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

Jian Li; Yiding Gu; Ting Zhang; Jiang Huang; Zhi David Chen; Chaoyue Zheng; Shibin Li

doi:10.1109/TED.2023.3274502

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

Jian Li, Yiding Gu, Ting Zhang, Jiang Huang, Zhi David Chen, Chaoyue Zheng, Shibin Li

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	3801-3807
Number of pages	7
Journal	IEEE Transactions on Electron Devices
Volume	70
Issue number	7
DOIs	https://doi.org/10.1109/TED.2023.3274502
State	Published - Jul 1 2023

Bibliographical note

Publisher Copyright:
© 1963-2012 IEEE.

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 62104028 and Grant 62174021; in part by the Creative Research Groups of the National Natural Science Foundation of Sichuan Province under Grant 2023NSFSC1973; in part by the Natural Science Foundation of Sichuan Province under Grant 2022NSFSC0899; in part by the China Postdoctoral Science Foundation under Grant 2021M700689; and in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2019A1515110438. This work was also sponsored by the Sichuan Province Key Laboratory of Display Science and Technology.

Funders	Funder number
Sichuan Province Key Laboratory of Display Science and Technology
National Natural Science Foundation of China (NSFC)	62104028, 62174021
China Postdoctoral Science Foundation	2021M700689
Natural Science Foundation of Sichuan Province	2022NSFSC0899, 2023NSFSC1973
Basic and Applied Basic Research Foundation of Guangdong Province	2019A1515110438

Keywords

Interface modification
neuromorphic computing
polyvinyl alcohol (PVA) polymer electret
self-assembled monolayer (SAM)
synaptic phototransistor

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

Access to Document

10.1109/TED.2023.3274502

Cite this

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

abstract = "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.",

keywords = "Interface modification, neuromorphic computing, polyvinyl alcohol (PVA) polymer electret, self-assembled monolayer (SAM), synaptic phototransistor",

author = "Jian Li and Yiding Gu and Ting Zhang and Jiang Huang and Chen, {Zhi David} and Chaoyue Zheng and Shibin Li",

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

Abstract

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

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