Библиографическое описание:Design criteria for selective nanofluidic ion-exchange membranes : научное издание / Kostadin V. Petrov [et al.]. - Текст : непосредственный // Journal of Membrane Science. - 2023. - Т. 688, № . - P. 122156. - ISSN 0376-7388, DOI 10.1016/j.memsci.2023.122156.
Аннотация:Polymeric ion-exchange membranes (IEMs) are key to many electrochemical processes, but their intrinsic selectivity limitations restrict scale-up possibilities. Nanofluidic IEMs, based on inorganic rigid materials and charged nanopores, offer a promising alternative. We present design criteria for selective nanofluidic membranes. We used commercial anodized aluminium oxide (AAO) membranes with varying pore sizes to measure permselectivity between different KCl concentrations. Our experiments reveal that membranes with 10-nm pores have permselectivities above 90%, comparable to those of polymeric IEMs, up to electrolyte concentrations of 0.15 vs. 0.75 M. To our knowledge, this is the highest reported ion selectivity for nanofluidic IEMs. Conversely, asymmetric AAO membranes featuring a thin selective layer, exhibited low permselectivity. We explored the influence of other parameters through simulations using the space-charge model. Our numerical results indicate that pore size and surface potential are the most sensitive parameters for increasing selectivity. Additionally, pore length has a minimum requirement for good performance although increasing it beyond the μm scale yields no significant result. This study highlights nanofluidic IEMs as a promising alternative to polymeric IEMs and their capability to improve performance of many electrochemical processes, especially those involving low electrolyte concentrations on at least one membrane side.
Издательство:Elsevier Science Publishing Company, Inc.
Источник:Journal of Membrane Science
Выпуск:Т. 688
Номера страниц:122156
Держатель оригинала документа:Department of Chemical Engineering, Delft University of Technology, 2629 HZ, Delft, the Netherlands, Institute of Computational Modeling SB RAS, Akademgorodok 50-44, 660036, Krasnoyarsk, Russia, Siberian Federal University, Svobodny 79, 660041, Krasnoyarsk, Russia
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