A high-linearity synaptic phototransistor based on CsPbBr3-attached MXene nanostructures for image classification and edge detection tasks
Artificial photonic synapses offer an efficient solution for overcoming the von Neumann bottleneck in data storage and processing, providing advantages over electrical synapses by eliminating the bandwidth-connection-density tradeoff and exhibiting low power consumption. Perovskite quantum dots (QDs) have garnered significant attention in artificial photonic synapses due to their facile synthesis and favorable optoelectronic properties. However, challenges such as limited carrier mobility and nonlinearity impede their performance in neuromorphic applications. In this study, CsPbBr 3 -attached MXene nanostructures (CsPbBr 3 -MXene), in-situ growth of CsPbBr 3 QDs on MXene nanosheets, were proposed as the light-absorbing layer of a synaptic phototransistor. The heterostructure formed by CsPbBr 3 and MXene enhances photocurrent generation. Comparative analyses between CsPbBr 3 -MXene synapse transistor and that containing only CsPbBr 3 revealed a 24.6% higher excitatory postsynaptic current (EPSC) in the CsPbBr 3 -MXene one under identical light pulse stimulation. Following calculations and comparisons, the linearity exhibited significant improvement, decreasing from 4.586 to 1.099. Furthermore, the recognition accuracy in handwritten digit classification notably increased, rising from 86.13% to 92.05%. Moreover, the F1 score in edge detection had improvement, advancing from 0.8165 to 0.9065, approaching closer to 1. These improvements have demonstrated substantial assistance in the field of neural computing.
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