Spectrally selective coatings are used in absorbers of solar collectors to maximize efficiency of solar thermal energy systems. Desired coating should have high absorptance at solar wavelengths and low emittance at the wavelengths where absorber emits heat. This study focuses on pigmented coatings that consist of a binder and uniformly distributed nano-particles known as pigments that exhibit the desired spectrally selective behavior. Radiative behavior of coatings depend on coating thickness, pigment size, concentration, and the optical properties of binder and pigment materials. In order to understand the effect of these parameters, a radiative model of the pigmented coatings is developed using Lorentz-Mie theory in conjunction with Hartel theory to incorporate the multiple scattering effects. Through the solution of the radiative transfer equation by the four flux method, spectral emittance is predicted. Design of such a coating is formulated as an inverse problem of estimating design variables yielding the desired spectral emittance of the ideal coating. The nonlinear problem is solved by optimization applying two algorithms for the solution. While both algorithms are capable of providing the same solution, the convergence of Quasi Newton method is found to be superior to that of Nelder Mead simplex algorithm.
Spectrally Selective Solar Absorbers based on Ta:SiO
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Cermets for Next‐Generation Concentrated Solar–Thermal Applications
