Wang Jianwei, Ghosh Dipta B, Zhang Zelong
Department of Geology and Geophysics, Center for Computation and Technology, Louisiana State University, Baton Rouge, LA 70803, USA.
Department of Geology and Geophysics, Louisiana State University, Baton Rouge, LA 70803, USA.
Materials (Basel). 2023 Jul 13;16(14):4985. doi: 10.3390/ma16144985.
Ceramic waste forms are designed to immobilize radionuclides for permanent disposal in geological repositories. One of the principal criteria for the effective incorporation of waste elements is their compatibility with the host material. In terms of performance under environmental conditions, the resistance of the waste forms to degradation over long periods of time is a critical concern when they are exposed to natural environments. Due to their unique crystallographic features and behavior in nature environment as exemplified by their natural analogues, ceramic waste forms are capable of incorporating problematic nuclear waste elements while showing promising chemical durability in aqueous environments. Recent studies of apatite- and hollandite-structured waste forms demonstrated an approach that can predict the compositions of ceramic waste forms and their long-term dissolution rate by a combination of computational techniques including machine learning, first-principles thermodynamics calculations, and modeling using kinetic rate equations based on critical laboratory experiments. By integrating the predictions of elemental incorporation and degradation kinetics in a holistic framework, the approach could be promising for the design of advanced ceramic waste forms with optimized incorporation capacity and environmental degradation performance. Such an approach could provide a path for accelerated ceramic waste form development and performance prediction for problematic nuclear waste elements.
陶瓷废物固化体旨在固定放射性核素，以便在地质处置库中永久处置。有效掺入废物元素的主要标准之一是它们与主体材料的兼容性。就环境条件下的性能而言，当废物固化体暴露于自然环境时，其长期抗降解能力是一个关键问题。由于其独特的晶体学特征以及在自然环境中的行为（以其天然类似物为例），陶瓷废物固化体能够掺入有问题的核废物元素，同时在水环境中表现出良好的化学耐久性。最近对磷灰石和钡硬锰矿结构的废物固化体的研究展示了一种方法，该方法可以通过包括机器学习、第一性原理热力学计算以及基于关键实验室实验使用动力学速率方程进行建模等计算技术的组合，预测陶瓷废物固化体的组成及其长期溶解速率。通过在一个整体框架中整合元素掺入和降解动力学的预测，该方法对于设计具有优化掺入能力和环境降解性能的先进陶瓷废物固化体可能很有前景。这样一种方法可以为加速陶瓷废物固化体的开发以及对有问题的核废物元素的性能预测提供一条途径。
