22nd International Symposium on Plasma Chemistry
July 5-10, 2015; Antwerp, Belgium
Numerical simulation of CH 4 -CO 2 plasma-chemistry in a dielectric barrier
discharge reactor
A.M. Montoro-Damas1, A. Gómez-Ramírez1, J. Cotrino1,2 and C. Soria-Hoyo2
1
2
Instituto de Ciencia de Materiales, CSIC, Avda. Américo Vespucio 49, 41092 Sevilla, Spain
Facultad de Física, Universidad de Sevilla, Avda. Reina Mercedes s/n, 41012 Sevilla, Spain
Abstract: The plasma-chemistry of CH 4 -CO 2 plasmas at atmospheric pressure are
simulated by 0D numerical modelling with a complex reaction scheme. The conditions are
typical of a dielectric barrier discharge at atmospheric pressure. The micro-discharges are
simulated by trains of nanosecond electronic pulses. The rates of electronic processes are
calculated from the electronic energy distribution function. The results show the generation
of syngas and valuable chemicals such as ethane, acetylene and methanol.
Keywords: numerical simulation, plasma chemistry, methane, carbon dioxide, syngas
1. Introduction
Dielectric barrier discharge (DBD) plasmas are a
powerful method of hydrocarbon reforming [1]. A high
number of contributions have explored the feasibility of
DBD and other types of discharges for hydrocarbon
reforming (see [2] for a review). It has been also shown
that DBDs are a practical procedure for in situ production
of hydrogen from highly available fuels such as gasoline
or natural gas [3].
The plasma-chemistry of DBDs is highly complex,
involving hundreds of reactions [4]. Fortunately, there are
extensive data of reaction rates for many processes
involving hydrocarbons [5] as well as for electronic
processes [6][7] that allow a reasonably realistic
modelling of plasma-chemistry.
In this contribution, we report the results of numerical
simulations of the plasma chemistry of CH 4 -CO 2
plasmas. The numerical model is analogous to the one
developed by Snoeckx et al. [4] and use most or their
data. The model assumes a completely homogeneous
volume of plasma where only the evolution in time of
species concentration is taking into account (“0D”
modelling). The effect of microdischarges present in a
real DBD is simulated by a train of short pulses of electric
field with nanoseconds duration. The frequency and
deposited power by pulse are inputs to the model are
chosen to provide an optimum agreement with the
experimental DBD reactor developed by the authors.
Although the 0D modelling neglects many effects that
may be important in the DBD we expect that it will allow
predicting the effects of different inputs to the reactor
and will guide the interpretation of experimental results.
2. Numerical methods
The numerical simulations have been built basing on
software ZDPlaskin [7]. This software integrates
Boltzmann’s equation for electron energy distribution
from a given a set of electronic processes and marches in
time balance equations of species concentrations. For a
P-I-2-12
system of 𝑟 reactions between 𝑠 species, the reactions
may
be
represented
schematically
by
𝑘𝑗
𝑐𝑙1 𝑗 𝑆𝑙1 + 𝑐𝑙2 𝑗 𝑆𝑙2 + ⋯ + 𝑐𝑙𝑛 𝑗 𝑆𝑙𝑛 → 𝑐𝑙𝑛+1𝑗 𝑆𝑙𝑛+1 +
𝑐𝑙𝑛+2𝑗 𝑆𝑙𝑛+2 + ⋯ + 𝑐𝑙𝑛+𝑚𝑗 𝑆𝑙𝑛+𝑚
where 𝑆𝑙 represent species with index 𝑙 = 1,2, … , 𝑠 and
reaction proceeds at rate 𝑘𝑗 with 𝑗 = 1,2, … , 𝑟.
In the 0D model, the balance equations form a system of
ordinary first-order differential equations for species
concentration
𝑑[𝑆𝑖 ]
= � ±𝑐𝑖𝑖 𝑘𝑗 �[𝑆𝑙 ]𝑐𝑙𝑙
𝑑𝑑
𝑗
𝑙
where 𝑐𝑖𝑖 is the stoichiometric coefficients of species 𝑖 in
reaction 𝑗 and [𝑆𝑙 ] denotes the concentration of species
with index 𝑙 [4].
