Hauser.2018

Samuel M. Fruehwirth, Ralf Meyer, Andreas W. Hauser. Chiral Separation via Molecular Sieving: A Computational Screening of Suitable Functionalizations for Nanoporous Graphene. ChemPhysChem, 19(18):2331-2339, 2018.

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Abstract

{In a recent study Angew. Chem. Int. Ed., 2014, 53, 9957–9960 a new concept of chiral separation has been suggested, which is based on functionalized, nanoporous sheets of graphene. In this follow–up article we discuss the underlying principle in greater detail and make suggestions for suitable pore functionalizations with respect to a selection of chiral prototype molecules. Considering drug molecules as future targets for a chiral separation via membranes, the necessary pore sizes represent a big challenge for standard methods of computational chemistry. Therefore, we test two common force fields (GAFF, CGenFF) as well as a semiempirical tight–binding approach recently developed by the Grimme group (GFN–xTB) against the computationally much more expensive density functional theory. We identify the GFN–xTB method as the most suitable approach for future simulations of functionalized pores for the given purpose, as it is able to produce reaction pathways in very good agreement with density functional theory, even in cases where force fields tend to an extreme overestimation of barrier heights. Chiral separation can be achieved by employing functionalized, nanoporous sheets of graphene. The underlying principle of this technique is discussed and suggestions are made for suitable pore functionalizations with respect to a selection of chiral prototype molecules. The semiempirical tight–binding approach GFN–xTB method is identified as the most suitable for future simulations of functionalized pores.}

BibTex Reference

@article{Hauser.2018,
   Author = {Fruehwirth, Samuel M. and Meyer, Ralf and Hauser, Andreas W.},
   Title = {{Chiral Separation via Molecular Sieving: A Computational Screening of Suitable Functionalizations for Nanoporous Graphene}},
   Journal = {ChemPhysChem},
   Volume = {19},
   Number = {18},
   Pages = {2331--2339},
   Year = {2018}
}

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