Demonstrates wavelength-specific detection in devices, suggesting new pathways for intelligent computing.
In‐sensor computing integrates signal acquisition and processing within a single device, enabling real‐time, low‐power visual perception. Wavelength‐multiplexing holds great promise for leveraging the spectral dimension of light to expand parallel processing channels. However, current in‐sensor architectures typically rely on photodetectors with fixed spectral responses, limiting their ability to perform wavelength‐specific computations. Here, we present a neuromorphic wavelength photodetector integrated with 3D laser‐nanoprinted nanopillar metafilters that can simultaneously detect light intensity and wavelength across the visible range. The device features a bidirectional Indium Tin Oxide/n‐Si/Indium Tin Oxide heterojunction with two independently addressable regions, each covered by a metafilter with distinct transmittance spectra. By analyzing the photocurrent ratio under opposite biases, wavelength‐resolved detection is achieved with a resolution of 16.9 nm after accounting for the power‐dependent variation of the photocurrent ratio. Furthermore, the metafilters enable wavelength‐dependent binary weight encoding, thus we could demonstrate a binary neural network (BNN) model that switches computational tasks based on input wavelength—classifying handwritten digits at 520 nm and fashion items at 450 nm, respectively. This work provides a scalable and programmable approach for multifunctional, wavelength‐multiplexed in‐sensor computing, and highlights the potential of laser‐printed metasurface‐integrated photodetectors for future intelligent optoelectronics.
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Dong et al. (2026) studied this question.
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