Tracing the impact of stack configuration on interface resistances in reverse electrodialysis by in situ electrochemical impedance spectroscopy

Wenjuan Zhang, Bo Han, Ramato Ashu Tufa, Chuyang Tang, Xunuo Liu, Ge Zhang, Jing Chang, Rui Zhang, Rong Mu, Caihong Liu, Dan Song, Junjing Li, Jun Ma, Yufeng Zhang

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Front. Environ. Sci. Eng. ›› 2022, Vol. 16 ›› Issue (4) : 46. DOI: 10.1007/s11783-021-1480-9
RESEARCH ARTICLE
RESEARCH ARTICLE

Tracing the impact of stack configuration on interface resistances in reverse electrodialysis by in situ electrochemical impedance spectroscopy

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Highlights

• RED performance and stack resistance were studied by EIS and LSV.

• Interface resistance were discriminated from Ohmic resistance by EIS.

• Impacts of spacer shadow effect and concentration polarization were analyzed.

• Ionic short current reduced the power density for more cell pairs.

• The results enabled to predict RED performance with different configurations.

Abstract

Reverse electrodialysis (RED) is an emerging membrane-based technology for the production of renewable energy from mixing waters with different salinities. Herein, the impact of the stack configuration on the Ohmic and non-Ohmic resistances as well as the performance of RED were systematically studied by using in situ electrochemical impedance spectroscopy (EIS). Three different parameters (membrane type, number of cell pairs and spacer design) were controlled. The Ohmic and non-Ohmic resistances were evaluated for RED stacks equipped with two types of commercial membranes (Type I and Type II) supplied by Fujifilm Manufacturing Europe B.V: Type I Fuji membranes displayed higher Ohmic and non-Ohmic resistances than Type II membranes, which was mainly attributed to the difference in fixed charge density. The output power of the stack was observed to decrease with the increasing number of cell pairs mainly due to the increase in ionic shortcut currents. With the reduction in spacer thickness from 750 to 200 µm, the permselectivity of membranes in the stack decreased from 0.86 to 0.79 whereas the energy efficiency losses increased from 31% to 49%. Overall, the output of the present study provides a basis for understanding the impact of stack design on internal losses during the scaling-up of RED.

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Keywords

Reverse electrodialysis / Electrochemical impedance spectroscopy / Concentration polarization / Spacer shadow effect

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Wenjuan Zhang, Bo Han, Ramato Ashu Tufa, Chuyang Tang, Xunuo Liu, Ge Zhang, Jing Chang, Rui Zhang, Rong Mu, Caihong Liu, Dan Song, Junjing Li, Jun Ma, Yufeng Zhang. Tracing the impact of stack configuration on interface resistances in reverse electrodialysis by in situ electrochemical impedance spectroscopy. Front. Environ. Sci. Eng., 2022, 16(4): 46 https://doi.org/10.1007/s11783-021-1480-9

