Floating-gate transistors improve recognition precision in image preprocessing for edge computing, suggesting high potential.
Nonvolatile optoelectronic synapses motivated by the human eye can effectively function as convolutional kernels to preprocess images, demonstrating significant promise for edge computing. Among the optoelectronic synapses, the floating-gate photosensitive transistor (FG-PT) is particularly noteworthy due to its rapid response speed and excellent retention. Although some FG-PTs are reported, they still suffer from high operating voltages, low conductance ratios, and difficulties in array preparation. Here, a ZnO QDs@CsPbBr3 poly-heterocrystalline (PHC) film to serve as the floating gate layer of FG-PT is synthesized. The PHC film combines the desirable properties of each phase, exhibiting both high electrical conductivity and excellent photoelectric properties. The high electrical conductivity allows FG-PT to store a large amount of charge at a low voltage (1 V). While the excellent photoelectric properties facilitate the gradual erasure of these charges under light pulses, resulting in a large conductance ratio (≈3.57×105). Moreover, the excellent film-forming properties of the PHC film enable the fabrication of an FG-PT array comprising 25,600 devices on 1 cm2 substrate. Using the FG-PT array to preprocess images achieves a significantly higher recognition precision at the fifth epoch (87.64%) than that of the original images (58.08%) and CMOS-processed images (77.68%), indicating great potential for edge computing.
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Xu et al. (2025) studied this question.
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