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@PHDTHESIS{Scheffczyk:726523,
      author       = {Scheffczyk, Jan David},
      othercontributors = {Bardow, André and Sundmacher, Kai and Leonhard, Kai},
      title        = {{I}ntegrated computer-aided design of molecules and
                      processes using {COSMO}-{RS}; 1. {A}uflage},
      volume       = {14},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {Wissenschaftsverlag Mainz GmbH - Aachen},
      reportid     = {RWTH-2018-225002},
      isbn         = {978-3-95886-236-4},
      series       = {Aachener Beiträge zur technischen Thermodynamik},
      pages        = {1 Online-Ressource (XXI, 166 Seiten) : Illustrationen},
      year         = {2018},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University; Dissertation, RWTH Aachen University, 2018},
      abstract     = {Optimal performance of chemical processes requires both
                      optimized operating conditions and carefully selected
                      molecules such as solvents. However, the search for optimal
                      molecules and process concepts often has a limited focus:
                      Either processes are optimized using a pre-defined set of
                      molecules or molecules are selected for novel applications
                      based on simplified process indicators. At the same time,
                      the search for optimal molecules often relies on strongly
                      simplified thermodynamic models that require experimentally
                      determined group interaction parameters and confine the
                      molecular design space. Overall, current design approaches
                      often do not capture complex process trade-offs and are
                      limited to prescriptive sets of molecules which likely
                      results in suboptimal choices. To address the challenge of
                      identifying optimal processes and molecules, this thesis
                      presents an integrated computer-aided molecular and process
                      design (CAMPD) approach. The design approach uses quantum
                      mechanics (QM)-based property prediction by COSMO-RS and is
                      thus independent of experimental determined group
                      interaction parameters while not relying on group
                      additivity. For reliable and fast evaluation of complex
                      processes, advanced pinch-based process models are employed.
                      These pinch-based process models account for the inherent
                      trade-off in molecular properties while being both
                      computationally efficient and accurate in comparison to
                      rigorous process models. The integrated design approach in
                      this thesis is stepwise extended from process-level
                      molecular screenings towards molecular design for separation
                      and reaction-separation processes. The application of the
                      presented integrated design approach is illustrated for
                      various examples of solvent selection and process
                      optimization. In particular, process concepts and solvents
                      are investigated for the purification of bio-based platform
                      chemicals as well as the production of CO from CO2. Overall,
                      this thesis successfully integrates COSMO-RS property
                      prediction in CAMPD and thus significantly expands the range
                      and applicability of current CAMPD approaches.},
      cin          = {412110},
      ddc          = {620},
      cid          = {$I:(DE-82)412110_20140620$},
      typ          = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2018-225002},
      url          = {https://publications.rwth-aachen.de/record/726523},
}