Plasmonic metasurfaces for subtractive color filtering: optimized nonlinear regression models.

We develop and explore a nonlinear regression modeling approach to designing subtractive color filters (SCFs) based on plasmonic metasurfaces. The approach opens up the possibility of rapidly choosing a desired optimized SCF design with high color saturation and brightness using an analytical expression. In this Letter, colors are produced by absorbing the light of specific wavelengths and reflecting the remaining spectrum with silver gap-plasmon nanoantennas deposited on a silver film. First, we design three different SCFs-yellow, magenta, and cyan. Then, by adjusting the design parameters of the nanoantennas, we optimize their high absorption resonance peaks (reflections dips), which are tunable over the visible spectrum. Finally, by using nonlinear regression analysis, we fit our results to a cubic regression model. Accordingly, a SCF for a color of choice can be designed in a straightforward way. This is a promising technique that provides a methodology to design preoptimized filters for practical applications such as color printing, high-resolution chromatic displays, and multi-spectral imaging.