Models for estimating nanoparticle transmission efficiency through an adverse axial electric field

An adverse electric field is often encountered or utilized when classifying charged nanoparticles or ions according to their electrical mobility. For instance, the classified charged particles usually have to be transported through an adverse electric field against the aerosol sample flow before exiting the outlet of a differential mobility analyzer (DMA). Recently, we reported the transmission of charged nanoparticles through the DMA adverse axial electric field and its improvements. Herein, the simplified analytical model used in that study and a new simplified numerical model to evaluate particle transmission efficiency through the adverse axial electric field are introduced in detail. In addition to the DMA sample outlet, these models are also tested for the electrical mobility filter (EMF) for segregating charged nanoparticles, especially under the unfavorable conditions when the assumptions for these models are violated. The modeled results are compared to a Monte Carlo method based on single-particle tracking and the experimentally determined transmission efficiencies. For the typical geometries and test conditions of a half-mini DMA sample outlet and the EMF, the mean absolute differences between these models and the Monte Carlo method are less than 1%. However, the accuracy of these models is guaranteed only when their assumptions are satisfied, i.e., when the adverse electric field is longer than 4 times the tube radius so that the field lines are axially parallel and the tube length before the adverse electric field is at least half of the entrance length for the air flow. In addition, the simplified analytical model may deviate from the true transmission efficiency when the adverse electric field is longer than 10% of the entire tube. In such cases that the assumptions for both the simplified analytical model and the simplified numerical model are violated, the Monte Carlo method can be used instead. Copyright © 2019 American Association for Aerosol Research