WORCESTER BOSCH SET OF ELECTRODES 87186643010

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In summary, the use of various electrode material, operational conditions, and surface modifications for selective ion separation was reviewed in this section. Thus, it is evident that electrodes can act as selective elements in CDI processes. In the following section, we will review the use of membranes for selective ion separation in CDI. 3. Membranes for ion selectivity In the previous section, ion selectivity in terms of electrodes was discussed. The use of membranes also plays a vital role in CDI. This section is dedicated for exploring the studies which rely on membranes for achieving ion selectivity. 3.1 Cation selectivity Several different studies have demonstrated the advantages of using IEMs to prevent co-ion repulsion, reduce anode oxidation, and to boost the salt removal by employing gradient of solutions in multi-chamber cells. 7,114 An IEM can also be used as a barrier for specific ions, and therefore, improve the ion selectivity. Y. Gao, L. Pan, H. B. Li, Y. Zhang, Z. Zhang, Y. Chen and Z. Sun, Thin Solid Films, 2009, 517, 1616–1619 CrossRef CAS. which is set up and solved at each coordinate twice, first for i = Na + with j = K + and second for the reverse situation. In this equation, parameter V T is the thermal voltage given by V T = RT/ F which at room temperature is around 25.6 mV. All other parameter values are given in ESI (Section 7) of Porada et al. 78

P. Srimuk, J. Lee, Ö. Budak, J. Choi, M. Chen, G. Feng, C. Prehal and V. Presser, Langmuir, 2018, 34, 13132–13143 CrossRef CAS.

C. Erinmwingbovo, M. S. Palagonia, D. Brogioli and F. La Mantia, ChemPhysChem, 2017, 18, 917–925 CrossRef CAS.

B. W. Byles, B. Hayes-Oberst and E. Pomerantseva, ACS Appl. Mater. Interfaces, 2018, 10, 32313–32322 CrossRef CAS. Fig. 5 Typical desalination curves of potentiostatic, galvanostatic, and G/P modes in single-pass systems for CDI intended to support a qualitative comparison. To facilitate this comparison further, the potentiostatic mode in batch systems is also presented. Peng Liang is a professor in the School of Environment at Tsinghua University. His research interests include energy and resource recovery from wastewater through microbial electrochemical technologies, capacitive deionization, and autotrophic denitrification. He is now serving as the chair of the international working group for capacitive deionization and electrosorption (CDI&E), founded in 2014 and aims to establish interdisciplinary collaborations towards better understanding and application of CDI&E-related technologies.

Conflicts of Interest

K. Singh, L. Zhang, H. Zuilhof and L. C. P. M. de Smet, Desalination, 2020, 496, 114647 CrossRef CAS. S. Jeon, H. Park, J. Yeo, S. Yang, C. H. Cho, M. H. Han and D. K. Kim, Energy Environ. Sci., 2013, 6, 1471–1475 RSC. In addition to the pore size and morphological characteristics of the electrodes, the valence of the adsorbing ion has an influence on its selectivity. Studies have reported that ions with a higher valence are more effectively adsorbed in the EDL due to their stronger interactions with the electrodes. 25,52,54,55 In a mixture of mono- and divalent ions, at equilibrium the divalent ions were preferably electrosorbed as a result of the higher electrostatic attraction ( Fig. 6A). 56 Gao et al. obtained a higher divalent ion selectivity using carbon nanotube and carbon nanofiber electrodes due to charge-exclusion effect as depicted in ( Fig. 6B). 50 They also stated that ions with smaller hydrated radii were preferred if they have the same valence. Ions with identical valence are electrosorbed according to their hydration energy ( Fig. 6D). Thus, ions with lower hydration energy are preferred as their hydration shell can be readily rearranged inside the pores. 57 An ability to predict ion-selectivity will help streamline the efforts being made in this field of CDI, enhancing the strength of the technology to remove ions selectively. Our work takes a step in this direction by putting forward a theory, at the system level, for prediction of ion-selectivity of a class of intercalation electrodes. A logical next step is the investigation of the molecular origins for the preference of electrode materials towards different ions. Further insight into the mechanism of preferential electrosorption of ions can help to tune the selectivity-inducing properties of the electrode material. Hawks et al. 41 carried out molecular dynamics (MD) simulations to elucidate the selective adsorption of NO 3 − over Cl − and SO 4 2− in carbon electrodes. This simulation assisted the authors to understand how hydration of the ions influenced the anion selectivity in very narrow micropores. According to the MD simulations, nitrate and chloride have similar hydration energies, much lower than sulfate, which suggests that sulfate is less prone to rearrange its solvation shell to fit inside of the micropores. At the same time, the higher selectivity of nitrate over chloride is explained by the higher distribution of the water molecules on the equatorial region rather than the perpendicular region of nitrate, suggesting that water molecules are weakly bound on the axial region of nitrate. Since NO 3 − has a delocalized water shell, 41 as predicted by MD simulations, the ion is more prone to fit inside of the slit micropores of the investigated activated carbon. For porous carbon materials, the use of MD simulations can be extended to several other ions, which allows one to predict the ion selectivity based on the surface characteristics of the electrode material. At each x-coordinate, the relationship between electrode potential ϕ e, solution potential ϕ mA and occupancy of a cation in the IHC, ϑ i, is implemented. This is given by the extended Frumkin equation eqn (12) for binary mixtures, 78

