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Energy harvesting from salinity gradient by reverse electrodialysis with anodic alumina nanopores

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  • Kim, Juwan
  • Kim, Sung Jin
  • Kim, Dong-Kwon

Abstract

Power generation by reverse electrodialysis from anodic alumina nanopores is experimentally investigated by placing an alumina nanopore array with a nominal pore radius of 10 nm between two sodium chloride solutions with various combinations of concentrations. Both bare and silica-coated alumina nanopore arrays are used in the present study. The current–potential characteristics are measured for various electrolyte concentration levels, and the transference number and the electrical conductance of the nanopore arrays are obtained from these characteristics. The transference numbers of the bare and silica-coated alumina nanopore arrays are 0.30 and 0.72, respectively; these values are nearly independent of the concentration of the sodium chloride solutions when it is less than 200 mM. Therefore, the bare and silica-coated alumina arrays can be used as anion selective and cation selective membranes, respectively, for micro batteries and micro power generators. Finally, power generation by reverse electrodialysis using an alumina nanopore array is presented. The highest power generation measured is 542 nW, which is several orders of magnitude higher than those measured in previous studies based on nanofluidic channels or nanopores.

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  • Kim, Juwan & Kim, Sung Jin & Kim, Dong-Kwon, 2013. "Energy harvesting from salinity gradient by reverse electrodialysis with anodic alumina nanopores," Energy, Elsevier, vol. 51(C), pages 413-421.
    • Handle: RePEc:eee:energy:v:51:y:2013:i:c:p:413-421
    DOI: 10.1016/j.energy.2013.01.019
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    3. Wang, Y. & Wang, H. & Wan, C.Q., 2018. "The effect of colloids on nanofluidic power generation," Energy, Elsevier, vol. 160(C), pages 863-867.
    4. Tamburini, A. & Tedesco, M. & Cipollina, A. & Micale, G. & Ciofalo, M. & Papapetrou, M. & Van Baak, W. & Piacentino, A., 2017. "Reverse electrodialysis heat engine for sustainable power production," Applied Energy, Elsevier, vol. 206(C), pages 1334-1353.
    5. Yunhyun Lee & Hyun Jung Kim & Dong-Kwon Kim, 2020. "Power Generation from Concentration Gradient by Reverse Electrodialysis in Anisotropic Nanoporous Anodic Aluminum Oxide Membranes," Energies, MDPI, vol. 13(4), pages 1-15, February.
    6. Sang Woo Lee & Hyun Jung Kim & Dong-Kwon Kim, 2016. "Power Generation from Concentration Gradient by Reverse Electrodialysis in Dense Silica Membranes for Microfluidic and Nanofluidic Systems," Energies, MDPI, vol. 9(1), pages 1-11, January.
    7. Chanda, Sourayon & Tsai, Peichun Amy, 2019. "Numerical simulation of renewable power generation using reverse electrodialysis," Energy, Elsevier, vol. 176(C), pages 531-543.
    8. Kang, Byeong Dong & Kim, Hyun Jung & Lee, Moon Gu & Kim, Dong-Kwon, 2015. "Numerical study on energy harvesting from concentration gradient by reverse electrodialysis in anodic alumina nanopores," Energy, Elsevier, vol. 86(C), pages 525-538.
    9. Abbasi-Garravand, Elham & Mulligan, Catherine N. & Laflamme, Claude B. & Clairet, Guillaume, 2016. "Role of two different pretreatment methods in osmotic power (salinity gradient energy) generation," Renewable Energy, Elsevier, vol. 96(PA), pages 98-119.
    10. Jiao, Yanmei & Yang, Chun & Zhang, Wenyao & Wang, Qiuwang & Zhao, Cunlu, 2024. "A review on direct osmotic power generation: Mechanism and membranes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    11. Tan, Guangcai & Xu, Nan & Gao, Dingxue & Zhu, Xiuping, 2022. "Superabsorbent graphene oxide/carbon nanotube hybrid Poly(acrylic acid-co-acrylamide) hydrogels for efficient salinity gradient energy harvest," Energy, Elsevier, vol. 258(C).
    12. Bevacqua, M. & Tamburini, A. & Papapetrou, M. & Cipollina, A. & Micale, G. & Piacentino, A., 2017. "Reverse electrodialysis with NH4HCO3-water systems for heat-to-power conversion," Energy, Elsevier, vol. 137(C), pages 1293-1307.
    13. Long, Rui & Li, Baode & Liu, Zhichun & Liu, Wei, 2018. "Reverse electrodialysis: Modelling and performance analysis based on multi-objective optimization," Energy, Elsevier, vol. 151(C), pages 1-10.

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