Resolving the Size and Charge of Small Particles: A Predictive Model of Nanopore Mechanics

The movement of small particles and molecules through nanopore membranes is widespread and has far-reaching implications. Consequently, the development of mathematical models is essential for understanding these processes on a micro level, leading to deeper insights. In this endeavor, we suggested a model based on a set of empirical equations to predict the transport of substances through a solid-state nanopore and the associated signals generated during their translocation. This model establishes analytical relationships between the ionic current and electrical double-layer potential observed during analyte translocation and their size, charge, and mobility in an electrolyte solution. This framework allows for rapid interpretation and prediction of the nanopore system's behavior and provides a means for quantitatively determining the physical properties of molecular analytes. To illustrate the analytical capability of this model, ceria nanoparticles were investigated while undergoing oxidation or reduction within an original nanopore device. The results obtained were found to be in good agreement with predictions from physicochemical methods. This developed approach and model possess transferable utility to various porous materials, thereby expediting research efforts in membrane characterization and the advancement of nano- and ultrafiltration or electrodialysis technologies.

Authors

Institutions

Publication Details

Journal
The Journal of Physical Chemistry C
Published
2024-08-09
DOI
https://doi.org/10.1021/acs.jpcc.4c02722
Citations
1
Primary Topic
Nanopore and Nanochannel Transport Studies
Type
article
Field-Weighted Citation Impact
0.18

Funders

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

Resolving the Size and Charge of Small Particles: A Predictive Model of Nanopore Mechanics

Tigran M. Abramyan, Vladimir K. Ivanov, S. V. Makaev, Samuel Bearden et al.
1 citations
The Journal of Physical Chemistry C
Nanopore and Nanochannel Transport Studies
0.18
article

Resolving the Size and Charge of Small Particles: A Predictive Model of Nanopore Mechanics

Tigran M. Abramyan, Vladimir K. Ivanov, S. V. Makaev, Samuel Bearden, Dmitry Gil, David Mai, А. Е. Баранчиков, Guigen Zhang, Vladimir Reukov, Jessica Johnson, Anton Murashko
article en
1 citations

Abstract

The movement of small particles and molecules through nanopore membranes is widespread and has far-reaching implications. Consequently, the development of mathematical models is essential for understanding these processes on a micro level, leading to deeper insights. In this endeavor, we suggested a model based on a set of empirical equations to predict the transport of substances through a solid-state nanopore and the associated signals generated during their translocation. This model establishes analytical relationships between the ionic current and electrical double-layer potential observed during analyte translocation and their size, charge, and mobility in an electrolyte solution. This framework allows for rapid interpretation and prediction of the nanopore system's behavior and provides a means for quantitatively determining the physical properties of molecular analytes. To illustrate the analytical capability of this model, ceria nanoparticles were investigated while undergoing oxidation or reduction within an original nanopore device. The results obtained were found to be in good agreement with predictions from physicochemical methods. This developed approach and model possess transferable utility to various porous materials, thereby expediting research efforts in membrane characterization and the advancement of nano- and ultrafiltration or electrodialysis technologies.

The Journal of Physical Chemistry CVol. 128(41)
Harvard University (US), University of Kentucky (US), University of Georgia (US), Massachusetts General Hospital (US), NS Kurnakova Institute of General and Inorganic Chemistry (RU), Clemson University (US), University of California, Berkeley (US)
National Science Foundation, Bill and Melinda Gates Foundation, Russian Science Foundation
Openalex Percentile: Top 54%
Nanopore and Nanochannel Transport Studies
0.18
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.