To yield reliable results, the numerical model must
simulate both electronic processes taking place in the time
scale of ns and neutral-neutral and neutral-ion reaction
kinetics that proceeds with typical times around tenths of
seconds. Therefore, the time step of the simulations is
limited by the rate of electronic processes and results in a
high number of temporal steps (~108) to reach the typical
gas residence times found in the experimental reactor.
For this work, we have used the reaction set given by
Snoeckx et al. [4] which comprises 52 species, 73
electronic processes and 452 reactions.
3. Results and discussion
The results shown in figures 1 and 2 demonstrate the
ability of the code to provide results comparable to
experimental data. Figure 1 shows the main species
concentration vs. time along a few seconds for an ambient
gas mixture of CH 4 -CO 2 in a ratio 4.0/9.3. The species
generated with higher concentration are H 2 and CO but
there are also significant amounts of higher hydrocarbons
and methanol. Figure 2 shows the electronic pulses and
their effects on species generation during the initial
moments of the simulation. It must be taken into account
1
that the duration of the electronic pulse is too short to be
resolved in this plot. The first pulse is generated from a
small initial density of electrons that grow exponentially
by ionization during the electric field pulse (a triangle
pulse of 10 ns with a peak value of 150 Td) and decay
slowly after the pulse. The following pulses are replicas
of
the
first
one.
Fig. 4.Species concentration as a function of time for a
mixture of CH4/CO2 with ratio 4.76/9.0 during the initial
microseconds.
Fig. 1.Species concentration vs. time for a mixture of
CH 4 /CO 2 with ratio 4.0/9.3.
The effect of even a small change in the composition of
the CH 4 /CO 2 can be much larger than expected, due to
the effect in ionization rate. For example, the results for a
mixture CH 4 /CO 2 with ratio 4.76/9.0 (figure 3) show that
it generates H 2 and CO in a significant smaller amount
that for ration 4.0/9.3. This is due to the smaller ionization
obtained in the 4.76/9.0 mixture, resulting in smaller
deposited power (see figure 4).
4.Conclusions
The plasma-chemistry of a DBD discharge in a
CH4/CO2 mixture has been numerically simulated by a
0D model. The results of the simulation are in reasonable
agreement with experimental results and allow the
analysis of different parameter on discharge behaviour.
Fig. 2.Species concentration as a function of time for a
mixture of CH4/CO2 with ratio 4.0/9.3 during the initial
microseconds.
Fig. 3.Species concentration vs. time for a mixture of
CH 4 /CO 2 with ratio 4.76/9.0.
2
5. Acknowledgements
We thank the Junta de Andalucía (Projects P12-FQM2265, P10-FQM-5735, University of Seville) and Spanish
Ministry of Science and Innovation (contract FIS201125161, Project Recupera2020-2.2.3, Spanish National
Research Council) for financial support.
4. References
[1] H. L. Chen, H. M. Lee, S. H. Chen, Y. Chao, M. B.
Chang, Applied Catalysis, 85, 1-9 (2008).
[2] G. Petitpas, J.D. Rollier, A. Darmon, J. GonzálexAguilar, R. Metkemeijer, L. Fulcheri, International
Journal of Hydrogen Energy, 32, 2848-2867 (2007).
[3] B. Sarmiento, J. J. Brey, I. G. Viera, A. R. GonzálezElipe, J. Cotrino, V J. Rico, Journal of Power Sources,
169, 140-143 (2007).
[4] R. Snoeckx, R. Aert, X. Tu, A. Bogaerts, J. Phys.
Chem. 117, 4957-4970, (2013).
[5] D. L. Baulch, C. T. Bowman, C. J. Cobos, R. A. Cox,
Th. Just, J. A. Kerr, M. J. Pilling, D. Stocker, J. Troe,
W. Tsang, R. W. Walker, J. Warnatz, Journal of
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(2005).
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[6]
D. Reiter, R. K. Janev, Contributions to Plasma
Physics, 50, 986 (2010).
[7]
Lxcat database, http://www.lxcat.net.
[8]
S. Pancheshnyi, B. Eismann, G.J.M. Hagelaar,
L.C.
Pitchford,
Computer
code
ZDPlasKin,http://www.zdplaskin.laplace.univ-tlse.fr
(University of Toulouse, LAPLACE, CNRS-UPS-INP,
Toulouse, France, 2008).
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