Nanophotonics (Apr 2024)
Color arrestor pixels for high-fidelity, high-sensitivity imaging sensors
Abstract
Silicon is the dominant material in complementary metal-oxide-semiconductor (CMOS) imaging devices because of its outstanding electrical and optical properties, well-established fabrication methods, and abundance in nature. However, with the ongoing trend toward electronic miniaturization, which demands smaller pixel sizes in CMOS image sensors, issues, such as crosstalk and reduced optical efficiency, have become critical. These problems stem from the intrinsic properties of Si, particularly its low absorption in the long wavelength range of the visible spectrum, which makes it difficult to devise effective solutions unless the material itself is changed. Recent advances in optical metasurfaces have offered new possibilities for solving these problems. In this study, we propose color arrestor pixels (CAPs) as a new class of color image sensors whose composite spectral responses directly mimic those of the human eye. The key idea is to employ linearly independent combinations of standardized color matching functions. These new basis functions allow our device to reproduce colors more accurately than the currently available image sensors with red-green-blue filters or other metasurface-based sensors, demonstrating an average CIEDE2000 color difference value of only 1.79 when evaluating 24 colors from the Gretag-Macbeth chart under standard illuminant D65. Owing to their high fidelity to the human eye response, CAPs consistently exhibit exceptional color reproduction accuracy under various spectral illumination compositions. With a small footprint of 860 nm height and 221 nm full-color pixel pitch, the CAPs demonstrated high absorption efficiencies of 79 %, 81 %, and 63 % at wavelengths of 452 nm, 544 nm, and 603 nm, respectively, and good angular tolerance. With such a high density of pixels efficiently capturing accurate colors, CAPs present a new direction for optical image sensor research and their applications.
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