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Photoelectric synaptic transistors integrate optical sensing and synaptic functions into a single device, which has significant advantages in neuromorphic computing for visual information, recognition, memory, and processing. However, the weight updating of existing photoelectric synapses is predominantly based on separate utilization of light and electrical stimuli to regulate synaptic excitation and inhibition. This approach significantly restricts the processing speed and application scenarios of devices. In this work, we propose bipolar synaptic organic/inorganic heterojunction transistor (BSOIHT) that can effectively simulate bidirectional (excitatory/inhibitory) synaptic behavior under light stimulation. Furthermore, by changing the position of electrode contacts and the metals of source and drain electrodes, carrier injection of the transistor is significantly improved with reduced synaptic event power consumption down to 2.4 fJ. Moreover, the BSOIHTs are adopted to build the neuromorphic vision system, which effectively facilitates image preprocessing and substantially enhances the recognition accuracy from 44.93% to 87.01%. This paper provides new avenues for the construction of energy-efficient artificial vision systems.
Liu et al. (Thu,) studied this question.
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