References

[1]
Bason S, Oren Y, Freger V (2007). Characterization of ion transport in thin films using electrochemical impedance spectroscopy: II: Examination of the polyamide layer of RO membranes. Journal of Membrane Science, 302(1–2): 10–19
CrossRef Google scholar
[2]
Cen J, Vukas M, Barton G, Kavanagh J, Coster H G L (2015). Real time fouling monitoring with Electrical Impedance Spectroscopy. Journal of Membrane Science, 484: 133–139
CrossRef Google scholar
[3]
Daniilidis A, Vermaas D A, Herber R, Nijmeijer K (2014). Experimentally obtainable energy from mixing river water, seawater or brines with reverse electrodialysis. Renewable Energy, 64: 123–131
CrossRef Google scholar
[4]
Długołęcki P, Anet B, Metz S J, Nijmeijer K, Wessling M (2010a). Transport limitations in ion exchange membranes at low salt concentrations. Journal of Membrane Science, 346(1): 163–171 doi:10.1016/j.memsci.2009.09.033
[5]
Dlugolecki P, Dabrowska J, Nijmeijer K, Wessling M (2010). Ion conductive spacers for increased power generation in reverse electrodialysis. Journal of Membrane Science, 347(1–2): 101–107
CrossRef Google scholar
[6]
Długołeçki P, Gambier A, Nijmeijer K, Wessling M (2009). Practical potential of reverse electrodialysis as process for sustainable energy generation. Environmental Science & Technology, 43(17): 6888–6894 doi:10.1021/es9009635
Pubmed
[7]
Długołęcki P, Nymeijer K, Metz S, Wessling M (2008). Current status of ion exchange membranes for power generation from salinity gradients. Journal of Membrane Science, 319(1–2): 214–222
CrossRef Google scholar
[8]
Długołęcki P, Ogonowski P, Metz S J, Saakes M, Nijmeijer K, Wessling M (2010b). On the resistances of membrane, diffusion boundary layer and double layer in ion exchange membrane transport. Journal of Membrane Science, 349(1–2): 369–379
CrossRef Google scholar
[9]
Fontananova E, Messana D, Tufa R A, Nicotera I, Kosma V, Curcio E, Van Baak W, Drioli E, Di Profio G (2017). Effect of solution concentration and composition on the electrochemical properties of ion exchange membranes for energy conversion. Journal of Power Sources, 340: 282–293
CrossRef Google scholar
[10]
Gao H, Zhang B, Tong X, Chen Y (2018). Monovalent-anion selective and antifouling polyelectrolytes multilayer anion exchange membrane for reverse electrodialysis. Journal of Membrane Science, 567: 68–75
CrossRef Google scholar
[11]
Güler E, Van Baak W, Saakes M, Nijmeijer K (2014). Monovalent-ion-selective membranes for reverse electrodialysis. Journal of Membrane Science, 455: 254–270
CrossRef Google scholar
[12]
Gurreri L, Tamburini A, Cipollina A, Micale G, Ciofalo M (2013). CFD Simulation of Mass Transfer Phenomena in Spacer Filled Channels for Reverse Electrodialysis Applications. Icheap-11: 11th International Conference on Chemical and Process Engineering, Pts 1–4, 32: 1879–1884 doi: 10.3303/cet1332314
[13]
Ho J S, Low J H, Sim L N, Webster R D, Rice S A, Fane A G, Coster H G L (2016). In-situ monitoring of biofouling on reverse osmosis membranes: Detection and mechanistic study using electrical impedance spectroscopy. Journal of Membrane Science, 518: 229–242
CrossRef Google scholar
[14]
Jande Y A C, Kim W S (2014). Integrating reverse electrodialysis with constant current operating capacitive deionization. Journal of Environmental Management, 146: 463–469 doi: 10.1016/j.jenvman.2014.07.039
[15]
Jing Y, Chaplin B P (2016). Electrochemical impedance spectroscopy study of membrane fouling characterization at a conductive sub-stoichiometric TiO2 reactive electrochemical membrane: Transmission line model development. Journal of Membrane Science, 511: 238–249
CrossRef Google scholar
[16]
Kim J, Kim S J, Kim D K (2013). Energy harvesting from salinity gradient by reverse electrodialysis with anodic alumina nanopores. Energy, 51: 413–421
CrossRef Google scholar
[17]
Mehdizadeh S, Yasukawa M, Abo T, Kakihana Y, Higa M (2019). Effect of spacer geometry on membrane and solution compartment resistances in reverse electrodialysis. Journal of Membrane Science, 572: 271–280
CrossRef Google scholar
[18]
Pattle R E (1954). Production of electric power by mixing fresh and salt water in the hydroelectric pile. Nature, 174(4431): 660
CrossRef Google scholar
[19]
Post J W, Hamelers H V M, Buisman C J N (2009). Influence of multivalent ions on power production from mixing salt and fresh water with a reverse electrodialysis system. Journal of Membrane Science, 330(1–2): 65–72
CrossRef Google scholar
[20]
Rijnaarts T, Moreno J, Saakes M, De Vos W M, Nijmeijer K (2019). Role of anion exchange membrane fouling in reverse electrodialysis using natural feed waters. Colloids and Surfaces. A, Physicochemical and Engineering Aspects, 560: 198–204
CrossRef Google scholar
[21]
Tedesco M, Scalici C, Vaccari D, Cipollina A, Tamburini A, Micale G (2016). Performance of the first reverse electrodialysis pilot plant for power production from saline waters and concentrated brines. Journal of Membrane Science, 500: 33–45
CrossRef Google scholar
[22]
Tufa R A, Curcio E, Van Baak W, Veerman J, Grasman S, Fontananova E, Di Profio G (2014). Potential of brackish water and brine for energy generation by salinity gradient power-reverse electrodialysis (SGP-RE). RSC Advances, 4(80): 42617–42623
