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Hydrogen Bonding and Molecular Aggregates in Liquid Methanol, Ethanol, and 1-Propanol

Aleksander VrhovšekFaculty of Chemistry and Chemical Technology, University of Ljubljana, Aškerčeva 5, SI-1001 Ljubljana, SloveniaOrsolya GerebenResearch Institute for Solid State Physics and Optics, Hungarian Academy of Sciences, H-1525 Budapest, P.O. Box 49, HungaryAndrej JamnikFaculty of Chemistry and Chemical Technology, University of Ljubljana, Aškerčeva 5, SI-1001 Ljubljana, SloveniaLászló PusztaiResearch Institute for Solid State Physics and Optics, Hungarian Academy of Sciences, H-1525 Budapest, P.O. Box 49, Hungary
2011en
ABI

Аннотация

We present a detailed and comprehensive structural study of molecular models of liquid methanol, ethanol, and 1-propanol that originate from a series of reverse Monte Carlo (RMC), molecular dynamics (MD), and united-atom Monte Carlo (UA:MC) simulations. We compare several modeling approaches: RMC simulations that employ experimental neutron and X-ray diffraction data as sole constraints, RMC with diffraction data complemented with partial radial distribution functions (PRDFs) from MD or UA:MC, and conventional MD and UA:MC simulations. The assessment is done in view of the structural parameters of the hydrogen bond and resulting morphological characteristics of molecular aggregates. To achieve these tasks, a computer program for structural analysis of molecular configurations together with the appropriate aggregate classification scheme has been developed. We have analyzed the morphology of clusters, their probability, and size distributions. Any cyclic structures that appeared in the configurations were extracted and characterized in the same manner. We found that MD and UA:MC simulations resulted in configurations with bulkier, more threadlike aggregates that were not entirely consistent with the experimental evidence from diffraction experiments. A combination of neutron and X-ray diffraction data with PRDFs from MD simulations, simultaneously applied as constraints in the RMC procedure, proved to be a modeling approach with the most conclusive results.

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