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Issue 5, 2018
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A general strategy to simulate osmotic energy conversion in multi-pore nanofluidic systems

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Abstract

As a type of clean energy resource, salinity gradient power between seawater and river water is important to satisfy the ever-growing energy demand on earth. In the recent years, the use of reverse electrodialysis in biomimetic nanofluidic systems has become a promising way for large-scale and high-efficiency harvesting of the salinity gradient power and surpasses the conventional polymeric ion-exchange membrane-based process. With regard to practical applications, significant efforts have been made towards the design and fabrication of high-performance and economically viable materials and devices. However, while extrapolating from single nanopores to multi-pore membrane materials, the commonly used linear amplification method causes severe deviation from the actual experimental value obtained on nanoporous membranes, particularly at a high pore density. An appropriate simulation method is therefore highly demanded and a great challenge. Herein, we present a general strategy for multi-pore nanofluidic systems by taking the influence of neighbouring nanopores into consideration. We have found that the fourth nearest-neighbor approximation is sufficiently precise for simulation in nanoporous systems. The simulation data are in good agreement with the experimental results. The simulation method provides insights for understanding the pore–pore interaction in porous nanofluidic systems and for the design of high-performance devices.

Graphical abstract: A general strategy to simulate osmotic energy conversion in multi-pore nanofluidic systems

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Publication details

The article was received on 19 Jan 2018, accepted on 17 Feb 2018 and first published on 19 Feb 2018


Article type: Research Article
DOI: 10.1039/C8QM00031J
Citation: Mater. Chem. Front., 2018,2, 935-941
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    A general strategy to simulate osmotic energy conversion in multi-pore nanofluidic systems

    F. Xiao, D. Ji, H. Li, J. Tang, Y. Feng, L. Ding, L. Cao, N. Li, L. Jiang and W. Guo, Mater. Chem. Front., 2018, 2, 935
    DOI: 10.1039/C8QM00031J

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