Density Functional Theory (DFT) has over the years become the method of choice for quantitative modeling of complex chemical reactions. Due to the high computational demands, systems of choice are however always limited to a few number of molecules, rendering it impossible to simulate realistic mesoscopic systems as e.g. chemical reactions in liquid environments. Implicit, continuum models therefore coarse-grain all but the relevant solute's degrees of freedom and parameterize the environment-solute interactions based on pure electrostatics and in order to get the correct experimentally measured thermodynamic averages. Among the range of continuum embedding techniques, Poisson-Boltzmann (PB) methods have received considerable interest due to their ability to also model ionic distributions. Ion effects are known to have a crucial impact on chemical stability, geometries or dissociation constants in various systems ranging from biology to catalysis. Recently, we have therefore developed a coupled PB-DFT approach optimally suited for evaluating the influence of electrolytes on chemical reactions.<br/>Although PB methods have been extensively applied, generally applicable paramerization procotols are lacking so far. We therefore collected a large training set of neutral organic molecules and corresponding experimentally measured Setschenow coefficients probing the stability change of these solutes with respect to varying ionic strength. Using this data, we show that with a slight modification of the original PB model in terms of a Stern or ion exclusion layer parameterized as a function of the solute's electron density, good general agreement with experimental results can be obtained for different alkali halide aqueous solutions and present first interesting applications.

How to model chemical reactions in electrolytes?

253rd National Meeting (2017)

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