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Performance metrics for nanofiltration-based selective separation for resource extraction and recovery

Nature Water volume 1, pages 291–300 (2023)Cite this article

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An Author Correction to this article was published on 16 October 2023

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Abstract

Membrane filtration has been widely adopted in various water treatment applications, but its use in selective solute separation for resource extraction and recovery is an emerging research area. When a membrane process is applied for solute–solute separation to extract solutes as the product, the performance metrics and process optimization strategies should differ from a membrane process for water production because the separation goals are fundamentally different. Here we used lithium (Li) magnesium (Mg) separation as a representative solute–solute separation to illustrate the deficiency of existing performance evaluation framework developed for water–solute separation using nanofiltration (NF). We performed coupon- and module-scale analyses of mass transfer to elucidate how membrane properties and operating conditions affect the performance of Li/Mg separation in NF. Notably, we identified an important operational trade-off between Li/Mg selectivity and Li recovery, which is critical for process optimization. We also established a new framework for evaluating membrane performance based on the success criteria of Li purity and recovery and further extended this framework to separation with the target ions in the brine. This analysis lays the theoretical foundation for performance evaluation and process optimization for NF-based selective solute separation.

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Fig. 1: NF-based solute–solute separation and success criteria.
Fig. 2: Summary of membrane performance for NF-based Li/Mg separation.
Fig. 3: Application of the SDEM model to describe NF-based Li/Mg separation.
Fig. 4: Representative results from module-scale modelling of NF-based Li/Mg separation.
Fig. 5: Trade-off between Li selectivity and recovery in NF-based Li/Mg separation.
Fig. 6: Performance metrics of NF membrane for Li/Mg separation (with either permeate or retentate as the product).

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Data availability

Source data are provided with the paper. Source data for figures are in Excel format (.xlsx) and also available publicly via https://doi.org/10.6084/m9.figshare.21944408.

Code availability

The code for generating Fig. 4 in the manuscript is available publicly via the following link: https://github.com/ruoyuwang16/NATWATER-22-0394-Data-and-Codes.

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Acknowledgements

The authors acknowledge the support from the US National Science Foundation (#2017998), Water Research Foundation (Paul L. Busch Award to S.L.), US-Israel Binational Agricultural Research and Development Fund (BARD IS-5209-19) and the National Natural Science Foundation of China (#U20A20139).

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, USA

    Ruoyu Wang & Shihong Lin

  2. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China

    Rongrong He & Tao He

  3. Department of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA

    Menachem Elimelech

  4. Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA

    Shihong Lin

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Contributions

R.W. and S.L. conceived the idea and designed the research. R.W. conducted the quantitative analysis. All authors participated in the discussion and writing of the paper.

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Correspondence to Shihong Lin.

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Nature Water thanks Akshay Deshmukh, Jiangnan Shen and Jian Jin for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Text 1–2, Tables 1–4, Figs. 1–6 and codes.

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Supplementary Code 1

Codes of a MATLAB application used for data fitting.

Supplementary Data 1

Source data for supplementary figures.

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Source Data

Source data for Figs. 2–6.

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Wang, R., He, R., He, T. et al. Performance metrics for nanofiltration-based selective separation for resource extraction and recovery. Nat Water 1, 291–300 (2023). https://doi.org/10.1038/s44221-023-00037-0

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