A Turing model of pattern formation in atmospheric pressure gas discharges

TL;DR

This paper introduces a Turing model for pattern formation in atmospheric pressure gas discharges, explaining observed striations and structural changes with variations in power and pressure.

Contribution

It presents a novel Turing model applying activator-inhibitor dynamics to gas discharge patterns, aligning predictions with experimental observations.

Findings

Model predicts spatial striations matching experiments

Discharge structure changes with power and pressure variations

Quantitative agreement on pattern scale lengths

Abstract

In this letter we propose a Turing model of the formation of patterns of visible light emission intensity in atmospheric pressure gas discharges. The electron density and the electron temperature take the roles of activator and inhibitor respectively in a two-reactant Turing model, with the activator diffusion coeffcient being much smaller than that of the inhibitor, and ionization and excitation from excited state atoms considered as the dominant reaction processes. The model predicts striations in a 1D system, which quantitatively agree with experimental results in terms of the spatial variation scale lengths. Additionally, the model also predicts changes in the discharge structure observed experimentally when input power and gas pressure are varied.