A Novel Split-Gate Ferroelectric FET for a Compact and Energy Efficient Neuron

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Neuromorphic computing—brain-inspired computing—is considered a next-generation computing architecture that can overcome problems caused by the high computing cost of modern data science. Ferroelectric FETs (FeFETs) are one of the promising candidates for hardware implementation of bio-inspired neurons. However, the conventional FeFET-based neurons require a considerable number of device components for the realization of inhibitory operation, or they need negative supply voltage, leading to high routing costs. In this letter, a novel device, named a Split-Gate (SG) FeFET, is proposed for a bio-inspired neuron. Harnessing the capacitance difference between two gates, both excitatory and inhibitory operations can be simply implemented on a single device. Furthermore, adding a “current stopper” to the SG FeFET enables energy-efficient operation of the neuron by eliminating the remanent current of the FeFET, which has been a significant drawback of conventional FeFET-based leaky integration-and-firing (LIF) emulation.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2022-08
Language
English
Article Type
Article
Citation

IEEE ELECTRON DEVICE LETTERS, v.43, no.8, pp.1375 - 1378

ISSN
0741-3106
DOI
10.1109/LED.2022.3187624
URI
http://hdl.handle.net/10203/298015
Appears in Collection
EE-Journal Papers(저널논문)
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