Synaptic Response of Fluidic Nanopores: The Connection of Potentiation with Hysteresis

Iontronic fluidic ionic/electronic components are emerging as promising elements for artificial brain-like computation systems. Nanopore ionic rectifiers can be operated as a synapse element, exhibiting conductance modulation in response to a train of voltage impulses, thus producing programmable resistive states. We propose a model that replicates hysteresis, rectification, and time domain response properties, based on conductance modulation between two conducting modes and a relaxation time of the state variable. We show that the kinetic effects observed in hysteresis loops govern the potentiation phenomena related to conductivity modulation. To illustrate the efficacy of the model, we apply it to replicate rectification, hysteresis and conductance modulation of two different experimental systems: a polymer membrane with conical pores, and a blind-hole nanoporous anodic alumina membrane with a barrier oxide layer. We show that the time transient analysis of the model develops the observed potentiation and depression phenomena of the synaptic properties.

Authors

Institutions

Publication Details

Journal
ChemPhysChem
Published
2024-08-09
DOI
https://doi.org/10.1002/cphc.202400265
Citations
8
Primary Topic
Nanopore and Nanochannel Transport Studies
Type
article
Field-Weighted Citation Impact
1.48

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Synaptic Response of Fluidic Nanopores: The Connection of Potentiation with Hysteresis

Cheryl Suwen Law, Abel Santos, Agustín Bou, Juan Bisquert et al.
8 citations
ChemPhysChem
Nanopore and Nanochannel Transport Studies
1.48
article

Synaptic Response of Fluidic Nanopores: The Connection of Potentiation with Hysteresis

Cheryl Suwen Law, Abel Santos, Agustín Bou, Juan Bisquert, Marc Sánchez‐Mateu
article en
8 citations

Abstract

Iontronic fluidic ionic/electronic components are emerging as promising elements for artificial brain-like computation systems. Nanopore ionic rectifiers can be operated as a synapse element, exhibiting conductance modulation in response to a train of voltage impulses, thus producing programmable resistive states. We propose a model that replicates hysteresis, rectification, and time domain response properties, based on conductance modulation between two conducting modes and a relaxation time of the state variable. We show that the kinetic effects observed in hysteresis loops govern the potentiation phenomena related to conductivity modulation. To illustrate the efficacy of the model, we apply it to replicate rectification, hysteresis and conductance modulation of two different experimental systems: a polymer membrane with conical pores, and a blind-hole nanoporous anodic alumina membrane with a barrier oxide layer. We show that the time transient analysis of the model develops the observed potentiation and depression phenomena of the synaptic properties.

ChemPhysChemVol. 25(23)
Universitat Jaume I (ES), Consejo Superior de Investigaciones Científicas (ES), Leibniz Institute for Solid State and Materials Research (DE), Instituto de Tecnología Química (ES), The University of Adelaide (AU), Universitat Politècnica de València (ES)
University of Adelaide, HORIZON EUROPE Framework Programme, Australian Research Council
Clean water and sanitation
Openalex Percentile: Top 19%
Nanopore and Nanochannel Transport Studies
1.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Synaptic Response of Fluidic Nanopores: The Connection of Potentiation with Hysteresis — Cheryl Suwen Law, Abel Santos, et al. · ChemPhysChem (2024) | TGRS Research Map | TGRS