Abstract

Optoelectronic synaptic transistors possess the capability to simultaneously accomplish perception and process functions within a single device, thereby not only addressing the limitations of von Neumann architectures but also serving as a promising candidate for emulating neural vision systems. The extensive range of organic semiconductor materials offers a plethora of possibilities for device fabrication; however, the severe recombination of photogenerated carriers imposes limitations on the utilization of organic p-n bulk heterostructures in synaptic transistor construction. By incorporating an insulating polymer and implementing a p-n planar heterojunction architecture, the 30% PCBM@PAN-DPPDTT transistor was constructed using the PCBM/DPPDTT heterojunction and the PCBM@PAN photoresponsive charge trapping layer. Due to the effect of the photoresponsive charge trapping layer and interface traps, the device not only overcomes the shortcomings of p-n bulk heterojunction and exhibits typical synaptic properties but also demonstrates a significantly enhanced response to ultraviolet (UV) light, exhibiting nearly four times more excitatory postsynaptic current (ΔEPSC) compared to the device lacking PCBM. The transistor matrix was employed to simulate the image perception and memory functions of the human neural vision system. Furthermore, an artificial neural network with high recognition accuracy (∼95%) of handwritten numbers was constructed. This study proposes an additional approach for mitigating the issue of rapid recombination of photogenerated charge carriers in the construction of optoelectronic synaptic transistors by utilizing p-n heterojunction.

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