Big data approaches, overcoming critical limitations, and enhanced optical and environmental stability of Al2O3/Ti/Al2O3 colored solar-selective absorber coatings

Big data approaches include statistical, trend, and data-driven spectral fitting analyses. Colored solar selective absorbers (CSSAs), which offer a vibrant visual alternative to black solar selective absorbers due to their aesthetic appeal, are often assumed to have low solar absorptance (αs). Using CUDA-accelerated simulations of more than 900 million thin-film structures, we show that when 87% < αs < 90%, all color regions can achieve reflectance above 20%, overturning the misconception that bright coloration compromises solar absorptance. Trend- and big-data-driven spectral-fitting analyses elucidate the impact of film thickness variations on the wavelengths of extreme values and how surface roughness affects film thickness and αs, respectively. Additionally, critical limitations such as narrow viewing angle ranges and angular color shifts are systematically addressed. Optimized surface roughness in Al₂O₃/Ti/Al₂O₃ CSSAs broadens the viewing angle of approximately 60° with minimal color variation and enhances αs by > 4%. Environmental durability metrics—including adhesion strength, corrosion resistance, thermal stability, and self-cleaning potential—demonstrate exceptional long-term stability, with a long service lifetime. CSSAs optimized for surface roughness demonstrate vibrant colors, wide viewing angle ranges, high solar absorptance, and superior durability. Coupled with a well-designed marketing strategy, these features underscore the strong commercial potential of integrating CSSAs into sustainable building systems.