Reconfigurable Dual‐Gate Ferroelectric Field‐Effect Transistors Based on Semiconducting Polymer for Logic Operations and Synaptic Applications

• DOI: 10.1002/smm2.70003
• Publication Date: 2025-03-11T21:00:05Z
• Authors: Yuqing Ding; Xinzhao Xu; Yangjiang Wu; Haoqin Zhang; Lin Shao; Zhihui Wang; Hailing Zhang; Yan Zhao; Yunqi Liu

ABSTRACTOrganic field‐effect transistors (OFETs), with their potential for low‐cost manufacturing and compatibility with flexible substrates, have emerged as an indispensable element in next‐generation electronics. However, the existing OFETs are significantly hindered by their lack of reconfigurability and multifunctionality for application in complex electronic systems. To address these limitations, we propose a novel design strategy to develop a dual‐gate organic field‐effect transistor (DG‐OFET), primarily featuring a synergistic combination of interface charge trapping and the nonvolatile nature of ferroelectric polarization, which realizes the multifunctional integration within a single platform. Specifically, the DG‐OFET can be utilized as synaptic devices that can successfully perform both short‐term and long‐term synaptic plasticity by manipulating the input gate of artificial pulse voltages, depending on the switching mechanism between bottom‐gate controlled electrostatic doping and top‐gate induced ferroelectric polarization. Besides, the presynaptic spike applied to a specific gate electrode can trigger the excitatory and inhibitory postsynaptic current response. The potentiation and depression of synaptic weight are mimicked by consecutive positive and negative spikes, respectively. The dual‐gate coupling strategy further expands its functionality towards simulating the operation of logic gates. By modulating the combination of dual‐gate input signals, the channel conductivity can analogously perform a family of elementary Boolean logic operations, including AND, OR, NAND, NOR, XOR, and XNOR. These results highlight the electronic reconfigurability of DG‐OFET and tremendous potential for applications in energy‐efficient neuromorphic computing networks and organic circuits, thus providing a versatile strategy for the development of advanced and efficient multifunctional integration.