Zinc Tin Oxide Synaptic Device for Neuromorphic Engineering
Neuromorphic computing offers parallel data processing and low energy consumption and can be useful to replace conventional von Neumann computing. Memristors are two-terminal devices with varying conductance that can be used as synaptic arrays in hardware-based neuromorphic devices. In this research...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9144610/ |
| _version_ | 1818727451172274176 |
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| author | Ji-Ho Ryu Boram Kim Fayyaz Hussain Muhammad Ismail Chandreswar Mahata Teresa Oh Muhammad Imran Kyung Kyu Min Tae-Hyeon Kim Byung-Do Yang Seongjae Cho Byung-Gook Park Yoon Kim Sungjun Kim |
| author_facet | Ji-Ho Ryu Boram Kim Fayyaz Hussain Muhammad Ismail Chandreswar Mahata Teresa Oh Muhammad Imran Kyung Kyu Min Tae-Hyeon Kim Byung-Do Yang Seongjae Cho Byung-Gook Park Yoon Kim Sungjun Kim |
| author_sort | Ji-Ho Ryu |
| collection | DOAJ |
| description | Neuromorphic computing offers parallel data processing and low energy consumption and can be useful to replace conventional von Neumann computing. Memristors are two-terminal devices with varying conductance that can be used as synaptic arrays in hardware-based neuromorphic devices. In this research, we extensively investigate the analog symmetric multi-level switching characteristics of zinc tin oxide (ZTO)-based memristor devices for neuromorphic systems. A ZTO semiconductor layer is introduced between a complementary metal-oxide-semiconductor (CMOS) compatible Ni top electrode and a highly doped poly-Si bottom electrode. A variety of bio-realistic synaptic features are demonstrated, including long-term potentiation (LTP), long-term depression (LTD), and spike timing-dependent plasticity (STDP). The Ni/ZTO/Si device in which the adjustment of the number of states in conductance is realized by applying different pulse schemes is highly suitable for hardware-based neuromorphic applications. We evaluate the pattern recognition accuracy by implementing a system-level neural network simulation with ZTO-based memristor synapses. The density of states (DOS) and charge density plots reveal that oxygen vacancies in ZTO assist in generating resistive switching in the Ni/ZTO/Si device. The proposed ZTO-based memristor composed of metal-insulator-semiconductor (MIS) structure is expected to contribute to future neuromorphic applications through further studies. |
| first_indexed | 2024-12-17T22:14:18Z |
| format | Article |
| id | doaj.art-416a5877adb2467eb29a0ef8bf3986b5 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T22:14:18Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-416a5877adb2467eb29a0ef8bf3986b52022-12-21T21:30:39ZengIEEEIEEE Access2169-35362020-01-01813067813068610.1109/ACCESS.2020.30053039144610Zinc Tin Oxide Synaptic Device for Neuromorphic EngineeringJi-Ho Ryu0Boram Kim1Fayyaz Hussain2Muhammad Ismail3Chandreswar Mahata4Teresa Oh5https://orcid.org/0000-0002-4194-381XMuhammad Imran6Kyung Kyu Min7https://orcid.org/0000-0001-6514-5348Tae-Hyeon Kim8https://orcid.org/0000-0003-0964-7583Byung-Do Yang9https://orcid.org/0000-0002-5299-1075Seongjae Cho10https://orcid.org/0000-0001-8520-718XByung-Gook Park11https://orcid.org/0000-0002-2962-2458Yoon Kim12https://orcid.org/0000-0002-4837-8411Sungjun Kim13https://orcid.org/0000-0002-9873-2474School of Electronics Engineering, Chungbuk National University, Cheongju, South KoreaSchool of Electrical and Computer Engineering, University of Seoul, Seoul, South KoreaDepartment of Physics, Materials Research Simulation Laboratory (MSRL), Bahauddin Zakariya University, Multan, PakistanSchool of Electronics Engineering, Chungbuk National University, Cheongju, South KoreaSchool of Electronics Engineering, Chungbuk National University, Cheongju, South KoreaSchool of Semiconductor Engineering, Cheongju University, Cheongju, South KoreaDepartment of Physics, Government College University Faisalabad, Faisalabad, PakistanInter-University Semiconductor Research Center (ISRC), Seoul National University, Seoul, South KoreaInter-University Semiconductor Research Center (ISRC), Seoul National University, Seoul, South KoreaSchool of Electronics Engineering, Chungbuk National University, Cheongju, South KoreaDepartment of Electronics Engineering, Gachon University, Seongnam, South KoreaInter-University Semiconductor Research Center (ISRC), Seoul National University, Seoul, South KoreaSchool of Electrical and Computer Engineering, University of Seoul, Seoul, South KoreaDivision of Electronics and Electrical Engineering, Dongguk University, Seoul, South KoreaNeuromorphic computing offers parallel data processing and low energy consumption and can be useful to replace conventional von Neumann computing. Memristors are two-terminal devices with varying conductance that can be used as synaptic arrays in hardware-based neuromorphic devices. In this research, we extensively investigate the analog symmetric multi-level switching characteristics of zinc tin oxide (ZTO)-based memristor devices for neuromorphic systems. A ZTO semiconductor layer is introduced between a complementary metal-oxide-semiconductor (CMOS) compatible Ni top electrode and a highly doped poly-Si bottom electrode. A variety of bio-realistic synaptic features are demonstrated, including long-term potentiation (LTP), long-term depression (LTD), and spike timing-dependent plasticity (STDP). The Ni/ZTO/Si device in which the adjustment of the number of states in conductance is realized by applying different pulse schemes is highly suitable for hardware-based neuromorphic applications. We evaluate the pattern recognition accuracy by implementing a system-level neural network simulation with ZTO-based memristor synapses. The density of states (DOS) and charge density plots reveal that oxygen vacancies in ZTO assist in generating resistive switching in the Ni/ZTO/Si device. The proposed ZTO-based memristor composed of metal-insulator-semiconductor (MIS) structure is expected to contribute to future neuromorphic applications through further studies.https://ieeexplore.ieee.org/document/9144610/Neuromorphicsynaptic devicezinc tin oxidedensity function theoryneural network |
| spellingShingle | Ji-Ho Ryu Boram Kim Fayyaz Hussain Muhammad Ismail Chandreswar Mahata Teresa Oh Muhammad Imran Kyung Kyu Min Tae-Hyeon Kim Byung-Do Yang Seongjae Cho Byung-Gook Park Yoon Kim Sungjun Kim Zinc Tin Oxide Synaptic Device for Neuromorphic Engineering IEEE Access Neuromorphic synaptic device zinc tin oxide density function theory neural network |
| title | Zinc Tin Oxide Synaptic Device for Neuromorphic Engineering |
| title_full | Zinc Tin Oxide Synaptic Device for Neuromorphic Engineering |
| title_fullStr | Zinc Tin Oxide Synaptic Device for Neuromorphic Engineering |
| title_full_unstemmed | Zinc Tin Oxide Synaptic Device for Neuromorphic Engineering |
| title_short | Zinc Tin Oxide Synaptic Device for Neuromorphic Engineering |
| title_sort | zinc tin oxide synaptic device for neuromorphic engineering |
| topic | Neuromorphic synaptic device zinc tin oxide density function theory neural network |
| url | https://ieeexplore.ieee.org/document/9144610/ |
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