5. Conclusion

4.2.2 Gliding arc plasmatron (GAP)

Plasma Chemistry and Gas Conversion

with packing beads of ε<sup>r</sup> = 1000. Adopted from [97] with permission.

Figure 10.

Figure 11.

24

obtained from the model in [87].

Figure 11 illustrates a typical 3D gas flow pattern (a), as well as the calculated electron density profile (b), in a reverse vortex flow (RVF) GA plasma reactor, also called gliding arc plasmatron (GAP), operating in argon. The stream line plot clearly

Calculated steady-state gas flow stream lines (a) and electron density at a time of 5.3 ms, when the arc is stabilized in the center (b), for a reverse vortex flow GA plasma reactor at an arc current of 240 mA, as

Calculated electron number density distribution as a function of time, for a packed bed DBD reactor in dry air,

Plasma-based CO2 conversion is gaining increasing interest, but to improve this application, we need to obtain a better insight in the underlying mechanisms. The latter can be obtained by both plasma chemistry modeling and plasma reactor modeling. This chapter shows some examples of both modeling approaches from our own group, to illustrate what type of information can be obtained from such models and how this modeling can contribute to a better insight, in order to improve this application.

0D chemical reaction kinetic modeling is very suitable for describing the underlying plasma chemical reaction pathways of the conversion process. We have illustrated this for pure CO2 splitting, showing the difference between a DBD and MW/ GA plasma. Indeed, in a DBD, the CO2 conversion is mainly due to electron impact electronic excitation followed by dissociation with the CO2 ground-state molecules, which requires about 7–10 eV per molecule. This "waste of energy" explains the lower energy efficiency of CO2 splitting in a DBD. On the other hand, in a MW and GA plasma, vibrational excitation of CO2 is dominant, and VV relaxation gradually populates the higher vibrational levels (so-called ladder climbing). This is the most energy-efficient way of CO2 dissociation, as it requires only 5.5 eV per molecule, that is, exactly the C=O bond energy.

Acknowledgements

Author details

Belgium

27

Saudi Arabia

Annemie Bogaerts<sup>1</sup>

Laer for sharing their simulation results.

DOI: http://dx.doi.org/10.5772/intechopen.80436

Modeling for a Better Understanding of Plasma-Based CO2 Conversion

We would like to thank R. Aerts, A. Berthelot, C. De Bie, T. Kozák, and K. Van

\*, Ramses Snoeckx1,2, Georgi Trenchev1 and Weizong Wang1,3

1 Department of Chemistry, Research Group PLASMANT, University of Antwerp,

2 Clean Combustion Research Center (CCRC), Physical Science and Engineering Division (PSE), King Abdullah University of Science and Technology (KAUST),

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

3 School of Astronautics, Beihang University, Beijing, P.R. China

\*Address all correspondence to: annemie.bogaerts@uantwerpen.be

provided the original work is properly cited.

We also presented the important reaction pathways in CO2/CH4, CH4/O2, CO2/ H2 and CO2/H2O mixtures, as well as for the effect of N2 addition to a CO2 plasma. In a DBD plasma, the conversion is always initiated by electron impact dissociation, creating radicals that react further into value-added compounds. The main products formed are syngas (CO/H2), but higher hydrocarbons and oxygenates are also formed in limited amounts. However, the selective production of these targeted compounds is not yet possible, due to the high reactivity of the plasma. Therefore, a catalyst must be inserted in the plasma. Our models reveal that CO2/CH4 and CH4/ O2 mixtures exhibit totally different chemical reactions, resulting in different products. A CO2/H2 mixture does not produce many higher hydrocarbons and oxygenates, and the CO2 conversion is very limited, due to the lack of CH2 (and CH3) radical formation. Indeed, the CH2 radicals are the main collision partners of CO2 in the CO2/CH4 mixture. Furthermore, adding H2O to a CO2 DBD plasma yields a drop in CO2 conversion, and also the H2O conversion is limited, and virtually no oxygenated hydrocarbons are formed, which could also be explained from the chemical reaction paths. The insights obtained by the model might be useful to provide possible solutions. The last example of 0D chemical kinetic modeling was given for a CO2/N2 plasma, where it was shown that also NOx compounds are produced, which might give several environmental problems. Again, the model can explain their formation, which is useful to provide possible solutions on how to avoid this NOx formation.

Although 0D models can give useful information on the plasma chemistry, they cannot really account for details in the plasma reactor configuration and thus predict how modifications to the reactor design might lead to improved CO2 conversion. For this purpose, 2D or 3D fluid models of specific reactor designs are needed. Developing such fluid models for a detailed plasma chemistry, however, leads to excessive calculation times. Therefore, these models are up to now mainly developed for simpler chemistry, in argon or helium. We have shown here examples for a packed bed DBD reactor and a GAP. These models allow to elucidate why certain reactor designs give beneficial results and to pinpoint the limitations and finally how improvements in the reactor designs might yield a better CO2 conversion and energy efficiency.

In the future work, we intend to implement the more complex CO2 chemistry (either pure or mixed with other gases) in such fluid models, to obtain a more comprehensive picture of CO2 conversion in a real plasma reactor geometry. As this is quite challenging in terms of computation time, reduced chemistry sets must be developed for CO2 and its gas mixtures. When modeling CO2 conversion in a MW or GA plasma, the vibrational kinetics must be accounted for. To avoid the need of describing all individual levels, we have developed a level-lumping strategy [39], which enables to group the vibrational levels of the asymmetric stretch mode of CO2 into a number of groups. This reduces the calculation time, so that it can be implemented in 2D models [86]. We believe that a combination of 0D chemical kinetic models (to obtain detailed insight in the entire plasma chemistry and to develop reduced chemistry sets, identifying the main species and chemical reactions) and 2D/3D fluid models (for a detailed understanding of the reactor design) is the most promising approach to make further progress in this field.

Modeling for a Better Understanding of Plasma-Based CO2 Conversion DOI: http://dx.doi.org/10.5772/intechopen.80436
