Capability of SCM and RES3T Database for Blind Predictions

The paper presents the general strategy and an example for the current blind predictive capabilities of surface complexation models (SCM) and the respective database RES3T - the "Rossendorf Expert System for Surface and Sorption Thermodynamics"[1]. The approach for the elucidation of numerical data includes the collection of the mineral surface characteristics, the selection of reliable data records, the extrapolation to infinite dilution, the normalization to a reference site density and the averaging of selected thermodynamic data records.
The copper(II) sorption onto goethite was chosen as system illustrating the blind predictive capabilities. To keep the number of parameters at a minimum, the Diffuse Double Layer model was selected accounting for electrostatics. The calculations were performed with FITEQL code [2].
The model prediction represents the experimental values for the adsorbed amount of Cu(II), expressed as conventional distribution coefficients KD as required by most performance assessment software, within one order of magnitude or better.