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Bivariate-continuous-tunable interface memristor based on Bi2S3 nested nano-networks
Qian Liu1,4(
)
)Abstract
A memristor that can emulate biological synapses is a promising basic-processing unit in neural-network computation. Here we propose a new-conceptual memristor based on a memoristive interface composed of two types of non-memristive materials, successfully realizing continuously tunable resistance controlled by both voltage (current) and applied time of a single pulse with a swift response comparable with synapses. The brain-like memorizing capability of the memristor is demonstrated. The memoristive mechanism in the interface is thought to be dominated by a Schottky barrier tuned by the capture/release of the carriers in interface traps with dispersive energy.
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Pages 953-962
Cite this article:
Tian Y, Guo C, Guo S, et al. Bivariate-continuous-tunable interface memristor based on Bi2S3 nested nano-networks. Nano Research, 2014, 7(7): 953-962. https://doi.org/10.1007/s12274-014-0456-5
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