High-performance artificial neurons based on Ag/MXene/GST/Pt threshold switching memristors |
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Affiliation: | 1.The College of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;2.The National and Local Joint Engineering Laboratory of RF Integration and Micro-Assembly Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China |
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Abstract: | Threshold switching (TS) memristors can be used as artificial neurons in neuromorphic systems due to their continuous conductance modulation, scalable and energy-efficient properties. In this paper, we propose a low power artificial neuron based on the Ag/MXene/GST/Pt device with excellent TS characteristics, including a low set voltage (0.38 V) and current (200 nA), an extremely steep slope (< 0.1 mV/dec), and a relatively large off/on ratio (> 103). Besides, the characteristics of integrate and fire neurons that are indispensable for spiking neural networks have been experimentally demonstrated. Finally, its memristive mechanism is interpreted through the first-principles calculation depending on the electrochemical metallization effect. |
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Keywords: | memristors artificial neurons 2D MXene Ge2Sb2Te5 |
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