Modification of the electrode surface by adding functional surface groups is another approach to enhance the anion selectivity, as similarly observed in terms of cations ( Fig. 6E). Oyarzun et al. modified the carbon electrode surface with cetyltrimethylammonium bromide (CTAB) and sodium dodecylbenzenesulfonate (SDBS) to obtain a higher selectivity towards nitrate via inverse CDI (i-CDI). 76 The process of i-CDI can occur when the surface of the electrode is covered with functional surface groups. Therefore, during charging at high voltages, there is discharge of ions, while at lower voltages, there is adsorption of ions. The surface modification preferentially adsorbed nitrate by a factor of ≈7.7 over chloride. However, when using the i-CDI process, the selectivity was reduced to 6.5 at low cell voltages, 16% lower than the value observed for adsorption. Interestingly, the authors did not observe strong differences in the selectivity by varying the chloride ion concentration while keeping the nitrate ion concentration constant. Apart from more commonly targeted alkali and alkaline-earth metals, selective removal of heavy metals has also been of interest in CDI. In 2010, Li et al. utilized electrodes made of graphene nanoflakes to remove Fe 3+ and compared the electrosorption capacity with Mg 2+, Ca 2+, and Na + in single-salt experiments. 61 The Fe 3+ were preferred over the others, which was attributed to its higher valence ( Fig. 6A). Between Ca 2+ and Mg 2+, Ca 2+ were preferred due to their smaller hydrated radii ( Fig. 6B), as described before, whereas Na + exhibited the lowest electrosorption among all. In another study, Huang et al. employed activated carbon electrodes to remove Cu 2+ from aqueous solutions. 62 They also compared the Cu 2+ electrosorption in the presence of NaCl, natural organic matter (NOM), and dissolved reactive silica in binary salt solutions, and reported that Cu 2+ removal decreases with an increasing amount of the competitive species. However, no significant decrease in Cu 2+ electrosorption was observed in the presence of dissolved reactive silica. Formation of an electrical double-layer (EDL) is a fundamental feature of many topics in physics and chemistry, and is also exploited in CDI. The first EDL model, the Helmholtz model, was proposed by Hermann Helmholtz in 1879. This model was later revised by Louis Gouy and David Chapman in 1910 and in 1913, respectively. The Helmholtz model and the Gouy–Chapman model were combined into the widely utilized Gouy–Chapman–Stern (GCS) model by Otto Stern in 1924. 35 Moving forward, research into new electrode materials and chemistries, modification and optimization of existing materials, investigation of parameters in selectivity operation, modeling of selectivity at the system and molecular level, and finally, techno-economic analysis into the viability of selective ion separation via CDI will be crucial for fully realizing the potential of ion-selectivity via CDI. Dynamic calculations by Zhao et al. using porous electrode theory for mono/di cation mixtures, with monovalent anions, showed that an electrode that initially selectively adsorbed monovalent cations, switched to the adsorption of divalent cations and desorption of the adsorbed monovalent cations later in the process, in line with experimental observations. Also, in Zhao et al., Gouy–Chapman–Stern (GCS) theory was used for mono/di cation mixtures containing the same monovalent anion, and combined with a model that describes ion transport to a planar charged wall. This model qualitatively showed the same phenomenon of replacement of monovalent cations by divalent cations during prolonged charging of the electrode. Finally, Zhao et al. summarized relevant equations for the GCS model for the excess ion adsorption in an EDL in mono/di cation mixtures (or, equivalently, for mono/di anion mixtures containing the same monovalent cation). For the GCS model, these equations did not yet exist for a three-ion mixture, and therefore they extended the existing classical expressions for binary ion mixtures, such as mono/di cation mixtures with the same monovalent anion. 143,144 Iglesias et al. 145 combined a simple transport model for mono/di cation mixtures with an mD model, and also combined it with a model based on the Poisson–Boltzmann equation including the permanent fixed charges (their Fig. 4B) to describe ion adsorption. A similar Poisson–Boltzmann calculation including salt mixtures was developed for the reverse of CDI, the controlled mixing of salt and fresh water, by Fernandez et al. 146 and by Jimenez et al. 147 who included ion-volume effects as well.

