Key chemical reaction pathways in a helium-nitrogen atmospheric glow discharge plasma based on a global model coupled with the genetic algorithm and dynamic programming

Abstract

Determination of the key chemical reaction pathways in cold atmospheric plasmas (CAPs) is of great importance not only for understanding the spatiotemporal evolutions of the key plasma parameters during discharges but also for improving the plasma materials processing qualities. In this paper, a novel chemical reaction reduction method (CRRM) is proposed by using the global fluid model coupled with the genetic algorithm and the dynamic programming technique. With the aid of this newly developed CRRM, the key chemical reaction pathways can be automatically screened with a high computational efficiency under a pre-set critical calculation accuracy for the atmospheric pure helium and helium–nitrogen glow discharge plasmas. By comparing the calculated key plasma parameters, e.g., the species number densities, electron temperatures, voltage–current characteristics, based on the simplified models and their corresponding full models with those of the experimentally measured data, the reliability of the CRRM itself and the established key chemical reaction database for the atmospheric pure helium and helium–nitrogen CAPs are validated. This research also provides a general method for screening the key chemical reaction pathways for various low-temperature plasma sources.

Energy exchange modulation for selective control of gas temperature and electron number density in cold atmospheric plasmas

“…Such modeling results indicate that the Penning effect is not important in this study due to the very low nitrogen concentration in the plasma forming gas. (ii) The number density of He + 2 is about one order higher than that of He + due to the chemical reaction pathways discussed in our previous work [21]. (iii) Similarly, the number density of He * 2 is also much higher than that of He * , as shown in figure 4(b).…”

“…The considered key chemical reactions for high-purity helium (with an impurity of 0.5 ppm nitrogen) α-mode RF-APGDs are determined by the genetic algorithm and dynamic programming [21] as listed in table 1. The rate coefficients for R1, R2 and R5 are obtained from the stationary solution of the homogeneous electron Boltzmann equation using the two-term approximation based on BOLSIG+ [22,23], and the corresponding cross-section data are from Phelps database collected from LXCAT website [24].…”

“…Chemical reactions considered in the 1D modeling[21]. Units of the rate coefficients are m 3 s −1 for the two-body reactions, and m 6 s −1 for the three-body reactions.…”

Computational analysis of direct current breakdown process in SF6 at low pressure

“…Generally speaking, there are many reactions to be considered. Recently, some work related to mechanical learning [34,35] has been on how to select the most important reaction. In this work, we consider as many ion-molecule reactions as possible although it may play a limited role in improving accuracy.…”

Surface-induced gas-phase redistribution effects in plasma-catalytic dry reforming of methane: numerical investigation by fluid modeling

“…The synergy reflects the complex interdependence of plasmas and catalysts: the plasma affects the catalyst properties and vice versa-the catalyst affects the plasma properties. As reviewed by Neyts et al [29], on one hand, the effects of plasmas on catalysts include the variation in physical and chemical properties of the catalysts [30][31][32], the formation of hot spots [33], photon irradiation [34][35][36][37], reduction of the activation barrier [38,39], and change in the reaction pathways [40][41][42]. On the other hand, effects of catalysts on plasmas involve the electric field enhancement [43], the formation of microdischarges in holes [44,45], the variation of the discharge form [43,46], and adsorption of plasma species on the catalyst surface [47,48].…”