Direct laser writing of graphene oxide for ultra-low power consumption memristors in reservoir computing for digital recognition
A memristor is a promising candidate of new electronic synaptic devices for neuromorphic computing. However, conventional memristors often exhibit complex device structures, cumbersome manufacturing processes, and high energy consumption. Graphene-based materials show great potential as the building...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Science Press
2022-08-01
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| Series: | National Science Open |
| Subjects: | |
| Online Access: | https://www.sciengine.com/doi/10.1360/nso/20220020 |
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| Summary: | A memristor is a promising candidate of new electronic synaptic devices for neuromorphic computing. However, conventional memristors often exhibit complex device structures, cumbersome manufacturing processes, and high energy consumption. Graphene-based materials show great potential as the building materials of memristors. With direct laser writing technology, this paper proposes a lateral memristor with reduced graphene oxide (rGO) and Pt as electrodes and graphene oxide (GO) as function material. This Pt/GO/rGO memristor with a facile lateral structure can be easily fabricated and demonstrates an ultra-low energy consumption of 200 nW. Typical synaptic behaviors are successfully emulated. Meanwhile, the Pt/GO/rGO memristor array is applied in the reservoir computing network, performing the digital recognition with a high accuracy of 95.74%. This work provides a simple and low-cost preparation method for the massive production of artificial synapses with low energy consumption, which will greatly facilitate the development of neural network computing hardware platforms. |
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| ISSN: | 2097-1168 |