可调控光电双输出人工发光突触器件

Controllable photoelectric dual-output artificial light-emitting synapse device

  • 摘要: 人工突触器件是神经形态计算的重要硬件基础。然而,传统器件多依赖单一电学调控,突触权重难以直观获取,且缺乏独立的抑制型调控手段。本文在量子点发光二极管结构中引入聚(4-乙烯基苯酚)(Poly(4-vinylphenol),PVP)电荷俘获层,制备了一种可调控光电双输出人工发光突触器件,实现了电导调制与发光输出的同步耦合。该器件在电脉冲刺激下表现出典型的突触可塑性行为,其兴奋性突触后电流(excitatory postsynaptic current,EPSC)幅值可随脉冲频率和幅度连续调节,成对脉冲易化(paired-pulse facilitation,PPF)指数随脉冲间隔呈指数衰减特性。进一步引入紫外光作为独立抑制信号,可使器件电导在数秒内显著降低,从而实现对电脉冲诱导权重累积的有效调控。基于该器件构建的人工神经网络在MNIST手写数字识别任务中取得了最高93.05%的分类准确率,相比无光调控条件下提高了5.88%,展示了该器件在神经形态计算与可视化信息处理中的应用潜力。

     

    Abstract: Artificial synapse devices serve as a critical hardware foundation for neuromorphic computing. However, traditional devices predominantly rely on single electrical regulation, which limits the intuitive acquisition of synaptic weights and lacks independent inhibitory regulation mechanisms. This study introduces a charge -trapping layer of poly (4-vinylphenol) (PVP) into the quantum dot light-emitting diode (QLED) structure to fabricate an artificial light-emitting synapse device capable of achieving synchronous coupling between electrical conductance modulation and light output. The device demonstrates typical synaptic plasticity behavior under electrical pulse stimulation. The amplitude of the excitatory postsynaptic current (EPSC) can be continuously modulated by varying the pulse frequency and amplitude, while the paired-pulse facilitation (PPF) index exhibits an exponential decay characteristic with increasing pulse intervals. Furthermore, the introduction of ultraviolet (UV) light as an independent suppression signal effectively reduces the device's conductance within seconds, providing precise regulation of the synaptic weight accumulation induced by electrical pulses. An artificial neural network constructed using this device achieved a classification accuracy of 93.05% in the MNIST handwritten digit recognition task, which is 5.88% higher than the accuracy achieved without light regulation. These results highlight the significant application potential of this device in neuromorphic computing and visual information processing.

     

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