Direct-detected spectroscopy based on plasmonic Schottky photodetector and a deep neural network

Computational algorithms have facilitated the miniaturization of spectrometers, which is essential for on-chip and portable applications. Plasmonic Schottky photodetector provides a filter-free and complementary metal-oxide-semiconductor compatible scheme for spectral measurement. In this study, we report on a direct-detected spectral analysis based on a vertically coupled plasmonic nanostructure integrated Schottky photodetector. We demonstrate that the plasmonic Schottky photodetector has a fast response with a -3dB bandwidth of 600 kHz and a high peak detectivity of 8.65×1010 Jones. By designing a deep neural network, we demonstrate the reconstruction of the unknown spectrum with a mean-square error of 1.57×10-4 at a broad operating waveband of 450-950 nm, using only 20 distinct devices. Moreover, the spectral resolution of the 20 devices can reach to 7 nm. These findings provide a promising route for the development of chip-integrated spectrometers with high spectral accuracy and optical performance.