Random anti-reflective nanostructured surfaces (rARSS) enhance optical transmission through suppression of Fresnel reflection at layered-media boundaries. Windows with rARSS treatment are characterized (transmittance, reflectance, and scatter) using spectrophotometry and scatterometry to assess transmissive scatter performance over various spectral bands. Using measured spectral data, partial-integrated scatter values were obtained, allowing the comparison of random anti-reflective surface performance to optically flat surfaces.
Using a transfer function approach, an approximation of far-field light scatter can be modeled based on surface statistics. rARSS feature topology was determined using optical profilometry to obtain statistical surface roughness parameters, to assess the structured-surface feature scales. Random rough surfaces are well-modeled by Gaussian statistics, making them ideal candidates for a surface transfer function approach of surface scatter analysis.
The Generalized Harvey-Shack surface scatter theory was used to calculate surface feature diffractive effects. Scatter distributions predicted using a Gaussian two-parameter model of a random surface and structured surface metrology data were compared to measured scatter data for assessment of the transfer function model validity within the bandlimit of interest. Results show that prediction of wide angle rARSS optical scatter is viable using the transfer function approach, but the theory fails to predict transmission enhancement due to the inclusion of roughness.