AI-Augmented Photon-Trapping Spectrometer-on-a-Chip on Silicon Platform with Extended Near-Infrared Sensitivity

TL;DR

This paper introduces a silicon photodiode-based spectrometer-on-a-chip with AI-enhanced spectral reconstruction, achieving high-resolution hyperspectral imaging in the extended near-infrared range up to 1100nm, suitable for portable applications.

Contribution

The work presents a fully integrated, AI-augmented spectrometer with photon-trapping textures and neural network reconstruction, extending NIR sensitivity beyond traditional limits on a CMOS-compatible platform.

Findings

Achieves <0.05 RMSE spectral reconstruction accuracy

Operates effectively up to 1100nm wavelength

Maintains high SNR even with significant detector noise

Abstract

We present a compact, noise-resilient reconstructive spectrometer-on-a-chip that achieves high-resolution hyperspectral imaging across an extended near-infrared (NIR) range up to 1100nm. The device integrates monolithically fabricated silicon photodiodes enhanced with photon-trapping surface textures (PTST), enabling improved responsivity in the low-absorption NIR regime. Leveraging a fully connected neural network, we demonstrate accurate spectral reconstruction from only 16 uniquely engineered detectors, achieving <0.05 RMSE and 8nm resolution over a wide spectral range of 640nm to 1100nm. Our system outperforms conventional spectrometers, maintaining signal-to-noise ratio above 30dB even with 40dB of added detector noise; extending functionality to longer wavelengths up to 1100nm, while the traditional spectrometers fail to perform beyond 950nm due to poor detector efficiency and noise performance. With a footprint of 0.4mm2, dynamic range of 50dB, ultrafast time response (57ps), and high photodiode gain (>7000), this AI-augmented silicon spectrometer is well-suited for portable, real-time, and low-light applications in biomedical imaging, environmental monitoring, and remote sensing. The results establish a pathway toward fully integrated, high-performance hyperspectral sensing in a CMOS-compatible platform.