Abstract :
Although the demand for renewable energy is rapidly rising, and the supply of solar energy is truly abundant, the high cost of photovoltaic solar cells (PV) still limits their contribution to less than 0.5% the global energy mix. A design principle common to many next generation solar cells is the reduction of the cell thickness by 2 orders of magnitude, from 100 µm to 1 µm. This reduces costs, as each cell consumes less material, and this can be of lower purity. Nanowire (NW) arrays are particularly well suited to these aims, as they can be grown on cheap substrates using low grade materials and produce enhanced absorption to homogeneous films of equal thickness (let alone of equal mass).
The interaction of sun light with NW arrays involves a multitude of competing effects including diffraction, Fabry-Pérot resonances, modal coupling, and slow light propagation. These effects are highly dispersive across the broad bandwidth of the solar spectrum (700+ nm). Further more the prominence of each effect differs drastically between materials. Tuning the parameters of NW arrays for optimal solar energy conversion efficiency is therefore a difficult challenge, that currently requires large scale numerical simulations.
In my talk I will outline a semi-analytic method for predicting the optimal parameters of NW arrays. This method builds on an intuitive understanding of each design parameter (radius, period, volume fraction, height) and requires only a priori knowledge of the materials dispersive refractive indices. This approach provides a powerful predictive tool to guide NW array designs for PV, and is a satisfying synthesis of the complicated physics.
Biography : Björn Sturmberg is a PhD student at the University of Sydney, Australia, where he works with Prof. Martijn de Sterke and Prof. Ross McPhedran in the CUDOS research group. His work is supported by an Australian Solar Institute scholarship.
Contact Chercheur : bjorn.sturmberg@physics.usyd.edu.au
Invitation : Stefan ENOCH & Guillaume Demesy - Équipe CLARTE
ResearchGate
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