Implementation of an artificial neuron circuit model based on high speed AlN stacked threshold switching devices

Abstract

There has been a notable surge of interest in neuromorphic network computation, particularly concerning both non-volatile and volatile threshold devices. In this research, we have developed a multi-layer thin film architecture consisting of Al/AlN/Ag/AlN/Pt, which functions as a threshold switching (TS) device characterized by rapid switching speeds of 50 ns and minimal leakage current. We have effectively demonstrated biological neuron-like behaviors, such as threshold-driven spikes, all-or-nothing spikes, intensity-modulated frequency response, and frequency-modulated frequency response, through the deployment of a leaky integrate-and-fire (LIF) artificial neuron circuit, which surpasses earlier neuronal models. The resistance switching mechanism of the device is likely due to the migration of nitrogen vacancies in conjunction with silver filaments. This threshold switching device shows significant potential for applications in next-generation artificial neural networks.

Graphical abstract

Keywords

volatile memristor / artificial neurons / AlN / high speed switching

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Declarations

The authors declare that they have no competing interests and there are no conflicts.

Data availability

The data that support the findings of this study are available within the article.

Acknowledgements

This work was financially supported by the National Natural Science Foundation Joint Regional Innovation Development Project (Grant No. U23A20365), the National R&D Plan “Nano Frontier” Key Special Project (Grant No. 2021YFA1200502), the Cultivation Projects of National Major R&D Project (Grant No. 92164109), the National Natural Science Foundation of China (Grant Nos. 61874158, 62004056, and 62104058), the Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences (Grant No. XDB44000000-7), Hebei Basic Research Special Key Project (Grant No. F2021201045), the Support Program for the Top Young Talents of Hebei Province (Grant No. 70280011807), the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province (Grant No. SLRC2019018), the Interdisciplinary Research Program of Natural Science of Hebei University (No. DXK202101), the Institute of Life Sciences and Green Development (No. 521100311), the Natural Science Foundation of Hebei Province (Nos. F2022201054 and F2021201022), the Outstanding Young Scientific Research and Innovation Team of Hebei University (Grant No. 605020521001), the Special Support Funds for National High Level Talents (Grant No. 041500120001), the Advanced Talents Incubation Program of the Hebei University (Grant Nos. 521000981426, 521100221071, and 521000981363), High-level Talent Funding Program of Hebei Province(Grant No. B20231003), Yanzhao Young Science Project (Grant No. F2023201076), Science and Technology Project of Hebei Education Department (Grant Nos. QN2020178 and QN2021026), and Baoding Science and Technology Plan Project (Grant Nos. 2172P011 and 2272P014).

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