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Anti-reflective coatings (ARCs) are used on the vast majority of solar photovoltaic (PV) modules to increase power production. However, ARC longevity can vary from less than 1 year to over 15 years depending on coating quality and deployment conditions. A technique that can quantify ARC degradation non-destructively on commercial modules would be useful both for in-field diagnostics and accelerated aging tests. In this paper, we demonstrate that accurate measurements of ARC spectral reflectance can be performed using a modified commercially-available integrating-sphere probe. The measurement is fast, accurate, non-destructive and can be performed outdoors in full-sun conditions. We develop an interferometric model that estimates coating porosity, thickness and fractional area coverage from the measured reflectance spectrum for a uniform single-layer coating. We demonstrate the measurement outdoors on an active PV installation, identify the presence of an ARC and estimate the properties of the coating.
We use a state-of-the-art optimization algorithm combined with a careful methodology to find optimal anti-reflective coatings. Our results show that ultra thin structures (less than $300 ,nm$ thick) outperform much thicker gradual patterns as well as
The desire for higher sensitivity has driven ground-based cosmic microwave background (CMB) experiments to employ ever larger focal planes, which in turn require larger reimaging optics. Practical limits to the maximum size of these optics motivates
We report on a comparison of spin relaxation rates in a $^{199}$Hg magnetometer using different wall coatings. A compact mercury magnetometer was built for this purpose. Glass cells coated with fluorinated materials show longer spin coherence times t
ASTRI is a Flagship Project of the Italian Ministry of Education, University and Research, led by the Italian National Institute of Astrophysics, INAF. One of the main aims of the ASTRI Project is the design, construction and verification on-field of
We present a non-destructive beam profile imaging concept that utilizes machine learning tools, namely genetic algorithm with a gradient descent-like minimization. Electromagnetic fields around a charged beam carry information about its transverse pr