Black silicon nanotextures offer exceptionally low levels of reflectance and are of interest to the field of solar photovoltaics. The nanowires that form this texture create a graded refractive index, allowing light to be absorbed with high efficiency. Explored here is the application of these nanotextures on top of conventional microscale pyra- mids, combining the advantages forwarded by the latter, predominantly being a second chance for absorption, and the former, being light steering. These structures are known as hybrid black silicon. Variations on the wet chemical etch parameters are explored and related to topological features, which can, in–turn, be related to front surface reflectance. The hybrid black silicon textures created are shown to exhibit reflectance as low as 0.7%.
An advanced hemispherical reflectometry system is reported, designed for measuring the optical characteristics of a variety of samples resolved against wavelength, angle of incidence, and polarisation. Variable angle reflectance data enables a new perspective on the interaction between electromagnetic waves and nanostructures, which do not interact with light in the same way as their microscale counterparts. The versatility of this data is demonstrated for photovoltaics when combined with geographic spectral irradiance data. Solar cell optical performance, when structured with the textures measured in the reflectometer, is successfully predicted should that cell be placed in Southampton, UK. This mathematical formulation is capable, alongside the appropriate angle–resolved reflectance data, of approximating the optical performance of a given sample when situated almost anywhere in the world.
Supporting the reflectance data gathered through this work is a black silicon nanowire model, pseudorandomised using custom–made algorithms against a set of desired surface features. The model uniquely generates complex surface topologies that meet the requirements of electromagnetic wave optics simulations. The model reported showcases an accuracy within the ±2% relative error against measured reflectance, and offers a new, fast, and accurate way of simulating nanostructures without the need to manufacture them in bulk.