<p>Nanofluidic memristors based on nanoconfined aqueous salt electrolytes exhibit low power consumption and biomimetic neural activity, serving as key components for neuromorphic systems. Two-capacitor neuronal circuits are fundamental to exploring biophysical mechanisms and brain-inspired devices. In this paper, we construct a single-membrane nanofluidic memristive neuronal circuit by paralleling a nanofluidic memristor with a capacitor. A bi-membrane homogeneous model consisting of two nanofluidic memristive neuronal circuits achieves complete synchronization under a suitably selected resistive coupling strength. Furthermore, a bi-membrane heterogeneous model consisting of a nanofluidic memristive neuron circuit and a Fitzhugh-Nagumo (FHN) neuron circuit can exhibit phase synchronization at an appropriate coupling strength. Finally, a neuronal network composed of bi-membrane heterogeneous nanofluidic memristors is established. Numerical simulations indicate that the network exhibits rich spatiotemporal dynamical behaviors as the resistive coupling gain increases, and can achieve synchronization under optimized coupling strength. The results suggest that the nanofluidic devices are expected to develop novel neuromorphic circuits and related brain-inspired devices.</p>

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Synchronization of the bi-membrane nanofluidic memristive neuron circuits under resistive coupling

  • Huimin Qi,
  • Fengjun Li,
  • Fuqiang Wu,
  • Xinlei An

摘要

Nanofluidic memristors based on nanoconfined aqueous salt electrolytes exhibit low power consumption and biomimetic neural activity, serving as key components for neuromorphic systems. Two-capacitor neuronal circuits are fundamental to exploring biophysical mechanisms and brain-inspired devices. In this paper, we construct a single-membrane nanofluidic memristive neuronal circuit by paralleling a nanofluidic memristor with a capacitor. A bi-membrane homogeneous model consisting of two nanofluidic memristive neuronal circuits achieves complete synchronization under a suitably selected resistive coupling strength. Furthermore, a bi-membrane heterogeneous model consisting of a nanofluidic memristive neuron circuit and a Fitzhugh-Nagumo (FHN) neuron circuit can exhibit phase synchronization at an appropriate coupling strength. Finally, a neuronal network composed of bi-membrane heterogeneous nanofluidic memristors is established. Numerical simulations indicate that the network exhibits rich spatiotemporal dynamical behaviors as the resistive coupling gain increases, and can achieve synchronization under optimized coupling strength. The results suggest that the nanofluidic devices are expected to develop novel neuromorphic circuits and related brain-inspired devices.