CrossRef Google scholar
[23]
Tufa R A, Hnát J, Němeček M, Kodým R, Curcio E, Bouzek K (2018a). Hydrogen production from industrial wastewaters: An integrated reverse electrodialysis—Water electrolysis energy system. Journal of Cleaner Production, 203: 418–426
CrossRef Google scholar
[24]
Tufa R A, Pawlowski S, Veerman J, Bouzek K, Fontananova E, Di Profio G, Velizarov S, Goulão Crespo J, Nijmeijer K, Curcio E (2018b). Progress and prospects in reverse electrodialysis for salinity gradient energy conversion and storage. Applied Energy, 225: 290–331
CrossRef Google scholar
[25]
Veerman J, De Jong R M, Saakes M, Metz S J, Harmsen G J (2009a). Reverse electrodialysis: Comparison of six commercial membrane pairs on the thermodynamic efficiency and power density. Journal of Membrane Science, 343(1–2): 7–15
CrossRef Google scholar
[26]
Veerman J, Post J W, Saakes M, Metz S J, Harmsen G J (2008). Reducing power losses caused by ionic shortcut currents in reverse electrodialysis stacks by a validated model. Journal of Membrane Science, 310(1–2): 418–430
CrossRef Google scholar
[27]
Veerman J, Saakes M, Metz S J, Harmsen G J (2009b). Reverse electrodialysis: Performance of a stack with 50 cells on the mixing of sea and river water. Journal of Membrane Science, 327(1–2): 136–144
CrossRef Google scholar
[28]
Veerman J, Saakes M, Metz S J, Harmsen G J (2011). Reverse electrodialysis: A validated process model for design and optimization. Chemical Engineering Journal, 166(1): 256–268
CrossRef Google scholar
[29]
Vermaas D A, Saakes M, Nijmeijer K (2011). Power generation using profiled membranes in reverse electrodialysis. Journal of Membrane Science, 385–386: 234–242
CrossRef Google scholar
[30]
Vermaas D A, Saakes M, Nijmeijer K (2014). Enhanced mixing in the diffusive boundary layer for energy generation in reverse electrodialysis. Journal of Membrane Science, 453: 312–319
CrossRef Google scholar
[31]
Wang X, Li N, Li J, Feng J, Ma Z, Xu Y, Sun Y, Xu D, Wang J, Gao X, Gao J (2019). Fluoride removal from secondary effluent of the graphite industry using electrodialysis: Optimization with response surface methodology. Frontiers of Environmental Science & Engineering, 13(4): 51 doi:10.1007/s11783-019-1132-5
[32]
Xie H, Saito T, Hickner M A (2011). Zeta potential of ion-conductive membranes by streaming current measurements. Langmuir, 27(8): 4721–4727
CrossRef Pubmed Google scholar
[33]
Xue W, Zaw M, An X, Hu Y, Tabucanon S (2020). Sea salt bittern-driven forward osmosis for nutrient recovery from black water: A dual waste-to-resource innovation via the osmotic membrane process. Frontiers of Environmental Science & Engineering, 2020, 14(2): 32doi:10.1007/s11783-019-1211-7
[34]
Zhang B, Hong J G, Xie S, Xia S, Chen Y (2017). An integrative modeling and experimental study on the ionic resistance of ion-exchange membranes. Journal of Membrane Science, 524: 362–369
CrossRef Google scholar
[35]
Zhang W, Ma J, Wang P, Wang Z, Shi F, Liu H (2016a). Investigations on the interfacial capacitance and the diffusion boundary layer thickness of ion exchange membrane using electrochemical impedance spectroscopy. Journal of Membrane Science, 502: 37–47
CrossRef Google scholar
[36]
Zhang W, Wang P, Ma J, Wang Z, Liu H (2016b). Investigations on electrochemical properties of membrane systems in ion-exchange membrane transport processes by electrochemical impedance spectroscopy and direct current measurements. Electrochimica Acta, 216: 110-119
CrossRef Google scholar
[37]
Zhang Y, Liu R, Lang Q, Tan M, Zhang Y (2018). Composite anion exchange membrane made by layer-by-layer method for selective ion separation and water migration control. Separation and Purification Technology, 192: 278–286
CrossRef Google scholar
[38]
Zhu X, He W, Logan B E (2015). Reducing pumping energy by using different flow rates of high and low concentration solutions in reverse electrodialysis cells. Journal of Membrane Science, 486: 215–221
CrossRef Google scholar

Acknowledgements

The authors gratefully acknowledge the financial support from Tianjin Enterprise Science and Technology Commissioner Project (No. 19JCTPJC46900), Tianjin Municipal Education Commission Research Plan Projects (Nos.2018KJ161 and TJPU2k20170112), Tianjin Chengjian University research fund (No. 180501412), the National Key Research and Development Program of China (No. 2018YFC1903203), the Fundamental Research Funds for the Central Universities, China (2020CDJQY-A017), and Chongqing Technological Innovation and Application Development Project (No. cstc2019jscx-tjsbX0002). The work described in this paper was also partially supported by a grant from the Research Grants Council of the Hong Kong Special Administration Region, China (No. C7051-17G). Tao Lei from Metrohm China is also gratefully acknowledged for providing useful information about Metrohm Autolab potensiostat. The financial support of the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Actions IF Grant agreement (No. 748683) is gratefully acknowledged.

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11783-021-1480-9 and is accessible for authorized users.

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