Award Date

May 2018

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Mechanical Engineering

First Committee Member

Jaeyun Moon

Second Committee Member

Robert F. Boehm

Third Committee Member

Evangelos A. Yfantis

Fourth Committee Member

Yi-Tung Chen

Fifth Committee Member

Kathleen Robins

Number of Pages

208

Abstract

A special class of cuprous-based inorganic oxide materials, synthesized as nanoparticles via hydrothermal and co-precipitation methods, are portable to spectrally-selective absorber coatings with high solar-thermal energy conversion efficiency. Operating reliably at elevated temperatures when used in tandem with solar concentrators, these materials enable cost-competitive solar energy conversion technology that can be incorporated with thermal energy storage systems, supporting the viability of novel renewable power generation; notably, optimizing absorptive performance while mitigating thermal losses through re-radiated waste heat motivates sustainable energy production particular to desert climates, where water conservation and ecological sensitivity needs are paramount.

This work targets the chemical synthesis optimization of such absorber coating materials to reliably form spectrally-selective surface texturing. Specifically, the synthesis of phase-stable uni-metallic and bi-metallic oxide materials (CuO, Co3O4, Cu0.15Co2.84O4, Cu1.5Mn1.5O4, while viable for bulk manufacturability of absorber coatings, can be improved to increase solar absorptive capability with the addition of embedding sacrificial polymer beads. By modifying coating surface morphology, adjustable porous geometries materialize at mesoscale, enabling facile light-trapping structures for high ultraviolet and visible spectral absorptance while limiting infrared emittance. Morphological detail of the fabricated coating materials, as qualified by Field-Emission Scanning Electron Microscopy (FESEM), determine quantitative correlations in calculating spectral absorptance, optical scatter, and irradiance/exitance distributions of incident solar radiation. Image processing on the material’s microscopy data is used in custom raytracing simulations that calculate energy propagation to correlate material properties based on surface structuring. To ensure an accurate representation of the sample morphology, multiresolution analysis is performed to construct approximated surface profiles of the material. Ultimately, these computational approaches are proposed for optimizing chemical reaction conditions of inorganic nanomaterial syntheses, demonstrating simulation approaches to predict coating performance, supporting the characterization of nanomaterial fabrication that result in absorber coatings tenable for long-term usage in solar power technologies.

Keywords

Energy; Morphology; Raytracing; Solar; Spectrally-Selective; Transport

Disciplines

Engineering Science and Materials | Materials Science and Engineering

Language

English

Available for download on Wednesday, May 15, 2019


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