Relationships between Diffusion Properties and Index Tests for Bentonite-Polymer Composites

Bentonite-polymer composites (BPC) have been developed for use in waste and chemical containment applications where barriers comprising traditional sodium bentonite (NaB) are likely to undergo adverse chemical interactions that degrade barrier performance. Previous research has indicated BPC can maintain low hydraulic conductivity, k (e.g., k < 10⁻¹⁰ m/s) even when in contact with solutions of high ionic strength, extreme pH, and/or multivalent species, such that diffusion remains the dominant mechanism by which contaminants transport through the barrier. However, diffusion properties of BPC can be highly variable and are not yet fully understood. Further, diffusion testing on BPC can be challenging to perform, limiting available data. In this study, diffusion tests were performed on a range of BPC specimens using calcium chloride (CaCl₂) source solutions to evaluate potential correlations between measured solute diffusion coefficients (D_a) with index test properties that are simpler to measure. The index tests included cation exchange capacity (CEC), liquid limit by fall cone penetration (LL), and active water content (AWC). The four different materials evaluated were all commercial BPCs containing NaB that had been amended (via dry mixing) with either 4% or 8% anionic polymer (by weight). The preliminary results confirmed that index test results may be useful for predicting diffusion behavior of BPC. For example, there was an inverse relationship between D_a and AWC for all materials. However, the best empirical correlations between measured D_a and corresponding BPC index properties (R² ≈ 0.7) were relationships that combined all three parameters (CEC, LL, and AWC). Additional data points are needed to further refine such correlation and will be the focus of subsequent experimental research. The ability to estimate BPC diffusion coefficients from index test results when a diffusion testing program is not feasible can improve the prediction of long-term containment barrier performance and support BPC selection for site-specific conditions.