Self‐Adaptive Infrared Vision via Neural‐Controlled Gain Compression in a Single Photodetector
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/PdSe<sub>2</sub> 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.
Authors
- Feilong Yu (ORCID: https://orcid.org/0000-0002-6993-6558)
- Jiaji Yang
- Yu Song
- Wei Lu
- Guanhai Li
- Juntong Liu
- Jin Chen
- Xiaoshuang Chen
- Xin Li
- Junzhe Gu
Institutions
- ShanghaiTech University (CN)
- Shanghai Institute of Technical Physics (CN)
- Shanghai Clinical Research Center (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Small
- Published
- 2026-03-22
- DOI
- https://doi.org/10.1002/smll.202514438
- Primary Topic
- 2D Materials and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00