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Title: A physics-based mesoscale phase-field model for predicting the uptake kinetics of radionuclides in hierarchical nuclear wasteform materials

Journal Article · · Computational Materials Science

Multiscale, hierarchical, porous materials are promising nuclear wasteform materials with potential for efficiently adsorbing and sequestering radionuclides. However, fundamental understanding of such complex micro- and meso- structures on radionuclide diffusion and uptake kinetics is lacking, which is essential for designing advanced nuclear wasteform materials. In this work we developed a microstructural-dependent diffusion model which accounts for three-dimensional (3D) microstructural features, and heterogeneous thermodynamic and kinetic properties to predict the radionuclide uptake kinetics in complex porous structures. Na+ and Sr2+ ionic exchange in LTA zeolite multiscale materials in batch tests is taken as a model system to demonstrate the model and its application in hierarchical materials with multiscale porosity. It is found that the reduction of ionic mobility associated with chemistry, structure and/or phase changes has more profound impact on the uptake kinetics in a large 3D porous particle than that in a small particle. Uptake kinetics in large particles are limited by two diffusion processes, i.e., bulk diffusion and surface layer transport. Decreasing particle size and increasing mesoscale pore volume fraction changes the uptake kinetics from two diffusion processes to a single process and dramatically increase the uptake kinetics. Predicted uptake kinetics and the effect of microstructures on the effective capacity of radionuclides and uptake efficiency are consisted with the results observed in Ba2+ exchange experiments. The results demonstrate that the developed model should be highly adaptable to transport problems in other hierarchical material systems.

Research Organization:
Energy Frontier Research Centers (EFRC) (United States). Center for Hierarchical Waste Form Materials (CHWM); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
DOE Contract Number:
AC05-76RL01830
OSTI ID:
1490317
Report Number(s):
PNNL-SA-137890
Journal Information:
Computational Materials Science, Vol. 159, Issue C; ISSN 0927-0256
Publisher:
Elsevier
Country of Publication:
United States
Language:
English