Computational Investigations of Ion Selectivity in Capacitive Deionization from Electronic to Device Scales

Sustainable water treatment requires selective removal of deleterious ions, such as toxic metals and excess salts, while preserving beneficial minerals. Capacitive deionization (CDI), which is a membrane-free electrochemical desalination technology, offers a tunable alternative for targeted ion separation. Achieving high ion selectivity in CDI is, however, challenging as factors such as ion valence, hydrated radius, and hydration energy influence the preferential electrosorption of different ions into charged porous electrodes, making selectivity outcomes hard to predict and control. Theoretical and computational tools are crucial for understanding the selectivity mechanisms in CDI systems and informing the rational design of new materials and devices. However, these models operate at varying length scales, and integrating the insights gained from different scales into a unified multiscale framework still remains a grand challenge. Here, we overview recent advancements in computational modeling of CDI systems, showing how cross-scale insights can guide the design of next-generation CDI systems.