Ultralow‐Power Vertical Transistors for Multilevel Decoding Modes

Authors: Qing Zhang, Enlong Li, Yongshuai Wang, Changsong Gao, Congyong Wang, Lin Li, Dechao Geng, Huipeng Chen, Wei Chen, Wenping Hu

Published: 2022-11-07

DOI: 10.1002/adma.202208600

Source: Full article


Abstract

AbstractOrganic field‐effect transistors with parallel transmission and learning functions are of interest in the development of brain‐inspired neuromorphic computing. However, the poor performance and high power consumption are the two main issues limiting their practical applications. Herein, an ultralow‐power vertical transistor is demonstrated based on transition‐metal carbides/nitrides (MXene) and organic single crystal. The transistor exhibits a high JON of 16.6 mA cm−2 and a high JON/JOFF ratio of 9.12 × 105 under an ultralow working voltage of −1 mV. Furthermore, it can successfully simulate the functions of biological synapse under electrical modulation along with consuming only 8.7 aJ of power per spike. It also permits multilevel information decoding modes with a significant gap between the readable time of professionals and nonprofessionals, producing a high signal‐to‐noise ratio up to 114.15 dB. This work encourages the use of vertical transistors and organic single crystal in decoding information and advances the development of low‐power neuromorphic systems.