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Yoon, Tae-Sik
Nano Semiconductor Research Lab.
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Enhanced Nonvolatile Electrochemical Random-Access Memory and Artificial Synapse Characteristics through Oxygen Ion-Exchange Engineering in an Atomic-Layer-Deposited HfO2-x Gate Insulator and a Zinc Oxide Channel Layer

Author(s)
Han, JiminNoh, TaeyunJeong, BoyoungChung, Peter HayoungPark, GaramLee, Min-HyunKim, YuminYoon, Tae-Sik
Issued Date
2025-06
DOI
10.1021/acsami.5c04214
URI
https://scholarworks.unist.ac.kr/handle/201301/87423
Citation
ACS APPLIED MATERIALS & INTERFACES, v.17, no.25, pp.36866 - 36879
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 >10(4) 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 >10(4) 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
Publisher
AMER CHEMICAL SOC
ISSN
1944-8244
Keyword (Author)
artificial synapseoxygenion-based electrochemical random-access memoryoxygen ionexchange, thin-film transistor, atomic layer depositionnonvolatile memory
Keyword
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