Molecular-to-Systems Scale Design of Diafiltration Cascades for Improved Solute Recovery and Purity

Sustainable energy solutions and electrification are driving increased demand for critical minerals; albeit the existing technologies are at odds with the sustainability goals driving increased demand for critical minerals. The small footprint and modular nature of membrane technologies position them well to substitute current technologies as they are able to address the declining concentrations in ores and brines, the variable feed concentrations encountered in recycling, and the environmental issues associated with current separation processes. The success of implementing membranes into these processes’ hinges on the exploration and rapid development of new and existing materials over industrially diverse feed conditions.
In this context, this dissertation establishes new characterization techniques, which address knowledge gaps related to the interfacial processes that govern solute-solute selectivity and the performance of membranes in complex multi-component feeds streams, to advance membrane processes. Guided by the tools of data science, a diafiltration apparatus is developed to inform material and process design by rapidly characterizing membrane performance over a broad range of feed solution compositions. The apparatus is built from the ground up and validated with commercial membranes. One key component of the apparatus is the automation, implemented throughout the data collection and processing, that will become a critical piece towards developing self-driving laboratories. This dissertation subsequently extends the utility of the diafiltration apparatus to systematically characterize the effect of complex feed compositions on solute transport. The characterization of solute transport coupled with the systems scale design of diafiltration cascades highlights opportunities in which membranes can transform the field of separations.

可持续能源解决方案与电气化正推动对关键矿物的需求增长；尽管现有技术与驱动关键矿物需求增长的可持续目标相悖。膜技术的小占地面积和模块化特性使其具备替代现有技术的良好条件，因为它们能够应对矿石和卤水中浓度下降的问题、回收过程中遇到的进料浓度变化，以及现有分离工艺相关的环境问题。将膜应用于这些工艺的成功，取决于在工业多样化进料条件下探索和快速开发新型及现有材料。
在此背景下，本论文建立了新的表征技术，解决了与界面过程相关的知识空白——这些界面过程主导着溶质间选择性和复杂多组分进料流中膜的性能。借助数据科学工具，开发了一种渗滤装置，通过在广泛的进料溶液组成范围内快速表征膜性能，为材料和工艺设计提供信息。该装置从头构建，并通过商用膜验证。装置的关键组件之一是贯穿数据采集和处理的自动化，这将成为开发自动驾驶实验室的关键部分。随后，本论文扩展了渗滤装置的用途，系统地表征复杂进料组成对溶质传输的影响。溶质传输表征与渗滤级联的系统级设计相结合，凸显了膜技术能够变革分离领域的机遇。