氯仿改性聚(3-己基噻吩)有机电化学晶体管及其神经突触功能模仿  

Poly(3-hexylthiophene)Based Organic Electrochemical Transistor Optimized with Chloroform and Its Synaptic Function Emulation

作　　者：蒋倩 孙翠 郭哲成 刘雪蓉 孙启浩 段吉鹏 朱小健[1] 李润伟[1] JIANG Qian;SUN Cui;GUO Zhecheng;LIU Xuerong;SUN Qihao;DUAN Jipeng;ZHU Xiaojian;LI Runwei(Ningbo Institute of Materials Technology and Engineering,Chinese Academy of Sciences,Ningbo 315201,Zhejiang,China;University of Chinese Academy of Sciences,Beijing 100049,China;Faculty of Electrical Engineering and Computer Science,Ningbo University,Ningbo 315211,Zhejiang,China)

机构地区：[1]中国科学院宁波材料技术与工程研究所,浙江宁波315201 [2]中国科学院大学,北京100049 [3]宁波大学信息科学与工程学院,浙江宁波315211

出　　处：《功能高分子学报》2023年第4期358-364,I0003,共8页Journal of Functional Polymers

基　　金：国家重点研发计划项目(2021YFA1202600);国家自然科学基金(92064011、62174164、61974179、U22A2075);中国科学院青年创新促进会项目(2020297);浙江省自然科学基金项目(LR23E020001);宁波市自然科学基金(202003N4029)。

摘　　要：通过旋涂法制备了有机半导体聚(3-己基噻吩)(P3HT)薄膜,在二氯苯溶剂中引入氯仿对P3HT薄膜进行改性。以改性的P3HT薄膜作为沟道层,以离子凝胶作为电解质层制备了有机电化学晶体管(OECT)。通过原子力显微镜、紫外-可见光谱和拉曼光谱探究了氯仿改性对P3HT薄膜粗糙度和分子有序度的影响,采用半导体参数仪研究了氯仿改性对材料电学性能的影响。实验结果表明,氯仿改性降低了P3HT薄膜的粗糙度,提高了分子排列的有序度。氯仿改性后的OECT在−0.5 V和−1.0 V的电脉冲刺激下呈现显著的神经突触兴奋脉冲电流响应特性,相比于未改性的器件,电导调控幅值分别增加了约2倍和16倍,且延长了其保持特性。基于氯仿改性OECT的人工神经突触网络将MNIST手写数字识别准确率从73.6%提高至92.7%,有望在高性能神经形态计算方面发挥重要作用。The organic semiconductor poly(3-hexylthiophene)(P3HT)film prepared by the spin-coating method is optimized by dichlorobenzene(o-DCB)solvent added with chloroform(CF).The organic electrochemical transistor(OECT)is obtained using the optimized P3HT film as the channel layer and ion gel as the electrolyte layer.The effect of CF on the roughness and molecular order of P3HT film is inverstigated by atomic force microscopy,UV-visible spectroscopy and Raman spectroscopy.The effect of CF optimization on the electrical properties of the material is studied with a semiconductor parametric analyzer.Results show that CF introduction reduces the roughness of P3HT film and improves the order degree of P3HT molecular arrangement.The CF-optimized OECT exhibits significant synaptic excitatory pulse current characteristics under the stimulation of−0.5 V and−1.0 V electric pulses.Compared to the device without CF optimization,the amplitude of conductance regulation is increased by about twice and 16 times,respectively,along with the improved retention performance.The simulation results show that the accuracy of the neural network based on the CF-optimized OECT in recognizing MNIST(Modified National Institute of Standards and Technology)handwritten digits is increased from 73.6%to 92.7%.This device is expected to play an important role in large-scale neuromorphic computing applications.

关 键 词：有机电化学晶体管 P3HT 突触可塑性 人工神经网络 神经形态计算 

分 类 号：TN389[电子电信—物理电子学]