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Temperature control of diffusive memristor hysteresis and artificial neuron spiking

journal contribution
posted on 2023-01-25, 08:30 authored by Debi PattnaikDebi Pattnaik, Yury Ushakov, Zhaoxia ZhouZhaoxia Zhou, Pavel BorisovPavel Borisov, Michael Cropper, Upul Wijayantha-Kahagala-Gamage, Alexander BalanovAlexander Balanov, Sergey SavelievSergey Saveliev

Memristive devices are promising elements for energy-efficient neuromorphic computing and future artificial intelligence systems. For diffusive memristors, resistive switching occurs because of the sequential formation and rupture of conduction filaments between device electrodes due to drift and diffusion of silver nanoparticles in the dielectric matrix. This process is governed by the applied electric voltage. Here, both in experiment and in simulations we demonstrate that varying temperature offers an efficient control of memristor states and charges transport in the device. By raising and lowering the device temperature it was shown that the memristive state can be reset, even if it cannot be done by varying the applied voltage. In addition, a change in the spiking regime was observed when the spiking was generated in the memristive circuit at a constant applied voltage, but different device temperatures. Our simulations demonstrate a good qualitative agreement with the experiments, and help to explain the effects reported.


Neuromorphic memristive circuits to simulate inhibitory and excitatory dynamics of neuron networks: from physiological similarities to deep learning

Engineering and Physical Sciences Research Council

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  • Science
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  • Physics
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  • Chemistry

Published in

Physical Review Applied


American Physical Society


AM (Accepted Manuscript)

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This paper by [add citation] was published by American Physical Society (APS) and the definitive published version is available at

Acceptance date







Dr Debi Pattnaik. Deposit date: 24 January 2023