Abstract
An electronic synapse (e-synapse) based on memristive switching is a promising electronic element that emulates a biological synapse to realize neuromorphic computing. However, the complex resistive switching process it relies on hampers the reproducibility of its performance. Thus, achievement of a reproducible electronic synapse with a high rate of finished products has become a significant challenge in the development of an artificial intelligent circuit. Here, we demonstrate an ultrathin e-synapse having high yield (>95%), minimal performance variation, and extremely low power consumption based on an Al2O3/graphene quantum dots/Al2O3 sandwich structure that was fabricated using atomic layer deposition. The e-synapse showed both high device-to-device and cycle-to-cycle reproducibility with high stability, endurance, and switching uniformity, because the essential synaptic behaviors could be observed. This implementation of an e-synapse with an Al2O3/graphene quantum dots/Al2O3 structure should intensify motivation for engineering e-synapses for neuromorphic computing.
Highlights
Differing from computing systems based on the von Neumann architecture, nervous systems of human brain process information based on distributed, parallel, and event-driven computation[1,2,3,4]
The ultrathin Al2O3 film was first deposited on indium tin oxide (ITO)coated glass using atomic layer deposition (ALD)
Both the accurately controlled thickness of the Al2O3 film, which is due to the use of ALD, and the well-dispersed graphene quantum dots (GQDs) contribute to the high yield and high device-to-device uniformity of our e-synapses, which will be discussed later
Summary
Differing from computing systems based on the von Neumann architecture, nervous systems of human brain process information based on distributed, parallel, and event-driven computation[1,2,3,4]. Biological nervous systems exhibit advantages of fault tolerance and power efficiency for real-world problems involving visual information, audio recognition, and movement control. The idea of building an electronic system that can mimic part of the function of a biological nervous system is currently attracting significant interest[5]. Two-terminal memristive devices are promising candidates to act as a compact electronic element and have been widely demonstrated in the pursuit of certain synaptic functions[8,9,10]. E-synapses usually suffer from unavoidable temporal (cycle-to-cycle) and spatial (device-to-device) variations due to their intrinsic working mechanism and structure interaction. These variations exist because most two-terminal e-synapses
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