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dc.contributor.authorGómez Coma, Lucía 
dc.contributor.authorOrtiz Martínez, Víctor Manuel
dc.contributor.authorCarmona del Río, Francisco Javier
dc.contributor.authorPalacio Martínez, Laura
dc.contributor.authorPrádanos del Pico, Pedro
dc.contributor.authorFallanza Torices, Marcos 
dc.contributor.authorOrtiz Sainz de Aja, Alfredo 
dc.contributor.authorIbáñez Mendizábal, Raquel 
dc.contributor.authorOrtiz Uribe, Inmaculada 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2020-03-19T15:04:52Z
dc.date.issued2019-12-15
dc.identifier.issn0376-7388
dc.identifier.issn1873-3123
dc.identifier.otherCTQ2015-66078-Res_ES
dc.identifier.otherCTM2017-87850-Res_ES
dc.identifier.urihttp://hdl.handle.net/10902/18411
dc.description.abstractThe prospects and potential of Reverse Electrodialysis (RED) for energy harvesting from natural streams with salinity gradient demand more in-depth studies to understand and overcome the limitations posed by divalent ions. Power performance is greatly influenced by the ionic resistance displayed by the alternating cation and anion exchange membranes (CEMs and AEMs, respectively) housed in RED stacks, which in turn is determined by the type and concentration of ions and counter-ions in the water streams. The effects of divalent ions on power output have been experimentally approached in several works by using real or synthetic water. However, the development of comprehensive models including the effect of divalent ions on membrane resistance and power performance under different scenarios is still very scarce. Thus, this work investigates experimentally the effect of ion species on membrane resistance, providing for the first time mathematical correlations useful to predict power performance in RED stacks under a wide range of compositions of salinity gradient solutions. To this end, electrochemical impedance spectroscopy (EIS) measurements have been performed for CEM and AEM commercial membranes in contact with different concentration of NaCl solutions and including different mixtures of divalent ions (Ca2+, Mg2+, SO42). These correlations have been implemented in a previously developed model to determine power outputs as function of ion mixture compositions. Scenarios of general interest for RED practical implementation have been addressed; specifically, solutions with a composition representative of seawater or high salinity brines have been studied as high concentration solutions (HCS) and, on the other hand, typical concentrations of wastewater treatment plant effluents, river water or brackish water from desalination plants were used as low concentration solutions (LCS).es_ES
dc.description.sponsorshipThe authors want to acknowledge financial support from the Community of Cantabria - Regional Plan through the project: Gradisal “RM16-XX-046-SODERCAN/FEDER”, the projects funded by the Spanish Ministry of Economy and Competitiveness CTQ2015-66078-R, and CTM2017-87850-R and the project “HYLANTIC”- EAPA_204/2016, which is co-financed by the European Regional Development Fund in the framework of the Interreg Atlantic program. V.M. Ortiz-Martínez is supported by the Spanish Ministry of Science, Innovation and Universities (grant ‘Juan de la Cierva-Formación’ ref. FJCI-2017-32404).es_ES
dc.format.extent23 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 licensees_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceJournal of Membrane Science, 2019, 592, 117385es_ES
dc.subject.otherSalinity gradient energyes_ES
dc.subject.otherReverse electrodialysis (RED)es_ES
dc.subject.otherMathematical modeles_ES
dc.subject.otherIon exchange membrane resistancees_ES
dc.subject.otherDivalent ionses_ES
dc.titleModeling the influence of divalent ions on membrane resistance and electric power in reverse electrodialysises_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.memsci.2019.117385es_ES
dc.rights.accessRightsembargoedAccesses_ES
dc.identifier.DOI10.1016/j.memsci.2019.117385
dc.type.versionacceptedVersiones_ES
dc.date.embargoEndDate2021-12-15


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© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 licenseExcept where otherwise noted, this item's license is described as © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license