Solid-StateNanopore Sensors: Analyte Quantificationby Event Frequency Analysis at High Voltages

Solid state nanopores have emerged as an important electrical label-free single-molecule detection platform. While much effort has been spent on analyzing the current trace to determine size, shape and charge of the translocating species, a less studied aspect is the number of events and how this relates to analyte concentration. In this work we systematically investigate how the event frequency depends on voltage applied across the pore and show that this dependence can be utilized to determine target concentration. Importantly, this method does not require any calibration or any additional species added to the solution. Data analysis algorithms are introduced to accurately count events also for high voltages (up to 1 V). For double stranded DNA as model analyte, we find a linear relation between event frequency and voltage for pores 10 nm or more in diameter. For smaller pores, the majority of events are dockings rather than translocations and the linear relation is lost, in agreement with theory. Our model also predicts that the electrophoretic mobility of the species will influence event frequency, while diffusivity does not, which we confirm by using two different sizes of DNA. The analyte concentration determination is found to be remarkably accurate (10% error) when taking the average of multiple (∼4) experiments. If based on a single experiment, the predictive power is lower, but the method still provides a useful estimate (<30% error). This study should be useful as a guide when performing experiments at higher voltages and may serve as a method to extract analyte concentration in bioanalytical applications of nanopore sensors.

Publication Details

Journal
Figshare
Published
2025-02-20
DOI
https://doi.org/10.1021/acs.analchem.4c05037.s001
Primary Topic
Nanopore and Nanochannel Transport Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Solid-StateNanopore Sensors: Analyte Quantificationby Event Frequency Analysis at High Voltages

Figshare
Nanopore and Nanochannel Transport Studies
article

Solid-StateNanopore Sensors: Analyte Quantificationby Event Frequency Analysis at High Voltages

article en

Abstract

Solid state nanopores have emerged as an important electrical label-free single-molecule detection platform. While much effort has been spent on analyzing the current trace to determine size, shape and charge of the translocating species, a less studied aspect is the number of events and how this relates to analyte concentration. In this work we systematically investigate how the event frequency depends on voltage applied across the pore and show that this dependence can be utilized to determine target concentration. Importantly, this method does not require any calibration or any additional species added to the solution. Data analysis algorithms are introduced to accurately count events also for high voltages (up to 1 V). For double stranded DNA as model analyte, we find a linear relation between event frequency and voltage for pores 10 nm or more in diameter. For smaller pores, the majority of events are dockings rather than translocations and the linear relation is lost, in agreement with theory. Our model also predicts that the electrophoretic mobility of the species will influence event frequency, while diffusivity does not, which we confirm by using two different sizes of DNA. The analyte concentration determination is found to be remarkably accurate (10% error) when taking the average of multiple (∼4) experiments. If based on a single experiment, the predictive power is lower, but the method still provides a useful estimate (<30% error). This study should be useful as a guide when performing experiments at higher voltages and may serve as a method to extract analyte concentration in bioanalytical applications of nanopore sensors.

Figshare
Life in Land
Openalex Percentile: Top 54%
Nanopore and Nanochannel Transport Studies
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.