Analysis Method of the Ion Current–Time Waveform Obtained from Low Aspect Ratio Solid-state Nanopores

Abstract

Low aspect ratio nanopores are expected to be applied to the detection of viruses and bacteria because of their high spatial resolution. Multiphysics simulations have revealed that the ion current–time waveform obtained from low aspect ratio nanopores contains information on not only the volume of viruses and bacteria, but also the structure, surface charge, and flow dynamics. Analysis using machine learning extracts information about these analytes from the ion current–time waveform. The combination of low aspect ratio nanopores, multiphysics simulation, and machine learning has made it possible to distinguish different types of viruses and bacteria with high accuracy.