Proton-assisted redox-based three-terminal memristor for synaptic device applications
Emerging technologies, i.e., spintronics, 2D materials, and memristive devices, have been widely investigated as the building block of neuromorphic computing systems. Three-terminal memristor (3TM) is specifically designed to mitigate the challenges encountered by its two-terminal counterpart as it...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Online Access: | https://hdl.handle.net/10356/171394 |
| _version_ | 1824456291930603520 |
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| author | Liu, Lingli Dananjaya, Putu Andhita Chee, Mun Yin Lim, Gerard Joseph Lee, Calvin Xiu Xian Lew, Wen Siang |
| author2 | School of Physical and Mathematical Sciences |
| author_facet | School of Physical and Mathematical Sciences Liu, Lingli Dananjaya, Putu Andhita Chee, Mun Yin Lim, Gerard Joseph Lee, Calvin Xiu Xian Lew, Wen Siang |
| author_sort | Liu, Lingli |
| collection | NTU |
| description | Emerging technologies, i.e., spintronics, 2D materials, and memristive devices, have been widely investigated as the building block of neuromorphic computing systems. Three-terminal memristor (3TM) is specifically designed to mitigate the challenges encountered by its two-terminal counterpart as it can concurrently execute signal transmission and memory operations. In this work, we present a complementary metal-oxide-semiconductor-compatible 3TM with highly linear weight update characteristics and a dynamic range of ∼15. The switching mechanism is governed by the migration of oxygen ions and protons in and out of the channel under an external gate electric field. The involvement of the protonic defects in the electrochemical reactions is proposed based on the bipolar pulse trains required to initiate the oxidation process and the device electrical characteristics under different humidity levels. For the synaptic operation, an excellent endurance performance with over 256k synaptic weight updates was demonstrated while maintaining a stable dynamic range. Additionally, the synaptic performance of the 3TM is simulated and implemented into a four-layer neural network (NN) model, achieving an accuracy of ∼92% in MNIST handwritten digit recognition. With such desirable conductance modulation characteristics, our proposed 3T-memristor is a promising synaptic device candidate to realize the hardware implementation of the artificial NN. |
| first_indexed | 2025-02-19T03:51:47Z |
| format | Journal Article |
| id | ntu-10356/171394 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:51:47Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1713942023-10-24T02:12:41Z Proton-assisted redox-based three-terminal memristor for synaptic device applications Liu, Lingli Dananjaya, Putu Andhita Chee, Mun Yin Lim, Gerard Joseph Lee, Calvin Xiu Xian Lew, Wen Siang School of Physical and Mathematical Sciences Science::Physics Neuromorphic Computing Three-terminal Emerging technologies, i.e., spintronics, 2D materials, and memristive devices, have been widely investigated as the building block of neuromorphic computing systems. Three-terminal memristor (3TM) is specifically designed to mitigate the challenges encountered by its two-terminal counterpart as it can concurrently execute signal transmission and memory operations. In this work, we present a complementary metal-oxide-semiconductor-compatible 3TM with highly linear weight update characteristics and a dynamic range of ∼15. The switching mechanism is governed by the migration of oxygen ions and protons in and out of the channel under an external gate electric field. The involvement of the protonic defects in the electrochemical reactions is proposed based on the bipolar pulse trains required to initiate the oxidation process and the device electrical characteristics under different humidity levels. For the synaptic operation, an excellent endurance performance with over 256k synaptic weight updates was demonstrated while maintaining a stable dynamic range. Additionally, the synaptic performance of the 3TM is simulated and implemented into a four-layer neural network (NN) model, achieving an accuracy of ∼92% in MNIST handwritten digit recognition. With such desirable conductance modulation characteristics, our proposed 3T-memristor is a promising synaptic device candidate to realize the hardware implementation of the artificial NN. Agency for Science, Technology and Research (A*STAR) This work was supported by a RIE2020 ASTAR AME IAF-ICP grant (no. I1801E0030). 2023-10-24T02:12:41Z 2023-10-24T02:12:41Z 2023 Journal Article Liu, L., Dananjaya, P. A., Chee, M. Y., Lim, G. J., Lee, C. X. X. & Lew, W. S. (2023). Proton-assisted redox-based three-terminal memristor for synaptic device applications. ACS Applied Materials and Interfaces, 15(24), 29287-29296. https://dx.doi.org/10.1021/acsami.3c03974 1944-8244 https://hdl.handle.net/10356/171394 10.1021/acsami.3c03974 37303194 2-s2.0-85163792809 24 15 29287 29296 en I1801E0030 ACS Applied Materials and Interfaces © 2023 American Chemical Society. All rights reserved. |
| spellingShingle | Science::Physics Neuromorphic Computing Three-terminal Liu, Lingli Dananjaya, Putu Andhita Chee, Mun Yin Lim, Gerard Joseph Lee, Calvin Xiu Xian Lew, Wen Siang Proton-assisted redox-based three-terminal memristor for synaptic device applications |
| title | Proton-assisted redox-based three-terminal memristor for synaptic device applications |
| title_full | Proton-assisted redox-based three-terminal memristor for synaptic device applications |
| title_fullStr | Proton-assisted redox-based three-terminal memristor for synaptic device applications |
| title_full_unstemmed | Proton-assisted redox-based three-terminal memristor for synaptic device applications |
| title_short | Proton-assisted redox-based three-terminal memristor for synaptic device applications |
| title_sort | proton assisted redox based three terminal memristor for synaptic device applications |
| topic | Science::Physics Neuromorphic Computing Three-terminal |
| url | https://hdl.handle.net/10356/171394 |
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