Dynamic Instability and Time Domain Response of a Model Halide Perovskite Memristor for Artificial Neurons
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Dynamic Instability and Time Domain Response of a Model Halide Perovskite Memristor for Artificial NeuronsData de publicació
2022-04-22Editor
American Chemical SocietyISSN
1948-7185Cita bibliogràfica
Dynamic Instability and Time Domain Response of a Model Halide Perovskite Memristor for Artificial Neurons Juan Bisquert and Antonio Guerrero The Journal of Physical Chemistry Letters 2022 13 (17), 3789-3795 DOI: 10.1021/acs.jpclett.2c00790Tipus de document
info:eu-repo/semantics/articleVersió
info:eu-repo/semantics/acceptedVersionParaules clau / Matèries
Resum
Memristors are candidate devices for constructing artificial neurons, synapses, and computational networks for brainlike information processing and sensory-motor autonomous systems. However, the dynamics of natural ... [+]
Memristors are candidate devices for constructing artificial neurons, synapses, and computational networks for brainlike information processing and sensory-motor autonomous systems. However, the dynamics of natural neurons and synapses are challenging and cannot be well reproduced with standard electronic components. Halide perovskite memristors operate by mixed ionic–electronic properties that may lead to replicate the live computation elements. Here we explore the dynamical behavior of a halide perovskite memristor model to evaluate the response to a step perturbation and the self-sustained oscillations that produce analog neuron spiking. As the system contains a capacitor and a voltage-dependent chemical inductor, it can mimic an action potential in response to a square current pulse. Furthermore, we discover a property that cannot occur in the standard two-dimensional model systems: a three-dimensional model shows a dynamical instability that produces a spiking regime without the need for an intrinsic negative resistance. These results open a new pathway to create spiking neurons without the support of electronic circuits. [-]
Publicat a
J. Phys. Chem. Lett. 2022, 13, 17, 3789–3795Dades relacionades
https://pubs.acs.org/doi/10.1021/acs.jpclett.2c00790Entitat finançadora
Generalitat Valenciana
Codi del projecte o subvenció
PROMETEU/2020/028
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Copyright © 2022 American Chemical Society
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info:eu-repo/semantics/openAccess
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