(Bio)Plasma Chemistry
Plasma to Plasma! Workshop, Jan 2013
Wouter Van Gaens, Annemie Bogaerts
PLASMANT
University of Antwerp, Belgium
1. Introduction

Plasma medicine applications
 Microdischarge
 Non-LTE plasma at atmospheric pressure



Large interest in plasma jets
Usually noble gas mixing with ambient air
Both physically and chemically complicated processes
NOBLE GAS
PLASMA
MIXING
ZONE
1. Introduction
NOBLE GAS
PLASMA

MIXING
ZONE
Aim of this work





Insight in chemical phenomena (generally valid ?!?)
Simple model = low computational load
Mainly qualitative study
Implement humid air chemistry set with argon coupling
Reduced chemistry set (can be used in higher level models ?!?)
1. Introduction

Other important/relevant humid air reaction chemistry
modelling, i.a.:

Kogelschatz et al (1988) & Kossyi et al (1992) : Dry air

NIST Standard reference data (‘90-’00): Humid air


Gentille and Kushner (1995): Humid air


Plasma medicine, RF discharges
Sakiyama et al (2012): Humid air


General biomedical applications, hydrogen peroxide generation
Iza et al (‘10): He/O2/H2O


Plasma remediation of NxOy
Liu, Bruggeman, Iza and Kong (2010): He/H2O


Combustion and atmospheric chemistry community (Herron, Atkinson, Tsang et al)
Plasma medicine, surface micro discharge
Babaeva and Kushner (2013): Humid air

Plasma medicine, DBD filaments and fluxes towards wounded skin
2. Typical plasmajet configurations
Recent review: X Lu et al, Plasma Sources Sci. Technol. 21 (2012) 03400)
2. Typical plasmajet configurations
Recent review: X Lu et al, Plasma Sources Sci. Technol. 21 (2012) 03400)
2. Typical plasma jet configurations
Prof. P. Bruggeman,
Eindhoven Univ. of Technology
•
•
•
Needle electrode (Ø ± 0.5
mm)
Coaxially inserted in
dielectric tube (inner Ø ± 1.8
mm)
Needle tip 1.9 mm from
nozzle exit
10 mm
3 mm
Device of our choice:
2. Typical plasma jet configurations
•
6.5 Watt dissipated power
•
RF discharge
•
Ar gas feed 2 slm
•
Possibility of oxygen
admixture
9 mm
3 mm
Operating conditions:
3. Model

0D model ‘GlobalKin'
Prof. M. J. Kushner, University of Michigan, US
Boltzmann solver(*)
Species kinetics
Electron energy equation
(*) can be called very frequently
with changing background gas
composition!!!!!!!
3. Model

0D fluid model ‘GlobalKin'
Prof. M. J. Kushner, University of Michigan, US
Boltzmann solver(*)
Power input!
Species kinetics
Electron energy equation
(*) can be called frequently, for
example with changing
background gas composition
3. Model

Assumptions to obtain ‘semi-empirical’ model
1) Pseudo-1D simulation (to give idea of “distance to nozzle”)



Volume averaged element moving along the plasmajet stream > imaginary
cylinder
Moving speed ̴ flow velocity & Ø cylinder (1cm ≈ 1msec)
No radial transport (high flow speed) / no axial drift & diffusion flux
3. Model

Assumptions to obtain ‘semi-empirical’ model
2) Humid air diffusion


Ar replaced by N2/O2/H2O
Mixing speed fitted to literature values and 2D fluid simulation calculation
Ellerweg et al (2012)
2D Fluid flow model
Reuter et al (2012)
3. Model

Assumptions to obtain ‘semi-empirical’ model
3) Tgas evolution
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
Fitted to measurements TU/e (Tg, radially averaged)
Self consistent Tgas calculations by model only accurate in first few mm!
3. Model

Why ‘device specific’ plasma chemistry study (≠ more general
approach)?



