A comparative analysis of opto-thermal figures of merit for high temperature solar thermal absorber coatings

Solar thermal absorber coatings play a key role in the thermal efficiency of receivers for applications in the field of Concentrated Solar Power (CSP). The development of stable spectral selective coatings with a high solar absorptance alpha sol and a low thermal emittance epsilon th is often desired to reduce thermal losses. However, quantitative indicators describing selectivity and the trade-off between solar absorptance and thermal emittance is seldom discussed in the literature. In this review, relevant opto-thermal figures of merit are analyzed for the comparison of reference solar thermal absorber coatings, including real and ideal coatings, both black and spectral selective. The comparison is made for a temperature ranging from 25 to 1000 degrees C and for a concentration factor ranging from 20 to 1000, based on spectral data measured at room temperature from 0.25 to 20 mu m. New figures of merit are introduced, i.e. a normalized selectivity ratio Si*, a trade-off factor Ztrade-off, a normalized solar reflectance index SRI* and a peak efficiency temperature Tpeak,opt. These metrics are derived from existing figures of merit and adapted for CSP. The set of figures of merit analyzed in this review offer a complementary perspective for the detailed characterization of any coating opto-thermal performance. For solar thermal absorber coatings, thermal efficiency eta thermal and peak efficiency temperature Tpeak,opt are respectively deemed more insightful than opto-thermal efficiency eta opt-th and maximum steady-state temperature TSST,max, when comparing the relative opto-thermal performance of two coating formulations.

Automated summary

This review analyzes opto-thermal figures of merit to compare solar thermal absorber coatings, focusing on the trade-off between selectivity, solar absorptance, and thermal emittance. New figures of merit are introduced and adapted for Concentrated Solar Power applications, providing insights for detailed characterization and comparison of coating performance.