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      • Record: found
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      Multi-Level Analog Resistive Switching Characteristics in Tri-Layer HfO 2/Al 2O 3/HfO 2 Based Memristor on ITO Electrode

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          Abstract

          Atomic layer deposited (ALD) HfO 2/Al 2O 3/HfO 2 tri-layer resistive random access memory (RRAM) structure has been studied with a transparent indium tin oxide (ITO) transparent electrode. Highly stable and reliable multilevel conductance can be controlled by the set current compliance and reset stop voltage in bipolar resistive switching. Improved gradual resistive switching was achieved because of the interdiffusion in the HfO 2/Al 2O 3 interface where tri-valent Al incorporates with HfO 2 and produces HfAlO. The uniformity in bipolar resistive switching with I on/I off ratio (>10) and excellent endurance up to >10 3 cycles was achieved. Multilevel conductance levels in potentiation/depression were realized with constant amplitude pulse train and increasing pulse amplitude. Thus, tri-layer structure-based RRAM can be a potential candidate for the synaptic device in neuromorphic computing.

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          Redox-Based Resistive Switching Memories - Nanoionic Mechanisms, Prospects, and Challenges

          Rainer Waser, Regina Dittmann, Georgi Staikov … (2009)
          Article 0 comments Cited 305 times – based on 0 reviews     Review now
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            A low energy oxide-based electronic synaptic device for neuromorphic visual systems with tolerance to device variation.

            Carlos K. H. Wong, Jinfeng Kang, Bin Gao … (2013)
            Neuromorphic computing is an emerging computing paradigm beyond the conventional digital von Neumann computation. An oxide-based resistive switching memory is engineered to emulate synaptic devices. At the device level, the gradual resistance modulation is characterized by hundreds of identical pulses, achieving a low energy consumption of less than 1 pJ per spike. Furthermore, a stochastic compact model is developed to quantify the device switching dynamics and variation. At system level, the performance of an artificial visual system on the image orientation or edge detection with 16 348 oxide-based synaptic devices is simulated, successfully demonstrating a key feature of neuromorphic computing: tolerance to device variation. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
            Article 0 comments Cited 144 times – based on 0 reviews     Review now
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              Activity-Dependent Synaptic Plasticity of a Chalcogenide Electronic Synapse for Neuromorphic Systems

              Yi Li, Yingpeng Zhong, Jinjian Zhang … (2014)
              Nanoscale inorganic electronic synapses or synaptic devices, which are capable of emulating the functions of biological synapses of brain neuronal systems, are regarded as the basic building blocks for beyond-Von Neumann computing architecture, combining information storage and processing. Here, we demonstrate a Ag/AgInSbTe/Ag structure for chalcogenide memristor-based electronic synapses. The memristive characteristics with reproducible gradual resistance tuning are utilised to mimic the activity-dependent synaptic plasticity that serves as the basis of memory and learning. Bidirectional long-term Hebbian plasticity modulation is implemented by the coactivity of pre- and postsynaptic spikes, and the sign and degree are affected by assorted factors including the temporal difference, spike rate and voltage. Moreover, synaptic saturation is observed to be an adjustment of Hebbian rules to stabilise the growth of synaptic weights. Our results may contribute to the development of highly functional plastic electronic synapses and the further construction of next-generation parallel neuromorphic computing architecture.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nanomaterials (Basel)
                Journal ID (iso-abbrev): Nanomaterials (Basel)
                Journal ID (publisher-id): nanomaterials
                Title: Nanomaterials
                Publisher: MDPI
                ISSN (Electronic): 2079-4991
                Publication date (Electronic): 20 October 2020
                Publication date Collection: October 2020
                Volume: 10
                Issue: 10
                Electronic Location Identifier: 2069
                Affiliations
                [1 ]School of Electronics Engineering, Chungbuk National University, Cheongju 28644, Korea; chandreswar@ 123456gmail.com
                [2 ]Department of Electronics Engineering, Korea National University of Transportation, Chungju-si 27469, Korea
                [3 ]Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Korea
                Author notes
                [* ]Correspondence: mgkang@ 123456ut.ac.kr (M.K.); sungjun@ 123456dongguk.edu (S.K.)
                Author information
                https://orcid.org/0000-0003-4132-0038
                Article
                Publisher ID: nanomaterials-10-02069
                DOI: 10.3390/nano10102069
                PMC ID: 7589730
                PubMed ID: 33092042
                SO-VID: caffb50a-9df5-4828-bad0-ffbc4afeb39a
                Copyright © © 2020 by the authors.
                License:

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                Date received : 06 September 2020
                Date accepted : 16 October 2020
                Categories
                Subject: Article

                Keywords: hfo2/al2o3/hfo2 tri-layer rram,transparent electrode,multilevel conductance,synaptic properties
                Data availability:
                Keywords: hfo2/al2o3/hfo2 tri-layer rram, transparent electrode, multilevel conductance, synaptic properties

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