<p>The world’s dependence on oil cannot continue indefinitely. As reserves dwindle and demand continues to increase, prices will soar to new highs and fundamentally change the way society deals with energy generation and consumption. Use of oil and other carbon-based fuels also have detrimental effects on human health, as pollution that arises from the combustion of these fuels necessitates treating respiratory problems in millions of people annually. Moreover, evidence that climate change is anthropogenic has become undeniable and has been proven to be direct related to dependence on carbon-based fuels.</p> <p>Renewable energy offers clean and dependable alternatives for electricity, heating and transport. In particular, solar energy looks to be the most promising owing to its sheer abundance and ubiquity. The main obstacle hindering the adoption of solar cell technology en masse is cost. One of the ways to reduce cost is to fabricate thinner solar cells, but this compromises efficiency due to lower optical absorption that results, especially in silicon. In order to become a serious competitor in the energy market, highly absorptive solar cells must be developed at reduced material costs, which is the essence of light-trapping.</p> <p>In this study, two of the most common ways to trap light by reducing reflection were investigated: the application of anti-reflection coatings and surface texturing in silicon. Analytic models were created to optimize optical design in both single-junction and multi-junction solar cells. The single-junction silicon models accounted for non-normal incidence, which allowed angle-averaged calculations to be made for planar and textured surfaces. Single-junction GaAs models included a GaInP window layer whose optical effects were considered in anti-reflection coating optimization. The multi-junction GaAs-on-silicon (GaAs/Si) and AlGaAs-on-silicon (AlGaAs/Si) models that were created clearly demonstrated the need to adjust individual subcell thicknesses in order to optimize optical design.</p> / Master of Applied Science (MASc)
Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/11272 |
Date | 10 1900 |
Creators | Al-Turk, Sarry |
Contributors | Kleiman, Rafael, Engineering Physics |
Source Sets | McMaster University |
Detected Language | English |
Type | thesis |
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