Cite this article:
Xiao-Juan Lian, Jin-Ke Fu, Zhi-Xuan Gao, Shi-Pu Gu, Lei Wang. High-performance artificial neurons based on Ag/MXene/GST/Pt threshold switching memristorsJ. Chin. Phys. B, 2023, 32(1): 017304.
| Xiao-Juan Lian, Jin-Ke Fu, Zhi-Xuan Gao, Shi-Pu Gu, Lei Wang. High-performance artificial neurons based on Ag/MXene/GST/Pt threshold switching memristorsJ. Chin. Phys. B, 2023, 32(1): 017304. |
High-performance artificial neurons based on Ag/MXene/GST/Pt threshold switching memristors
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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 (> 10 3). 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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