Simulation of a model nanopore sensor: ion competition underlies device behavior

TL;DR

This paper models a nanopore sensor where ion competition at binding sites affects current signals, enabling detection of low analyte concentrations through a hybrid simulation approach that captures ionic correlations and device behavior.

Contribution

It introduces a hybrid NP+LEMC simulation method to accurately model ion competition and device response in nanopore sensors, including low concentration regimes.

Findings

Ion competition influences current reduction signals.

Device behavior depends on pore and electrolyte parameters.

The model accurately captures ionic correlations and low concentration effects.

Abstract

We study a model nanopore sensor with which a very low concentration of analyte molecules can be detected on the basis of the selective binding of the analyte molecules to the binding sites on the pore wall. The bound analyte ions partially replace the current-carrier cations in a thermodynamic competition. This competition depends both on the properties of the nanopore and the concentrations of the competing ions (through their chemical potentials). The output signal given by the device is the current reduction caused by the presence of the analyte ions. The concentration of the analyte ions can be determined through calibration curves. We model the binding site with the square-well potential and the electrolyte as charged hard spheres in an implicit background solvent. We study the system with a hybrid method in which we compute the ion flux with the Nernst-Planck (NP) equation coupled with the Local Equilibrium Monte Carlo (LEMC) simulation technique. The resulting NP+LEMC method is able to handle both strong ionic correlations inside the pore (including finite size of ions) and bulk concentrations as low as micromolar. We analyze the effect of bulk ion concentrations, pore parameters, binding site parameters, electrolyte properties, and voltage on the behavior of the device.