Use of Multi-Dimensional Sorption Data-Sets to Constrain Models of Radionuclide-Solid Interactions
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Use of Multi-Dimensional Sorption Data-Sets to Constrain Models of Radionuclide-Solid Interactions T. E. Payne1, T. D. Waite2 and G.R. Lumpkin1 1 Australian Nuclear Science and Technology Organisation, PMB 1, Menai 2234, Australia 2 School of Civil and Environmental Engineering, University of New South Wales, Sydney 2052, Australia ABSTRACT In order to adequately constrain surface complexation models for radionuclide sorption, large ‘multi-dimensional’ data-sets, showing the dependence of sorption on numerous experimental parameters, are required. This paper describes how large sorption databases were used to develop surface complexation models of U(VI) uptake on kaolinite and ferrihydrite. It is shown that the shape of U uptake curves as a function of pH and total U (ΣU) can be used to distinguish between U adsorption and the precipitation of amorphous uranyl hydroxide. The U sorption data-set obtained in this work also includes the effects of several complexing ligands, including phosphate. The dependence of U uptake on these variables can be used to assess the formation of various types of surface complexes (including ternary surface complexes) and the possibility of precipitation reactions. Adsorption experiments with different sorbing materials were also useful in developing models for U sorption and for excluding some possible surface and precipitation reactions. This study shows how combining multi-dimensional sorption databases with advanced spectroscopic or microscopic techniques (such as EXAFS or AEM) can lead to improved models of interactions at mineral-water interfaces. INTRODUCTION Models of radionuclide sorption are important tools for predicting the migration of radionuclides in the environment. However, the predictive capability of these models is limited if the experimental data used to construct the models are only obtained over a limited range of conditions, or by varying only a small number of experimental parameters. For example, a model derived from a sorption ‘isotherm’ (where sorption is studied as a function of total radionuclide concentration) may not provide any predictive capability if another parameter, such as the pH, is varied. To adequately constrain sorption models, large ‘multi-dimensional’ data-sets, showing the dependence of sorption on numerous experimental parameters, are required. These parameters should include pH, ionic strength and radionuclide concentration, and preferably other variables such as the concentration of complexing ligands. This paper describes how multi-parameter data-sets were used to develop models of U(VI) uptake on ferrihydrite and kaolinite, and to distinguish between adsorption and precipitation. While modern solid-phase analytical techniques can sometimes distinguish between these processes, the complex mixture of solid phases and the low concentrations of the radionuclide may prevent characterization of the mode of retention of the radionuclide. Therefore, modelling must be guided by inferences drawn from experiments in which several experimental para
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