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Published on: May 13, 2020
Enhanced Nonvolatile Electrochemical Random-Access Memory and Artificial Synapse Characteristics through Oxygen
Jimin Han1, Taeyun Noh2, Boyoung Jeong2
1Department of Materials Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.
Abstract:
Enhanced nonvolatile memory and artificial synapse characteristics are achieved in oxygen ion-based ECRAM consisting of a low-temperature atomic layer-deposited (ALD) oxygen-deficient hafnium oxide (HfO2-x) ion-exchange layer and zinc oxide (ZnO) channel layer. The drain current modulation of the device reaches a few orders of magnitude upon application of positive programming and negative erasing gate bias. Also, the device exhibits nonvolatile retention of modulated current up to >104 higher than the initial value for 24 h. Nonvolatile modulation of channel conductance results from oxygen ion exchange between the HfO2-x ion-exchange layer and ZnO channel layer in the nanometer scale, facilitated by using oxygen-deficient HfO2-x deposited at a low temperature (LT-HfO2-x) and ZnO layers as well as the use of UV/ozone treatment on LT-HfO2-x. Additionally, it presents various synaptic characteristics including analog, linear, and symmetric potentiation and depression behaviors upon repeating >104 pulses, paired-pulse facilitation depending on the pulse number, amplitude, and width, and short-term and long-term plasticity. These synapse characteristics are benchmarked to have MNIST pattern recognition accuracy over 93% using a CrossSim simulator. These enhanced nonvolatile memory and artificial synaptic characteristics verify the potential application of the proposed ECRAM for high-density stand-alone nonvolatile memory and artificial synapses for brain-inspired neuromorphic computing systems.
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