Improved Conductance Blockage Modeling of Cylindrical Nanopores, from 2D to Thick Membranes.

Conductance Modeling Nanopore Resistive Pulse

Journal

Nano letters
ISSN: 1530-6992
Titre abrégé: Nano Lett
Pays: United States
ID NLM: 101088070

Informations de publication

Date de publication:
15 Aug 2024
Historique:
medline: 15 8 2024
pubmed: 15 8 2024
entrez: 15 8 2024
Statut: aheadofprint

Résumé

The ionic current blockage from a nanopore sensor is a fundamental metric for characterizing its dimensions and identifying molecules translocating through it. Yet, most analytical models predicting the conductance of a nanopore in both open and obstructed states remain inaccurate. Here, using an oblate spheroidal coordinate framework to study the electrical response of nanopore access regions, we reveal that the widely used model from Kowalczyk et al. significantly overestimates access region contributions when blocked by a cylindrical object, like DNA. To address this, we present an improved analytical model for the obstructed access resistance, which we establish as highly accurate through finite-element simulations, especially for ultrathin membranes and long narrow channels. Equipped with an improved nanopore conductance model, this work provides tools for more accurate calculation of the pore size and for the expected blockade from DNA, of high practical value for many biosensing applications.

Identifiants

pubmed: 39146027
doi: 10.1021/acs.nanolett.4c02538
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Martin Charron (M)

150 Louis-Pasteur Private, Department of Physics, University of Ottawa, Ottawa K1N 6N5, Canada.

Zachary Roelen (Z)

150 Louis-Pasteur Private, Department of Physics, University of Ottawa, Ottawa K1N 6N5, Canada.

Deekshant Wadhwa (D)

150 Louis-Pasteur Private, Department of Physics, University of Ottawa, Ottawa K1N 6N5, Canada.

Vincent Tabard-Cossa (V)

150 Louis-Pasteur Private, Department of Physics, University of Ottawa, Ottawa K1N 6N5, Canada.

Classifications MeSH