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.