Solid-state micro- and nanopores are a versatile sensor platform capable of detecting single particles in electrolyte solution by cross-pore ionic current. Here we report on a use of this technology to identify airborne particulate matter. The detection concept lies in an electrophoretic control of air-floating particles captured in liquid to deliver them into a pore detector via microfluidic channels. We demonstrate resistive pulse measurements to machine-learning-based discriminations of intragranular contents of cypress and cedar pollens at a single-particle level. This all-electrical-sensor technique would pave a new venue toward real-time monitoring of single particles and molecules in air.
Keywords: machine learning; nanopore; particulate matter; resistive pulse analysis; sensor.