Journal article
Forefronts in structure-performance models of separation membranes
- Abstract:
- Polymeric membranes used for separations are complex porous structures, spanning lengths that range from truly molecular scales up to many micrometers. These porous structures can be characterized by both the spatial and size distribution of the pores, which can further be divided between the membrane surface distribution versus the depth distribution. Such structural features have a wide impact on membrane performance, ultimately dictating the fluid permeability and solute selectivity as well as the propensity for and severity of fouling. It is thus not surprising that in recent years significant emphasis has been placed on engineering the pore size and distribution to achieve a specific task. However, despite the technological progress, it is difficult to quantify the effects of membrane morphology on overall performance. Identifying advantageous porous structures would benefit design and motivate the development of better control over the formation of a given morphology. In this discussion, the relative importance of membrane morphologies, manifested as pore spatial and size distributions, is considered for several illustrative cases: pressure-driven flow as impacted by membrane surface pore locations and depth morphologies; the selectivity of a porous membrane as affected by a porosity gradient; and the performance of a composite membrane as impacted by the porous morphologies of the support layer, as well as the overlaying thin-film. Emphasis is placed on unifying concepts of mathematical modelling, as well as the link between theory and experimental observation. Finally, some future extensions needed for consolidating structure–performance models are mentioned.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 4.1MB, Terms of use)
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- Publisher copy:
- 10.1016/j.memsci.2019.06.006
Authors
- Publisher:
- Elsevier
- Journal:
- Journal of Membrane Science More from this journal
- Volume:
- 588
- Article number:
- 117166
- Publication date:
- 2019-06-20
- Acceptance date:
- 2019-06-03
- DOI:
- ISSN:
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0376-7388
- Keywords:
- Pubs id:
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pubs:1007234
- UUID:
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uuid:fc243ea5-08cd-4144-875b-7d2bc3dc4b92
- Local pid:
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pubs:1007234
- Source identifiers:
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1007234
- Deposit date:
-
2019-06-04
- ARK identifier:
Terms of use
- Copyright holder:
- Elsevier
- Copyright date:
- 2019
- Rights statement:
- © 2019 Elsevier B.V. All rights reserved.
- Notes:
- This is the accepted manuscript version of the article. The final version is available from Elsevier at: https://doi.org/10.1016/j.memsci.2019.06.006
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