In2O3 composites. The model adequately predicts the size distribution and film thickness when the nanocrystals are well-structured at the controlled temperature and concentration.

Notes

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Graduation Date

2014

Semester

Fall

Advisor

Ilegbusi, Olusegun

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Mechanical and Aerospace Engineering

Degree Program

Engineering and Computer Science

Format

application/pdf

Identifier

CFE0005817

URL

http://purl.fcla.edu/fcla/etd/CFE0005817

Language

English

Release Date

June 2015

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science; Engineering and Computer Science -- Dissertations, Academic

Restricted to the UCF community until June 2015; it will then be open access.

Included in

Engineering Commons

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