ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Filtering by
- Creators: Phelan, Patrick
In this study, primary focus was on optimizing the operating conditions, determining the better catalyst material, and analyzing the reaction products for the process of electrochemical reduction of carbon dioxide (ERC). Membrane electrode assemblies (MEA’s) are developed by air bushing the metal particles with a spray gun on to Nafion-212 which is a solid polymer based electrolyte (SPE), to support the electrodes in the electrochemical reactor gas diffusion layers (GDL) are developed using porous carbon paper. Anode was always made using the same material which is platinum but cathode material was changed as it is the working electrode.
The membrane electrode assembly (MEA) is then placed into the electrochemical reactor along with gas diffusion layer (GDL) to assess the performance of the catalyst material by techniques like linear sweep voltammetry and chronoamperometry. Performance of MEA was analyzed at 4 different potentials, 2 different temperatures and for 2 different cathode catalyst materials. The reaction products of the process are analyzed using gas chromatography (GC) which has thermal conductivity detector (TCD) used for detecting hydrogen (H2), carbon monoxide (CO) and flame ionization detector (FID) used for detecting hydrocarbons. The experiments performed at 40o C gave the better results when compared with the experiments performed at ambient temperature. Also results suggested that copper oxide cathode catalyst has better durability than platinum-carbon. Maximum faradaic efficiency for methane was 5.3% it was obtained at 2.25V using copper oxide catalyst. Furthermore, experiments must be carried out to make the electrochemical reactor more robust to withstand all the operating conditions like higher potentials and to make it a solar powered reactor.
The main objective of this work is to experimentally study the near-field radiative transfer and the excitation of resonance modes by designing nanostructured thin films separated by nanometer vacuum gaps. In particular, the near-field radiative heat transfer between two parallel plates of intrinsic silicon wafers coated with a thin film of aluminum nanostructure is investigated. In addition, theoretical studies about the effects of different physical mechanisms such as SPhP/SPP, MPs, and HM on near-field radiative transfer in various nanostructured metamaterials are conducted particularly for near-field TPV applications. Numerical simulations are performed by using multilayer transfer matrix method, rigorous coupled wave analysis, and finite difference time domain techniques incorporated with fluctuational electrodynamics. The understanding gained here will undoubtedly benefit the spectral control of near-field thermal radiation for energy-harvesting applications like thermophotovoltaic energy conversion and radiation-based thermal management.
In this dissertation, I first present colloidal nanocrystal superlattices as a new class of three-dimensional phononic crystals with periodicity in the sub-20 nm size regime using the plane wave expansion method. These calculations show that colloidal nanocrystal superlattices possess phononic band gaps with center frequencies in the 102 GHz range and widths in the 101 GHz range. Varying the colloidal nanocrystal size and composition provides additional opportunities to fine-tune the phononic band gap. This suggests that colloidal nanocrystal superlattices are a promising platform for the creation of high frequency phononic crystals.
For the next topic, I explore opportunities to use supervised machine learning for expedited discovery of phononic band gap presence, center frequency and width for over 14,000 two-dimensional phononic crystal structures. The best trained model predicts band gap formation, center frequencies and band gap widths, with 94% accuracy and coefficients of determination (R2) values of 0.66 and 0.83, respectively.
Lastly, I expand the above machine learning approach to use machine learning to design a phononic crystal for a given set of phononic band gap properties. The best model could predict elastic modulus of host and inclusion, density of host and inclusion, and diameter-to-lattice constant ratio for target center and width frequencies with coefficients of determinations of 0.94, 0.98, 0.94, 0.71, and 0.94 respectively. The high values coefficients of determination represents great opportunity for phononic crystal design.