@article{Tian2014, 
author = {Ye Tian and Chuangfei Guo and Shengming Guo and Taifung Yu and Qian Liu},
title = {Bivariate-continuous-tunable interface memristor based on Bi2S3 nested nano-networks},
year = {2014},
journal = {Nano Research},
volume = {7},
number = {7},
pages = {953-962},
keywords = {nanostructure, interface memristor, resistive switching, synaptic electronics},
url = {https://www.sciopen.com/article/10.1007/s12274-014-0456-5},
doi = {10.1007/s12274-014-0456-5},
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.}
}