Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 451107
Title How to mix molecules with mathematics
Author(s) Molenaar, J.; Hof, B. van 't; Ros, L.; Zaal, M.
Source In: Proceedings of the Sixty-Seventh European Study Group Mathematics with Industry, 26-30 January 2009, Wageningen, The Netherlands. - - p. 47 - 65.
Event Proceedings of the Sixty-Seventh European Study Group Mathematics with Industry, Wageningen, The Netherland, 2009-01-26/2009-01-30
Department(s) Biometris (WU MAT)
PE&RC
Publication type Contribution in proceedings
Publication year 2009
Abstract In this paper we develop two methods to calculate thermodynamic properties of mixtures. Starting point are the basic assumptions that also form the basis for the COSMO-RS model. In this approach, the individual molecules are represented by their geometrical shape with an electrical charge density on their surfaces. Next, the surface is split up into surface segments each with its own charge. In COSMO-RS a strong reduction is introduced by treating the segments as if they are completely independent. In the present study we take into account that the coupling between two patches is essentially dependent on the charge distribution on neighboring segments and on the local geometrical structure of the surface. Two approaches are followed. The first one points out how the model equations, which comprise the optimization of the entropy and conservation of internal energy, can efficiently be solved in general, thus also if the dependency between segments and the local geometry is included in the expression for the coupling energy between segments. In the second method the configuration with maximal entropy and prescribed energy is sought via simulation. Successive molecular configurations of the mixture are simulated and updated via a genetic algorithm to optimize the entropy. The second method is more time consuming but very general.
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