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An experimental and graph theoretic study of atomic layer deposition processes for spacecraft applications

dc.contributor.advisorAdomaitis, Raymond Aen_US
dc.contributor.authorSalami, Hosseinen_US
dc.description.abstractAccurate understanding of the atomic layer deposition (ALD) process kinetics is necessary for developing new ALD chemistries to produce novel nanomaterials, and also optimization of typical ALD processes used in industrial applications. Proposing a potential reaction sequence alongside with accurate kinetic data is among the very first steps in studying the ALD process kinetics and forms the backbone of further engineering analysis. A valid and proper ALD reaction net work (RN) must be able to reflect the self-limiting and cycle to cycle reproducibility behavior experimentally observed for practical ALD processes. Otherwise, the mathematical model built based on it fails to precisely capture and reproduce ALD behavior no matter how accurate the available kinetic data are. In this work, a RN analysis method based on species-reaction graphs and the principles of convex analysis is developed to study the mathematical structure and dynamical behavior of thin-film deposition RN models. The key factor in ALD RN analysis is the presence of consistent surface-originated invariant states for each ALD half-cycle. Therefore, the primary focus of the proposed approach is on identifying and formulating physically-relevant RN invariant states, and to study the chemical significance of these conserved modes for ALD reaction mechanisms. The proposed method provides a well-defined framework, applicable to all ALD systems, to examine the above criteria of a proper ALD RN without requiring any information on the reaction rates. This method fills a gap in the procedure of ALD process modeling before the time-consuming step of calculating individual reaction rates which is usually done through ALD experiments in reactors equipped with in-situ measurement instruments or computationally expensive computational chemistry-based calculations such as density functional theory. The presented approach is also extended to study the variant states of a RN. The generalized method provides information on different variant states dynamically depending on each individual reaction in the network which facilitates the study and ultimately the formulation of different reaction rates in the system. In the second part of this dissertation, an experimental study of ALD of indium oxide and indium tin oxide films using the trimethylindium, tetrakis (dimethylamino) tin(IV), and ozone precursor system is conducted to first, investigate the potential application of this ALD process for producing high-quality transparent conducting layers; and second, to understand the relationship between the thickness of the deposited films and their electrical and optical properties. The optimized recipe was then used to process commercial Z93 heat radiator pigments used in manufacturing spacecraft thermal radiator panels to enhance their electrical conductivity to avoid the differential charging that may occur due to the interaction with charged particles in Van Allen radiation belts. To this aim a specialized ALD reactor was designed and constructed capable of processing standard flat substrates as well as coating micron-sized particles. The results confirm that the proposed process can be used to coat the heat radiator pigment particles and that the indium oxide film can nucleate and grow on their surface. This provides an example from a variety of potential space-related applications that can benefit from the ALD process.en_US
dc.titleAn experimental and graph theoretic study of atomic layer deposition processes for spacecraft applicationsen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentChemical Engineeringen_US
dc.subject.pqcontrolledChemical engineeringen_US
dc.subject.pquncontrolledAtomic layer depositionen_US
dc.subject.pquncontrolledReaction networken_US
dc.subject.pquncontrolledSpecies-reaction graphen_US

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