Numerical simulation and experimental diagnostics of fast electron kinetics and plasma parameters in a microhollow cathode discharges in helium

Abstract

The paper presents the results of studies of plasma parameters and kinetics of fast electrons in the region of negative glow of a discharge with a microhollow cathode at high pressures based on a hybrid model that includes a kinetic description of electrons and a hydrodynamic description of the heavy plasma component. The results of numerical calculations are compared with the results of probe studies. It is shown that the hybrid model makes it possible to accurately describe the formation of EDF peaks from fast electrons produced as a result of Penning ionization reactions and superelastic collisions. The results of numerical calculations make it possible to predict the parameters of the negative glow plasma in discharges with a microhollow cathode in pure helium and in helium with impurities of various gases, including organic ones.

Distinguishing methane from other hydrocarbons using machine learning and atmospheric pressure plasma optical emission spectroscopy

“…In our recent paper [1], plasma modeling provides evidence for limited dissociation, whereas algorithm detection of methane is based on both indirect mechanisms through plasma interaction with impurities, and on low-intensity carbon species emission-namely CH and C 2-the former producing an identifiable emission line at 431 nm [10][11][12][13]. In recent years, few techniques proposed to detect hydrocarbons and gas impurities in the form of molecular using Glow discharge and kinetics of fast electrons [14,15]. In this study, different gas mixtures of methane, acetylene, and ethane at various concentrations from 1 ppm to 100 ppm in helium were used to provide emission spectra in the range of 194-1122 nm as input to ML classification models based on PLS-DA with the aim of detecting hydrocarbon type and concentration.…”