Ferroelectric Gate-All-Around Transistors for 3D-Integrated Electronics and Neuromorphic Vision

ACS Nano 2026

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Authors: Wenjie Chen, Dan Tang, Chengming Luo, Shankun Xu, Qunrui Deng, Xueting Liu, Xiaojie Yi, Yan Li, Ruolin Wu, Zhen Wang, Lei Zhao, Li Li
+3 more Zhidong Pan, Yiming Sun, Nengjie Huo
DOI: 10.1021/acsnano.6c02136
Cited by: 1
References: 46

Abstract

gate, we further demonstrate its application prospects as compact edge computing devices for binary logic operations and spiking neurons on a unified hardware platform. Monolithic 3D-integrated logic circuits (inverter and NOR gate) reduce footprint by 50% versus planar CMOS, and the artificial neuron emulates leaky integrate-and-fire (LIF) behavior without additional capacitors and external reset circuitry in a conventional neuron, significantly reducing the energy consumption and hardware footprint. Implemented in a spiking neural network (SNN) for gesture recognition, this system attains 92.71% accuracy on the DVS128Gesture data set. This work establishes a paradigm for multifunctional edge intelligence processors that transcend traditional power-area trade-offs.

Fields of Study & Subjects

Advanced Memory and Neural Computing Ferroelectric and Negative Capacitance Devices Advanced Sensor and Energy Harvesting Materials

Publication details

Journal / source
ACS Nano
Publisher
American Chemical Society (ACS)
Volume
20
Issue
26
Pages
18679–18687
Publication date
10 June 2026
Language
EN