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Polymeric Gas Separation Membranes
Abstract
This short Perspective conveys to the general reader of Macromolecules basic approaches of materials science of polymeric membranes for gas and vapor separation. The relations between the polymer structure and transport properties of rubbery and glassy membrane materials are considered. On the basis of acquired information, several methods for quantitative prediction of permeability were developed, and their comparative analysis is given in the Perspective. The past decade was marked by the appearance of a number of novel interesting membrane materials, which will be briefly described in the text. In conclusion, novel approaches for achieving highly permeable and permselective materials (e.g., mixed matrix membranes) will be considered as well as several relevant but not solved so far problems of membrane gas separation.
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Citations
Cited by
CO2 capture and separation technologies for end-of-pipe applications – A review
Olajire, A. A. (2010) · Energy · doi:10.1016/j.energy.2010.02.030 · Cited by 1,217
Transport and structural characteristics of crosslinked poly(ethylene oxide) rubbers
LIN, H., WAGNER, E., SWINNEA, J., FREEMAN, B., PAS, S., HILL, A., KALAKKUNNATH, S., & KALIKA, D. (2006) · Journal of Membrane Science · doi:10.1016/j.memsci.2005.09.040 · Cited by 327
Saha, D., Grappe, H. A., Chakraborty, A., & Orkoulas, G. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00745 · Cited by 316
Metadata
- Authors
- Yampolskii, Y.
- Venue
- Macromolecules
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-03-28
- Volume
- 45
- Issue
- 8
- Pages
- 3298-3311
- ISSN
- 0024-9297 (ISSN-L)
- 1520-5835
- OpenAlex
- W2105677359
- Cited by
- 1,254
- References
- 0
- FWCI
- 110.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yampolskii, Y. (2012). Polymeric Gas Separation Membranes. Macromolecules. https://doi.org/10.1021/ma300213b
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
