Predicting and Enhancing the Ion Selectivity in Multi-Ion Capacitive Deionization.

Lack of potable water in communities across the globe is a serious humanitarian problem promoting the desalination of saline water (seawater and brackish water) to meet the growing demands of human civilization. Multiple ionic species can be present in natural water sources in addition to sodium chloride, and capacitive deionization (CDI) is an upcoming technology with the potential to address these challenges because of its efficacy in removing charged species from water by electro-adsorption. In this work, we have investigated the effect of device operation on the preferential removal of different ionic species. A dynamic Langmuir (DL) model has been a starting point for deriving the theory, and the model predictions have been validated using data from reports in the literature. Crucially, we derive a simple relationship between the adsorption of different ionic species for short and long adsorption periods. This is leveraged to directly predict and enhance the selective ion removal in CDI. Furthermore, we demonstrate an example of how this selectivity could reduce excess removal of ions to avoid remineralization needs. In conclusion, the method could be valuable for predicting the impact of improved device operation on capacitive deionization with multi-ion compositions prevalent in natural water sources.