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Abstract
Cutting-edge mid-wavelength infrared (MWIR) sensing technologies leverage infrared photodetectors, memory units, and computing units to enhance machine vision. Real-time processing and decision-making challenges emerge with the increasing number of intelligent pixels. However, current operations are limited to in-sensor computing capabilities for near-infrared technology, and high-performance MWIR detectors for multi-state switching functions are lacking. Here, we demonstrate a non-volatile MoS2/black phosphorus (BP) heterojunction MWIR photovoltaic detector featuring a semi-floating gate structure design, integrating near- to mid-infrared photodetection, memory and computing (PMC) functionalities. The PMC device exhibits the property of being able to store a stable responsivity, which varies linearly with the stored conductance state. Significantly, device weights (stable responsivity) can be programmed with power consumption as low as 1.8 fJ, and the blackbody peak responsivity can reach 1.68 A/W for the MWIR band. In the simulation of Faster Region with convolution neural network (CNN) based on the FLIR dataset, the PMC hardware responsivity weights can reach 89% mean Average Precision index of the feature extraction network software weights. This MWIR photovoltaic detector, with its versatile functionalities, holds significant promise for applications in advanced infrared object detection and recognition systems.
In-sensor computing architectures can provide energy-efficient multifunctional capabilities, but their application to the mid-infrared range is challenging. Here, the authors report the realization of non-volatile MoS2/black phosphorus photovoltaic detectors, integrating near- to mid-infrared photodetection, memory and computing functionalities.
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1 Fudan University, State Key Laboratory of ASIC and System, School of Microelectronics, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443)
2 Fudan University, State Key Laboratory of ASIC and System, School of Microelectronics, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Chinese Academy of Sciences, State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Shanghai, China (GRID:grid.9227.e) (ISNI:0000000119573309); Shaoxin Laboratory, Shaoxing, China (GRID:grid.9227.e); Fudan University, Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception, Institute of Optoelectronics, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443)
3 Chinese Academy of Sciences, State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Shanghai, China (GRID:grid.9227.e) (ISNI:0000000119573309); University of Chinese Academy of Sciences, Hangzhou Institute for Advanced Study, Hangzhou, China (GRID:grid.410726.6) (ISNI:0000 0004 1797 8419)
4 Chinese Academy of Sciences, State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Shanghai, China (GRID:grid.9227.e) (ISNI:0000000119573309)
5 Fudan University, State Key Laboratory of ASIC and System, School of Microelectronics, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Fudan University, State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443)
6 Fudan University, State Key Laboratory of ASIC and System, School of Microelectronics, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Shaoxin Laboratory, Shaoxing, China (GRID:grid.8547.e); Fudan University, Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception, Institute of Optoelectronics, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Fudan University, State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Shanghai, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443)