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S. P. Hong, H. Yoon, J. Lee, C. Kim, S. Kim, J. Lee, C. Lee and J. Yoon, J. Colloid Interface Sci., 2020, 564, 1–7 CrossRef CAS. R. Chen, H. Tanaka, T. Kawamoto, M. Asai, C. Fukushima, H. Na, M. Kurihara, M. Watanabe, M. Arisaka and T. Nankawa, Electrochim. Acta, 2013, 87, 119–125 CrossRef CAS.

S. Porada, R. Zhao, A. van der Wal, V. Presser and P. M. Biesheuvel, Prog. Mater. Sci., 2013, 58, 1388–1442 CrossRef CAS. c i,inf, c i,eff, c j,inf, c j,eff are concentrations ( c) of influent (inf) and effluent (eff) of two competing ions, i and j, respectively. Y. Bian, X. Chen, L. Lu, P. Liang and Z. J. Ren, ACS Sustainable Chem. Eng., 2019, 7, 7844–7850 CrossRef CAS.Broader context Increasing demand of non-renewables and dwindling resources require robust solutions to establish secure supply lines in the immediate future. The ability of capacitive deionization (CDI) to tune the system selectivity towards a particular ion of interest reveals tremendous potential in this endeavor. CDI has exhibited promising and exponential growth in the last two decades. This progress has been inspired by a multitude of motives including new electrodes, membranes, and their surface functionalization, CDI cell architectures, novel applications, and a better understanding of theory and practice. Particularly considering novel applications, CDI has recently deepened its roots in the field of selective ion separation. Ion selectivity is a crucial component in resource recovery, wastewater treatment, as well as ion sensing. Therefore, this work is intended to thoroughly examine the rapid growth of CDI in the field of ion selectivity until the state-of-the-art, and consequently, initiate new research dimensions by bringing forth a new theory of selective ion separation with intercalation materials. where η′ is a modified volume fraction of ions in the pore, which is the real volume fraction η, to which is added an empirical term γα′ which relates to the ion size to pore size ratio. The volume fraction η is given by a summation over all ions in the pore of their concentration in the micropores times the molar volume, i.e., the volume (per mole of ions), which can include the water molecules that are tightly bound to the ion (ion plus hydration shell). For larger ions, the γα′ term is larger, and thus for this ion, Φ exc, i will be lower and it will be excluded from the pores relative to the smaller ion. Though this function is derived from a Carnahan–Starling equation of state, which considers mixtures of ions of the same size, 160 we utilize this simplified expression here to describe a size-based selectivity in mixtures of ions of different sizes. W. Xing, J. Liang, W. Tang, G. Zeng, X. Wang, X. Li, L. Jiang, Y. Luo, X. Li, N. Tang and M. Huang, Chem. Eng. J., 2019, 361, 209–218 CrossRef CAS. A. Omosebi, X. Gao, J. Landon and K. Liu, ACS Appl. Mater. Interfaces, 2014, 6, 12640–12649 CrossRef CAS.