Predicting Resistive Pulse Signatures in Nanopores by Accurately Modeling Access Regions
Resistive pulse sensing is used to characterize and count single particles in solution moving through channels under an electric bias, with nanoscale pores providing enough spatial resolution for single-molecule identification and sequencing. This technique relies on measuring the ionic current drop produced by the passage of a molecule and, through conductance models, translating the blockage signal into molecular dimensions. However, no generalized model exists that considers the resistive contributions of the pore exterior, i.e. the access regions, when obstructed by a molecule. This is becoming increasingly important with the advent of 2D materials and ultrathin membranes featuring low aspect ratio pores. In this work, a general method by which to model the resistance of access regions in the presence of an insulating obstruction is presented. Thin oblate spheroidal slices are used to partition access regions and infer their conductance when blocked by differently shaped objects. We show that our model accurately estimates the blocked-state conductance of 2D and finite-length pores in the presence of simple or complex structures positioned at varying distances from the pore opening. The model is shown to capture off-axis effects by predicting deeper blockages for obstructions offset from the pore's central axis. A model-based web app was created to predict the electrical signatures of a wide range of molecule geometries translocating through differently shaped pores. The introduced model and accompanying tool will help guide future experimental designs and thus present a straightforward way to extend the quantification of the resistive pulse technique at the nanoscale.