Sb2Se3铁电晶体管突触器件的制备及其性能研究

Fabrication and performance study of Sb2Se3 ferroelectric transistor synaptic devices

  • 摘要: 铁电晶体管(ferroelectric field-effect transistor, FeFET)兼具无损读取、低功耗以及栅压可调的非易失沟道电导等优势,被认为是实现高性能人工突触器件的重要候选之一。为满足神经形态系统对多模态信息处理的需求,本研究设计并制备一种融合电信号与光信号感知功能的FeFET型突触器件。采用Hf0.5Zr0.5O2(HZO)作为铁电栅介质层,以光敏Sb2Se3半导体作为导电沟道层,成功制备出Sb2Se3铁电晶体管。实验结果表明,通过调控栅极电脉冲参数,该器件能够有效模拟兴奋性突触后电流(excitatory postsynaptic current, EPSC)、双脉冲易化(paired-pulse facilitation, PPF)以及短时程可塑性到长时程可塑性转变等一系列生物突触行为。在手写数据集识别任务中,该器件实现了90.2%的识别精度。在光信号感知方面,该器件在405~1050 nm的宽光谱范围内表现出优异的光电响应特性。当光信号与电信号协同输入时,该器件成功实现了布尔逻辑“与”运算,展现了在光电信息感知与逻辑处理方面的综合性能。研究为开发高效多模态的神经形态计算系统提供了新的材料与器件选择。

     

    Abstract: The ferroelectric field-effect transistor (FeFET) is considered a highly promising candidate for high-performance artificial synapses due to its non-destructive readout capability, low power consumption, and gate-voltage-controlled non-volatile modulation of channel conductance. To meet the increasing demand for multimodal information processing in neuromorphic systems, this study introduces a FeFET-based synaptic device that integrates both electrical and optical signal sensing functionalities. The device was fabricated using Hf0.5Zr0.5O2 (HZO) as the ferroelectric gate dielectric layer and photosensitive Sb2Se3 semiconductor as the conducting channel layer. Experimental results indicate that by modulating the parameters of electrical pulses applied to the gate electrode, the device effectively emulates various biological synaptic behaviors, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and the transition from short-term plasticity to long-term plasticity. In a handwritten digit recognition task, the device achieves a recognition accuracy of 90.2%. Regarding optical signal detection, the device demonstrates excellent photoresponse characteristics across a broad spectral range from 405-1050 nm. Furthermore, through the synergistic use of optical and electrical inputs, the device successfully implements Boolean logic "AND" operations, showcasing its ability to integrate both photoelectric information sensing and logical processing within a single platform. This study offers new material and device alternatives for the development of efficient, multimodal neuromorphic computing systems.

     

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