% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Reiser:891761,
      author       = {Reiser, D. and von Keudell, A. and Urbanietz, T.},
      title        = {{D}etermining {C}hemical {R}eaction {S}ystems in
                      {P}lasma-{A}ssisted {C}onversion of {M}ethane {U}sing
                      {G}enetic {A}lgorithms},
      journal      = {Plasma chemistry and plasma processing},
      volume       = {41},
      issn         = {1572-8986},
      address      = {Dordrecht},
      publisher    = {Springer Science + Business Media B.V.},
      reportid     = {FZJ-2021-01721},
      pages        = {793–813},
      year         = {2021},
      abstract     = {Even for processes with only a few gas species involved the
                      detailed description of plasma-assisted conversion processes
                      in gas mixtures requires a large amount of processes to be
                      taken into account and a large number of neutral and charged
                      particles must be considered. In addition, setting up the
                      corresponding reaction kinetics model needs the knowledge of
                      the rate coefficients and their temperature dependence for
                      all possible reactions between those species. Reduced
                      reaction networks offer a simplified and pragmatic way to
                      obtain an overall reaction kinetics model, already useful
                      for the analysis of experimental data even if not all
                      details of chemistry can be covered. In this paper we
                      present a derivation of a data driven reduced model for
                      plasma-assisted conversion of methane in an helium
                      environment. By consideration of a small number of
                      elementary reactions, a simple model is set up. Experimental
                      data are analyzed by a genetic algorithm that provides
                      best-fit approximations for the open parameters of the
                      model. In a further step non-relevant parameters of the
                      model are identified and a further model reduction is
                      achieved. The data driven analysis of methane conversion
                      serves as an illustrative example of the proposed method.
                      The parameters and reaction channels found are compared with
                      known results from the literature. The method is described
                      in detail. The main goal of this work is to present the
                      potential of this data driven method for a simplified and
                      pragmatic modeling in the increasingly important field of
                      plasma-assisted catalytic processes.},
      cin          = {IEK-4},
      ddc          = {540},
      cid          = {I:(DE-Juel1)IEK-4-20101013},
      pnm          = {123 - Chemische Energieträger (POF4-123)},
      pid          = {G:(DE-HGF)POF4-123},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000629560500001},
      doi          = {10.1007/s11090-021-10159-6},
      url          = {https://juser.fz-juelich.de/record/891761},
}