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@PHDTHESIS{Gertig:988181,
      author       = {Gertig, Christoph Udo},
      othercontributors = {Bardow, André and Leonhard, Kai and Jupke, Andreas},
      title        = {{C}omputer-aided design of molecules and reactive chemical
                      processes based on quantum chemistry; 1. {A}uflage},
      volume       = {49},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {Wissenschaftsverlag Mainz GmbH},
      reportid     = {RWTH-2024-06057},
      series       = {Aachener Beiträge zur technischen Thermodynamik},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2023},
      note         = {Druckausgabe: 2023. - Auch veröffentlicht auf dem
                      Publikationsserver der RWTH Aachen University 2024;
                      Dissertation, RWTH Aachen University, 2023},
      abstract     = {Resource scarcity and global competition require the
                      optimization of existing and the development of efficient
                      novel chemical processes in short time. Chemical processes
                      use molecules as processing materials that strongly impact
                      process performance and thus play a crucial role in process
                      development and optimization. The performance of reactive
                      chemical processes is particularly influenced by molecules
                      such as reaction solvents and catalysts. Thus, such
                      molecules need to be selected with care. To identify optimal
                      molecules efficiently, computer-aided design methods are
                      desirable that automate the search for promising candidates.
                      However, currently available design methods for reaction
                      solvents and catalysts face significant limitations: These
                      methods typically consider small search spaces and evaluate
                      candidate molecules based on simplified kinetic models.
                      Additionally, most methods require extensive experimental
                      data to fit model parameters for specific reactions. To
                      overcome these limitations, this thesis presents novel
                      computer-aided molecular and process design (CAMPD) methods
                      that identify optimal reaction solvents and catalyst
                      molecules for reactive chemical processes. These CAMPD
                      methods employ advanced quantum chemical methods in
                      conjunction with transition state theory (TST) to predict
                      reaction kinetics without relying on the availability of
                      experimental data, even for catalytic reactions. Combining
                      this predictive power with an optimization-based molecular
                      design algorithm, large molecular design spaces are explored
                      efficiently to identify optimal solvent and catalyst
                      molecules. The proposed CAMPD methods evaluate every
                      designed molecule in an individually optimized chemical
                      process. As a result, the design inherently captures
                      relevant trade-offs between physicochemical properties and
                      accounts for mutual dependencies of optimal molecules and
                      process settings. The developed CAMPD methods are applied in
                      several case studies, including industrially relevant
                      auto-catalytic and catalytic processes. For all case
                      studies, the design methods identify promising molecules.
                      The presented results highlight the superiority of the
                      integrated molecular and process design compared to simpler
                      molecular design approaches. The developed CAMPD methods are
                      generally applicable to reactive chemical processes and
                      provide valuable tools for chemical process design and
                      optimization.},
      cin          = {412110},
      ddc          = {620},
      cid          = {$I:(DE-82)412110_20140620$},
      pnm          = {BMBF 03EK3042C - Verbundvorhaben Carbon2Chem-L5:
                      Herstellung von Wertstoffen für die Kunststoffindustrie auf
                      Basis von CO und CO2 aus Kuppelgasen (BMBF-03EK3042C)},
      pid          = {G:(DE-82)BMBF-03EK3042C},
      typ          = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
      doi          = {10.18154/RWTH-2024-06057},
      url          = {https://publications.rwth-aachen.de/record/988181},
}