Dynamic Instability and Time Domain Response of a Model Halide Perovskite Memristor for Artificial Neurons.
J Phys Chem Lett
; 13(17): 3789-3795, 2022 May 05.
Article
em En
| MEDLINE
| ID: mdl-35451841
ABSTRACT
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Redes Neurais de Computação
/
Neurônios
Idioma:
En
Revista:
J Phys Chem Lett
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Espanha