A bi-functional three-terminal memristor applicable as an artificial synapse and neuron.
Journal
Nanoscale
ISSN: 2040-3372
Titre abrégé: Nanoscale
Pays: England
ID NLM: 101525249
Informations de publication
Date de publication:
02 Nov 2023
02 Nov 2023
Historique:
medline:
3
11
2023
pubmed:
17
10
2023
entrez:
17
10
2023
Statut:
epublish
Résumé
Due to their significant resemblance to the biological brain, spiking neural networks (SNNs) show promise in handling spatiotemporal information with high time and energy efficiency. Two-terminal memristors have the capability to achieve both synaptic and neuronal functions; however, such memristors face asynchronous programming/reading operation issues. Here, a three-terminal memristor (3TM) based on oxygen ion migration is developed to function as both a synapse and a neuron. We demonstrate short-term plasticity such as pair-pulse facilitation and high-pass dynamic filtering in our devices. Additionally, a 'learning-forgetting-relearning' behavior is successfully mimicked, with lower power required for the relearning process than the first learning. Furthermore, by leveraging the short-term dynamics, the leaky-integrate-and-fire neuronal model is emulated by the 3TM without adopting an external capacitor to obtain the leakage property. The proposed bi-functional 3TM offers more process compatibility for integrating synaptic and neuronal components in the hardware implementation of an SNN.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM