Flowing Atmospheric Pressure Afterglow for Ambient Ionization: Reaction Pathways Revealed by Modeling

We describe the plasma chemistry in a helium flowing atmospheric pressure afterglow (FAPA) used for analytical spectrometry, by means of a quasi-one-dimensional (1D) plasma chemical kinetics model. We study the effect of typical impurities present in the feed gas, as well as the afterglow in ambient humid air. The model provides the species density profiles in the discharge and afterglow regions and the chemical pathways. We demonstrate that H, N, and O atoms are formed in the discharge region, while the dominant reactive neutral species in the afterglow are O-3 and NO. He* and He-2* are responsible for Penning ionization of O-2, N-2, H2O, H-2, and N, and especially O and H atoms. Besides, He-2(+) also contributes to ionization of N-2, O-2, H2O, and O through charge transfer reactions. From the pool of ions created in the discharge, NO+ and (H2O)(3)H+ are the dominant ions in the afterglow. Moreover, negatively charged clusters, such as NO3H2O- and NO2H2O-, are formed and their pathway is discussed as well. Our model predictions are in line with earlier observations in the literature about the important reagent ions and provide a comprehensive overview of the underlying pathways. The model explains in detail why helium provides a high analytical sensitivity because of high reagent ion formation by both Penning ionization and charge transfer. Such insights are very valuable for improving the analytical performance of this (and other) ambient desorption/ionization source(s).

Automated summary

In this study, plasma chemistry in a helium flowing atmospheric pressure afterglow (FAPA) for analytical spectrometry is described using a quasi-one-dimensional plasma chemical kinetics model. The model demonstrates the formation of H, N, and O atoms in the discharge region, and the dominance of O-3 and NO species in the afterglow. Helium plays a key role in Penning ionization and charge transfer reactions, leading to high analytical sensitivity. The model's predictions align with previous observations in the literature, providing insights to enhance analytical performance of ambient desorption/ionization sources.