Simplified Prediction of Ion Removal in Capacitive Deionization of Multi-Ion Solutions

Abstract

Capacitive deionization (CDI) is an upcoming desalination technology being increasingly considered to be a simple and cost-effective solution for brackish water, where electrosorption leads to the removal of charged species from water. Real-world water samples typically contain a multitude of ions that must be considered apart from sodium−chloride salt. In this work, we have developed a method to quantify the competitive adsorption of different ionic species during CDI processes. The method is straightforward, requiring a single calibrating experiment to extract a 'periodic table' of competitiveness scores for all ions present in the experiment. Using a dynamic Langmuir model that was developed by our group, it is shown that these scores could subsequently be used to predict the adsorption of any ion species in a multi-ion solution. Excellent agreement with data from the literature could be achieved with this model, and the method is especially well-suited for trace ions as these can be predicted directly. The derived method is simple and accurate for quantifying and predicting adsorption in multi-ion solutions and could be valuable for predicting the effect when applying CDI to real-world water samples.

Disinfection of Bacteria in Water by Capacitive Deionization

“…Ions with a higher oxidation number were adsorbed more effectively as they present a more energetically favorable option for screening the electrode surface charge (Hou and Huang, 2013 ; Li et al, 2016 ). However, when the charge on the ions was similar, the absolute concentrations took precedence, wherein ions with higher concentration like Na + are electrosorbed to a larger extent as compared to ions with lower concentrations like K + ( Table 1 ) (Nordstrand and Dutta, 2020 ). In addition to E. coli , the groundwater contains other bacterial species, such as Bacillus spp., Shigella spp., Vibrio spp., Klugiella spp., Coccus spp., and Polynucleobacter spp.…”

“…Thus, ionic species can have both a positive and negative effect on microbial neutralization. Figure 4A shows that the initial fast conductivity transition period (period 1) has the highest mass transfer rate of ions toward the electrode surface (Demirer et al, 2013 ), which reduces with time as the electrode approaches saturation (Nordstrand and Dutta, 2019 , 2020 ). The lower quantity of live bacterial cells in period 1 ( Figure 4B ) is plausible as the electric field strength between the CDI device electrodes is the strongest during period 1.…”

Basis and Prospects of Combining Electroadsorption Modeling Approaches for Capacitive Deionization

“…These fundamental equations have been shown to accurately model the charge storage and ion adsorption over varying concentrations and voltages. The full DL model, as derived elsewhere [13,19,20], has also been able to predict performance for multi-ion systems [20] and adsorption over time [19].…”

“…Modeling of CDI processes has evolved in different directions [9,[12][13][14][15], wherein models consider the same underlying physics but with widely varying Herein, we discuss the underlying model-independent physics governing electroadsorption. Primarily, this is used as a starting point for comparing the approaches and tools used in three different CDI models: the modified Donnan (mD) model [7][8][9][16][17][18], the Randles circuit [12], and the dynamic Langmuir (DL) model [13,19,20]. Crucially, we add value by discussing how tools used in the respective models could be implemented to enhance the other models.…”

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

“…In a recent study, we used a dynamic Langmuir (DL) 39 , 40 model to develop a metric for ion competitiveness in CDI. 41 A single experiment could be performed to extract a “periodic table” of competitiveness scores for all ions in the calibration solution at equilibrium, and the method made it possible to not only rank the comparative adsorption of different ions but also quantitatively predict it. A fundamental finding that allowed the predictions was that the relative adsorption of ionic species is proportional to their relative concentration.…”