A Self-Assembled Monolayer Modification to Enhance the Performance of PVA Polymer Electret-Based Organic Synaptic Phototransistor

神经形态工程学 材料科学 光电子学 感知器 计算机科学 纳米技术 人工神经网络 人工智能
作者
Jian Li,Yiding Gu,Ting Zhang,Jiang Huang,Zhi Chen,Chaoyue Zheng,Shibin Li
出处
期刊:IEEE Transactions on Electron Devices [Institute of Electrical and Electronics Engineers]
卷期号:70 (7): 3801-3807 被引量:12
标识
DOI:10.1109/ted.2023.3274502
摘要

The organic synaptic phototransistor (OSPT) is extensively considered to be a key building block of next-generation neuromorphic computing due to its advantages of computing in memory and large-scale parallel processing operation. However, the effective charge transport of the organic semiconductor layer still remains challenging in the field of OSPT. Here, a self-assembled monolayer (SAM) of octadecyltrichlorosilane (ODTS) is proposed to tailor the surface property between the pentacene channel layer and the biocompatible polyvinyl alcohol (PVA) electret. Both the hole mobility and the ON– OFF ratio of OSPT are notably improved by an order of magnitude, which finally enhances the corresponding photoelectric characteristics. The OSPT shows a large memory window (40 V) with the assistance of the optical erase process. Besides, several basic synaptic behaviors are effectively implemented presenting a better modulation of synaptic weight. Furthermore, the OSPT is applied in recognizing digital images based on the single-layer perceptron (SLP) artificial neural network (ANN) and three-layer perceptron (TLP) ANN, and the total average recognition accuracy improves from 82.6% to 87.5%. Our research provides a facile interface modification strategy for designing high-performance PVA-based OSPT and a potential synaptic application for neuromorphic computing in near future.
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