Pre-breakdown to stable phase and origin of multiple current pulses in argon dielectric barrier discharge

摘要

We report on the results of numerical models of the(i)initial growth and(ii)steady state phases of atmospheric-pressure homogeneous dielectric barrier discharge in argon.We employ our new inhouse code called Py DBD,which solves continuity equations for both particles and energy,shows exceptional stability,is accelerated by adaptive time stepping and is openly available to the scientific community.Modeling argon plasma is numerically challenging due to the lower speeds of more inertial ions compared to more commonly modeled neon and helium,but its common use for plasma jets in medicine makes its modeling compelling.Py DBD is here applied to modeling two setups:(i)the exponential growth from natural electron-ion seeds(onset phase)until saturation is reached and(ii)the multiple current pulses that naturally appear during the steady state phase.We find that the time required for the onset phase,when the plasma density grows from 10^(9)m^(-3)to 10^(17)m^(-3),varies from 80μs at 4.5 k V down to a fewμs above 6.5 k V,for voltage frequency f=80 k Hz and gap width d_(g)=0.9 mm.At the steady state,our model reproduces two previously observed features of the current in dielectric barrier discharge reactors:(1)an oscillatory behavior associated to the capacitative character of the circuit and(2)several(N_(p))current pulses occurring every half sinusoidal cycle.We show that the oscillations are present during the exponential growth,while current pulses appear approaching the steady state.After each micro-discharge,the gas voltage decreases abruptly and charged particles rapidly accumulate at the dielectric boundaries,causing avalanches of charged particles near the reactor boundaries.Finally,we run a parametric study finding that N_(p)increases linearly with voltage amplitude V_(amp),is inversely proportional to dielectric gap d_(g)and decreases when voltage frequency f increases.The code developed for this publication is freely available at the address https://github.com/gabersyd/PyDBD.