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

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.