Abstract

Ferroelectric switching devices employing doped hafnium oxide (HfO2)-based thin films have expanded their range of electronic applications from densely-packed memory to brain-inspired artificial synapses. Here, we introduce a novel and distinctive three-terminal vertical device using a heterogeneous stack of hafnium-zirconium-oxide (HZO) thin film and graphene, called ferroelectric synaptic barristor (FSB), which can function as a scalable artificial synapse for energy-efficient neuromorphic computing. Electrostatic gating in the FSB can simultaneously reorient the polarization degree and the direction of HZO as well as the Schottky barrier and the trapping degree at the graphene interface. With these peculiar controlling factors, this process mimics crucial synaptic characteristics with rebound depolarization (RD), which converts an incoming inhibitory pre-spike into cell excitation. Using the RD function mediated by both ferroelectric switching and trap-mediated charge transport, the FSB exhibited a stable long-term potentiation/depression for 5000 identical pulse schemes with excellent linearity, high yield (47/48 cells), and a good state-retaining ability for 5000 s. The learning ability and energy consumption based on a single neural network were evaluated using MNIST handwritten digits and fashion patterns. The FSB with RD exhibited better accuracy (90.03% and 74.65% for handwritten digits and fashion patterns, respectively), fast and low-power learning ability than that without RD. Our FSB device can bring the advantages of conventional ferroelectric synaptic devices while mitigating their ingrained technical and operational issues.

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