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@ARTICLE{Gertig:877621,
      author       = {Gertig, Christoph and Kröger, Leif and Fleitmann, Lorenz
                      and Scheffczyk, Jan and Bardow, André and Leonhard, Kai},
      title        = {{R}x-{COSMO}-{CAMD}: {C}omputer-{A}ided {M}olecular
                      {D}esign of {R}eaction {S}olvents {B}ased on {P}redictive
                      {K}inetics from {Q}uantum {C}hemistry},
      journal      = {Industrial $\&$ engineering chemistry},
      volume       = {58},
      number       = {51},
      issn         = {1520-5045},
      address      = {Washington, DC},
      publisher    = {Soc.75198},
      reportid     = {FZJ-2020-02336},
      pages        = {22835 - 22846},
      year         = {2019},
      abstract     = {The kinetics of chemical reactions in the liquid phase are
                      often strongly determined by the reaction solvent.
                      Consequently, the choice of the optimal solvent is an
                      important task in chemical process design. Because of the
                      vast number of potential solvents, experimental testing of
                      all candidates is infeasible. To explore the design space of
                      possible reaction solvents, computer-aided molecular design
                      (CAMD) methods have been developed. However,
                      state-of-the-art CAMD methods for reaction solvent design
                      consider usually only a limited molecular design space and
                      rely on simplified models fitted to experimental data to
                      predict solvent performance. To overcome these limitations,
                      we here propose Rx-COSMO-CAMD as the method for the design
                      of reaction solvents. Rx-COSMO-CAMD combines CAMD using the
                      genetic optimization algorithm LEA3D with sound prediction
                      of reaction kinetics based on transition-state theory and
                      advanced quantum chemical methods. Thereby, no experimental
                      data are required. The predictions are shown to be
                      computationally efficient and not limited to certain
                      structural groups. Thus, large and diverse molecular design
                      spaces can be explored. To demonstrate the proposed
                      Rx-COSMO-CAMD method, we successfully design solvents,
                      enhancing the reaction kinetics of a Menschutkin reaction
                      and a chain propagation reaction for the production of
                      polymers and microgels. The method is shown to identify
                      promising solvents for significant enhancement of reaction
                      rates. Rx-COSMO-CAMD is therefore a powerful, fully
                      predictive tool for the identification of optimal reaction
                      solvents.},
      cin          = {IEK-10},
      ddc          = {660},
      cid          = {I:(DE-Juel1)IEK-10-20170217},
      pnm          = {899 - ohne Topic (POF3-899)},
      pid          = {G:(DE-HGF)POF3-899},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000505632500014},
      doi          = {10.1021/acs.iecr.9b03232},
      url          = {https://juser.fz-juelich.de/record/877621},
}