Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul 120-749, Republic of Korea.
Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea.
ACS Appl Mater Interfaces. 2020 Mar 4;12(9):10737-10745. doi: 10.1021/acsami.9b22319. Epub 2020 Feb 20.
Herein, we propose an organic double heterojunction to enable a nonvolatile step modulation of the conductance of an artificial synapse; the double heterojunction is composed of ,'-dioctyl-3,4,9,10-perylene tetracarboxylic diimide (PTCDI-C), copper phthalocyanine (CuPc), and -sexiphenyl (-6P). The carrier confinement in the CuPc region present in the double-heterojunction structure enabled the nonvolatile modulation of the postsynaptic current. The proposed organic synapse exhibited an excellent conductance change, characteristic with a nonlinearity (NL) value below 0.01 in the long-term potentiation (LTP) region. Furthermore, the NL value for long-term depression (LTD) could be reduced effectively from 45 to 3.5 by a pulse modulation technique. A simple artificial neural network (ANN) was theoretically designed using the LTP/LTD characteristic curves of such organic synapses, and then, learning and recognition tasks were performed using Modified National Institute of Standards and Technology digit images. A four-amplitude weight update method enabled considerable enhancement of the recognition rate from 53 to 70%. Although the designed ANN was based on a single-layer perceptron model, a high maximum accuracy of 75% was achieved. These newly studied techniques for synaptic devices are expected to open up new possibilities for the realization of artificial synapses based on organic double heterojunctions.
在这里,我们提出了一种有机双异质结,以实现人工突触电导的非易失性阶跃调制;该双异质结由,'-二辛基-3,4,9,10-苝四羧酸二酰亚胺(PTCDI-C)、铜酞菁(CuPc)和 -六苯基(-6P)组成。双异质结结构中 CuPc 区域的载流子限制实现了突触后电流的非易失性调制。所提出的有机突触表现出优异的电导变化特性,在长时程增强(LTP)区域的非线性(NL)值低于 0.01。此外,通过脉冲调制技术,LTD 的 NL 值可以有效地从 45 降低到 3.5。使用这种有机突触的 LTP/LTD 特征曲线,理论上设计了一个简单的人工神经网络(ANN),然后使用修改后的国家标准与技术研究院数字图像执行学习和识别任务。四幅度权重更新方法可将识别率从 53%提高到 70%。尽管设计的 ANN 基于单层感知器模型,但仍实现了 75%的最高精度。这些新研究的突触器件技术有望为基于有机双异质结的人工突触的实现开辟新的可能性。