基于二维铁电钙钛矿的人工光突触晶体管制备与性能研究

Studies on the fabrication and performance of artificial optical synaptic transistor based on 2D perovskite ferroelectrics

  • 摘要: 神经形态计算通过模拟生物神经系统的突触可塑性,为构建低功耗、高容错的智能感知系统提供了新思路。本文提出了一种基于二维铁电钙钛矿材料(PMA)2PbCl4的光突触晶体管。该材料兼具铁电极化特性和宽光谱光响应能力。通过将其与高迁移率的有机半导体PDVT-10结合,设计了一种新型人工光突触器件。实验结果表明,该器件在光脉冲下能够成功模拟兴奋性突触后电流(EPSC)和双脉冲易化(PPF)等生物突触功能。基于该器件的神经网络在Fashion-MNIST数据集分类任务中表现出优异的抗噪声性能。本研究为开发高性能的神经形态视觉系统提供了新的材料与器件设计策略。

     

    Abstract: By simulating the synaptic plasticity of biological nervous systems, neuromorphic computing provides a new idea for building intelligent sensing systems with low power consumption and high fault tolerance. In this paper, an optical synaptic transistor based on a two-dimensional perovskite ferroelectrics (PMA)2PbCl4 is proposed, which has both ferroelectric polarization characteristics and wide-spectrum photoresponsiveness. By combining it with the high mobility organic semiconductor PDVT-10, a novel artificial optical synaptic device was designed. Experimental results show that the device successfully simulates biological synaptic functions such as excitatory post synaptic current (EPSC) and paired pulse facilitation (PPF) under light pulses. The neural network based on this device shows excellent anti-noise performance in the classification task of Fashion-MNIST dataset. This study provides a new material and device design strategy for the development of high-performance neuromorphic vision systems.

     

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