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March 25, 2026Small0 citations

Self‐Adaptive Infrared Vision via Neural‐Controlled Gain Compression in a Single Photodetector

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YSYu SongXLXin LiJGJunzhe Gu

Key Points

  • The research aims to develop a neuromorphic photodetector for adaptive infrared vision that exceeds human capability.
  • Utilized a gate-tunable Au/BP/PdSe2 van der Waals heterostructure for gain control.
  • Implemented electrostatic barrier reconfiguration for nonlinear gain compression.
  • Integrated a neural-network-based microcontroller for real-time adjustments of optical gain.
  • Achieved a linear dynamic range of approximately 80 dB at 1550 nm.
  • Demonstrated sub-millisecond response times with intrinsic polarization sensitivity (PR > 10).
  • Expanded adaptability in infrared vision without the need for external optics or analog circuitry.

Abstract

Biological vision relies on eye-mediated gain control to adapt across lighting conditions-but remains fundamentally blind to infrared wavelengths and polarization. Here, we report a neuromorphic photodetector that not only emulates this self-adaptive functionality, but surpasses human vision by enabling dynamic gain regulation across the infrared-polarization domain. Using a gate-tunable Au/BP/PdSe2 van der Waals heterostructure (vdWH), we achieve eye-like nonlinear gain compression via electrostatic barrier reconfiguration, which enables dynamic modulation of both the response area and responsivity. Integrated with a neural-network-based microcontroller, the system forms a device-level closed-loop that autonomously adjusts optical gain in real time. This expands the linear dynamic range (LDR) by three orders of magnitude, reaching ∼80 dB at 1550 nm, with sub-millisecond response and intrinsic polarization sensitivity (PR > 10)-all without external optics or analog circuitry. These results establish a scalable, intelligent optoelectronic platform that augments biological perception and advances chip-scale self-adaptive vision for autonomous sensing and edge photonic intelligence.

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Cite This Study

Song et al. (2026) studied this question.

synapsesocial.com/papers/69c37b93b34aaaeb1a67e214https://doi.org/10.1002/smll.202514438
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