Sorption Behavior of Radionuclides on Engineered and Natural Barriers and Prediction of Sorption Distribution Coefficients Using Support Vector Regression

Abstract

A low- and intermediate-level radioactive waste repository contains various types of radionuclides and organic complexing agents. Their chemical interaction within the repository can lead to the formation of radionuclide-ligand complexes, influencing the limited retention behaviors of radionuclides. This study focuses on the sorption behavior of radionuclides on both engineered (concrete) and natural barriers (sedimentary rock and granite), as well as the prediction of sorption distribution coefficients (Kd) using support vector regression. Batch studies were conducted to determine the $K_d$ values for three radionuclides (99Tc, 137Cs, and 238U) under different conditions, including pH, temperature, and the presence of organic ligands (such as ethylenediaminetetraacetic acid, nitrilotriacetic acid, and isosaccharinic acid). The $K_d$ values for 238U exhibited a sharp decrease with increasing concentrations of organic ligands. In contrast, the $K_d$ values for 99Tc showed only a slight reduction at higher organic ligand concentrations. Meanwhile, the $K_d$ values for 137Cs remained relatively unchanged, regardless of the type and initial concentration of organic ligands. This suggests a high level of retention for 137Cs in the rock samples. The support vector regression model with a radial basis kernel function proved effective in predicting the $K_d$ values under different experimental conditions. This enhancement in predicting accuracy contributes valuable insights into understanding the sorption processes involved in radionuclide behavior. Overall, this study advances our knowledge of radionuclide behavior on both engineered and natural barriers while providing a reliable prediction tool for estimating sorption distribution coefficients.