Pdeposition as function of plasma jet position unknown > plasma
properties matched to experiment
Tgas evolution device specific: crucial for chemistry (eg. NOx and O3)
Broad parameter study: more general chemical info
4. Reaction chemistry set

Extended Ar/N2/O2/H2O chemistry set

85 implemented species!
Ground State
Excited
Charged
Ar
Ar(4S), Ar(4P), Ar2* (a 3Σ+u)
e-, Ar+, Ar2+, ArH+
N2, N
N2,rot, N2,vib, N2(A 3Σ+u), N2 (a' 1Σ-u), N(2D) N2+, N3+, N4+, N+
O2, O3, O
O2,rot, O2,vib, O2 (a 1Δg), O2 (b 1Σ+g), O(1D) O2+, O4+, O+, O-, O2- , O3-
NO, NO2, N2O, NO3, N2O3, N2O4, N2O5 N2Ovib
NO+, NO2+, NO2-, NO3-
NH, HNO, HNO2, HNO3, HNO4
H +, H2 +, H 3 +,
H2, H, H2O, H2O2, HO2, OH
H*, H2,rot, H2,vib, H2*, OH (A)
H2O+, H3O+, H2O2-, OH+, H-,OH-
Waterclusters
H5O2+, H7O3+, H9O4+, H11O5+, H13O6+, H15O7+, H2NO2+, H4NO3+, H6NO4+

Some advantages & differences compared to other models:
1.
complex waterclusters
2.
Argon implementation (less expensive)
3.
Rot/Vib excited states (partially) included
4. Reaction chemistry set

Extended Ar/N2/O2/H2O chemistry set

1885 reactions! (can be reduced to ± 400 reactions)
278 electron impact & 1596 heavy particle reactions (692 dry air)
radiative
decay, 1%
ion
recombination
, 26%
physical
quenching,
17%
Penning
ionisation, 3%
excitation, 22%
chemical
change, 30%
cluster
reactions, 15%
charge
exchange, 6%
electron
detachment,
2%
electron
detachment,
2%
recombinations
, 14%
momentum
transfer, 17%
electron
attachment,
12%
dissociation,
deexcitation,
8%
10%
ionisation, 15%
5. Validation

Calc. [O3] vs. experim. [O3] by TU/e (2% O2 admixture)

Relatively good qualitative agreement

Detailed discussion in upcoming paper!

Agreement for [O], [NO] and [OH] (literature) for similar devices.
6. Output reaction chemistry model

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Similar conditions as for TU/e
plasmajet device, except no O2
admixture
Very rapid chem/phys quenching of energetic
Ar states by air
Fast charge exchange by Ar ions
Strong [e-] drop due to efficient dissociative
electron attachment of air
6. Output reaction chemistry model

Biomedically active species
O2(a), O3, NO, N2O, H2O2, HNO3 predicted to be
very long living species

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1-1000 ppm
N < H < O in lifetime and density, but ‘distance
of treatment’ is crucial!


O into O3 if Tgas low/ into NOx if Tgas high
Plasma becomes electronegative due to
electron attachment in the far effluent
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6. Output reaction chemistry model

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Water cluster formation
Complex mechanism by implementing
reaction rates (≠ Arrhenius form) by Sieck
et al (2000)
Dominant positive charge carrier
Water cluster size gradually increasing in
time
NO+ clusters less abundant
6. Output reaction chemistry model


Example of parameter variation: 300K
Large changes in densities (up to order of
magnitude)
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Changes in chemical pathways less drastic!
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Less NO, much more O3 in far effluent

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Faster recombination of radicals like O, H into OH,
HO2
Favors HNO3 formation! (though net less NOx)
Chemical pathway changes taken into account in
reduced chemistry set!
Rel. ∆[X] vs. [X] with
fitted Tg profile cfr. experiment
8. Conclusions & Outlook
• Large amount of chemical data studied
• Argon implementation
• Semi-empirical model (validation)
• More detailed chemical pathway analysis will be given in upcoming paper
• Idem ditto for effect of power, air humidity & flow speed on chemistry
• Reduced chemistry set
Acknowledgments:

Prof. Dr. M. J. Kushner

Flemish Agency for Innovation by Science and Technology

Computer facility CalcUA

Prof. P. Bruggeman of Eindhoven University of Technology
for providing experimental data
Thank you for your attention!
Questions?