论文和技术资料

The acid-disassociation of surface groups generates the surface charge that drives fundamental nanoscale ion transport behaviors, such as ion current rectification in nanopores. Ion current rectification can be utilized for high sensitivity label-free sensors. The disassociation of surface groups is influenced by the local proton concentration which itself is dictated by the applied voltage dependent enrichment/depletion of ions in the conical nanopore. Despite this, most models of ion transport in conical nanopore systems assume a fixed surface charge and ignore localized pH changes. To study the dynamic interplay between the magnitudes and distributions of ion concentrations, pH distributions and surface charges, a finite element model that calculates the surface charge based on surface site density and local pH values was developed. The model utilizes the Nernst-Planck, Poisson, and Navier-Stokes equations via the Transport of Diluted Species, Electrostatics, and Creeping Flow interfaces. The surface charge is additionally linked back into the steady-state proton concentrations at the surface elements as given by the Nernst-Planck equations, providing a dynamically calculated surface charge magnitude and distribution based only on the surface group density and acidity constant values. This model additionally includes the water auto-ionization reaction, as well as the experienced potential induced shifting of the acidity constants at the nanopore’s mouth. The surface charge density was found to be non-linear across the nanopore and highly asymmetric between the different applied potentials, as well as highly influenced by the bulk pH and electrolyte concentrations. We demonstrate that our model qualitatively predicts experimental measurements of ion current rectification for different bulk pH values at the low electrolyte concentration regime. These results may be of importance when designing nanopore sensors with non-uniform surface modification schemes, and for scanning ion conductance microscopy surface charge mapping, where surface charge values are extracted through finite element models.