A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions
Bionic artificial synapses based on 2D transition metal dichalcogenides are comparable to biological synapses due to the unique properties, which are important for building brain-like computing to break the energy and data throughput limit of the von Neumann architecture. In this work, a two-termina...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Published: |
Elsevier
2022
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| Online Access: | http://psasir.upm.edu.my/id/eprint/100170/ |
| _version_ | 1848863252202651648 |
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| author | Yu, T. Zhao, Z. Jiang, H. Weng, Z. Fang, Y. Liu, C. Lei, W. Shafe, S.B. Mohtar, M.N. |
| author_facet | Yu, T. Zhao, Z. Jiang, H. Weng, Z. Fang, Y. Liu, C. Lei, W. Shafe, S.B. Mohtar, M.N. |
| author_sort | Yu, T. |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Bionic artificial synapses based on 2D transition metal dichalcogenides are comparable to biological synapses due to the unique properties, which are important for building brain-like computing to break the energy and data throughput limit of the von Neumann architecture. In this work, a two-terminal memristor with vertical structure was fabricated by using 2H–MoTe2 nanosheet dispersion. The fabricated memristor based on the Cu/MoTe2/Si structure not only exhibits the stable bipolar nonvolatile resistive switching behavior but also implements the centralized distribution of threshold voltage, and the SET/RESET power can be as low as 0.86 μW/93 nW. Impressively, classical synaptic functions including long-term potentiation/long-term depression, excitatory postsynaptic currents, spike-timing-dependent plasticity, and paired-pulse facilitation were mimicked, which attribute to the formation and rupturing of Cu conductive filaments. Interestingly, the simple arithmetic functions can be operated. Therefore, this work provides a new solution for the development of synaptic devices and neural computing research in the future. |
| first_indexed | 2025-11-15T13:29:58Z |
| format | Article |
| id | upm-100170 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T13:29:58Z |
| publishDate | 2022 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1001702024-07-11T07:45:49Z http://psasir.upm.edu.my/id/eprint/100170/ A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions Yu, T. Zhao, Z. Jiang, H. Weng, Z. Fang, Y. Liu, C. Lei, W. Shafe, S.B. Mohtar, M.N. Bionic artificial synapses based on 2D transition metal dichalcogenides are comparable to biological synapses due to the unique properties, which are important for building brain-like computing to break the energy and data throughput limit of the von Neumann architecture. In this work, a two-terminal memristor with vertical structure was fabricated by using 2H–MoTe2 nanosheet dispersion. The fabricated memristor based on the Cu/MoTe2/Si structure not only exhibits the stable bipolar nonvolatile resistive switching behavior but also implements the centralized distribution of threshold voltage, and the SET/RESET power can be as low as 0.86 μW/93 nW. Impressively, classical synaptic functions including long-term potentiation/long-term depression, excitatory postsynaptic currents, spike-timing-dependent plasticity, and paired-pulse facilitation were mimicked, which attribute to the formation and rupturing of Cu conductive filaments. Interestingly, the simple arithmetic functions can be operated. Therefore, this work provides a new solution for the development of synaptic devices and neural computing research in the future. Elsevier 2022-08 Article PeerReviewed Yu, T. and Zhao, Z. and Jiang, H. and Weng, Z. and Fang, Y. and Liu, C. and Lei, W. and Shafe, S.B. and Mohtar, M.N. (2022) A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions. Materials Today Nano, 19. art. no. 100233. pp. 1-7. ISSN 2588-8420 https://www.sciencedirect.com/science/article/pii/S258884202200061X 10.1016/j.mtnano.2022.100233 |
| spellingShingle | Yu, T. Zhao, Z. Jiang, H. Weng, Z. Fang, Y. Liu, C. Lei, W. Shafe, S.B. Mohtar, M.N. A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions |
| title | A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions |
| title_full | A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions |
| title_fullStr | A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions |
| title_full_unstemmed | A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions |
| title_short | A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions |
| title_sort | low-power memristor based on 2h–mote2 nanosheets with synaptic plasticity and arithmetic functions |
| url | http://psasir.upm.edu.my/id/eprint/100170/ http://psasir.upm.edu.my/id/eprint/100170/ http://psasir.upm.edu.my/id/eprint/100170/ |