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• W2186250487 abstract "The paper presents examples illustrating the current blind predictive capabilities of surface complexation models (SCM) and respective databases. High-quality experimental sorption data sets were used as provided by Phase II of the Nuclear Energy Agency (NEA) Sorption Project for its fitting assessment efforts. The systems covered are Np(V) sorption onto hematite, U(VI) sorption onto quartz and Se sorption onto goethite. To keep the number of parameters at a minimum, the Diffuse Double Layer model was selected to account for electrostatics. All calculations were performed with the FITEQL code, version 3.2 [1]. Based on the information in the sorption database RES³T [2] for the above minerals and chemically similar phases, first a set of relevant species was formed. Then respective surface complexation parameters were taken from RES³T: the binding site density for the minerals, the surface protolysis constants, and the brutto stability constants for all relevant surface complexes. To be able to compare and average thermodynamic constants originating from different sources, the normalization concept as introduced by Kulik [3] was applied. Lacking data was substituted by estimates exploiting chemical analogy. The only system-specific parameters directly going into the computations were the solid-liquid ratio and the specific surface area. The model prediction almost always represented the experimental values for the sorbed amount of Np, U and Se within one order of magnitude or better, provided an adequate chemical system was assumed. There, sorption was expressed as conventional distribution coefficients KD as required by most performance assessment (PA) software. Further improvements may arise from a broader data base eliminating the need for data estimations through chemical analogies." @default.
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• W2186250487 date "2004-01-01" @default.
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• W2186250487 title "CAPABILITY OF SURFACE COMPLEXATION MODELS AND DATABASES FOR PREDICTING RADIONUCLIDE SORPTION" @default.
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