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Title: Biomimetic nanostructured surfaces for antireflection in photovoltaics
Author: Boden, Stuart Andrew
ISNI:       0000 0004 2668 2986
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2009
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A key consideration in the design of any solar cell is the reduction of reflectance from the top surface. Traditional thin film antireflection schemes are being challenged by new techniques that involve texturing on the subwavelength scale to form ‘moth-eye’ arrays, so called because they are inspired by Nature’s answer to unwanted reflections, the arrays of pillars found on the eyes and wings of some species of moth. In this work, a new method is presented for the optimization of thin film coatings that accounts for the angular and spectral variations in incident solar radiation from sunrise to sunset. This approach is then extended to silicon moth-eye arrays to assess how effectively these surfaces can provide antireflection for silicon solar cells over a full day. The reflectance spectra of moth-eye surfaces are found to depend on the period of the arrays and the height and shape of the pillars, and consequently these parameters can be optimized for the solar spectrum. Simulations predict that replacing an optimized double layer thin film coating with a moth-eye array could increase the full day cell performance by 2% for a laboratory cell and 3% for an encapsulated cell. Compared to a perfectly transmitting interface, this corresponds to losses in short circuit current of only 5.3% and 0.6% for a laboratory and an encapsulated cell, respectively. Furthermore, fabrication of silicon moth-eye arrays by electron beam lithography and dry etching leads to predicted percentage losses at peak irradiance, compared to an ideal antireflective surface, of only 1%. The potentially more scalable technique of nanoimprint lithography is also used to fabricate antireflective moth-eye arrays in silicon, over areas as large as 1 cm2, demonstrating great potential for stealth and antiglare applications in addition to photovoltaics.
Supervisor: Bagnall, Darren Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QA75 Electronic computers. Computer science