Dataset of reverse osmosis membrane transport properties calculated with and without assumptions about concentration polarization and solute rejection and the errors associated with each assumption
The data shared in this work represent aspects of the performance of reverse osmosis membranes during filtration. We present pressure, permeate flux, and solute rejection data gathered during cross-flow filtration experiments, which were used to (i) model water and solute permeation through the memb...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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Elsevier
2022-10-01
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Series: | Data in Brief |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340922007454 |
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author | Mikayla D. Armstrong Riley Vickers Orlando Coronell |
author_facet | Mikayla D. Armstrong Riley Vickers Orlando Coronell |
author_sort | Mikayla D. Armstrong |
collection | DOAJ |
description | The data shared in this work represent aspects of the performance of reverse osmosis membranes during filtration. We present pressure, permeate flux, and solute rejection data gathered during cross-flow filtration experiments, which were used to (i) model water and solute permeation through the membranes and (ii) calculate concentration polarization moduli and a suite of transport properties, including water permeance, solute permeance, and water-solute selectivity. Membrane transport properties were calculated with the different approaches commonly used to simplify transport property calculations. Typical calculations of these transport properties often use simplifying assumptions (e.g., negligible concentration polarization and solute rejection close to 100%). However, the extent of the errors associated with using simplifying assumptions in this context were not previously known or quantified. This publication and corresponding dataset pertain to figures presented in the accompanying work (Armstrong et al., 2022) [1]. |
first_indexed | 2024-04-11T11:28:04Z |
format | Article |
id | doaj.art-590b5e1ed7bd44c0aae886e29fc72240 |
institution | Directory Open Access Journal |
issn | 2352-3409 |
language | English |
last_indexed | 2024-04-11T11:28:04Z |
publishDate | 2022-10-01 |
publisher | Elsevier |
record_format | Article |
series | Data in Brief |
spelling | doaj.art-590b5e1ed7bd44c0aae886e29fc722402022-12-22T04:26:14ZengElsevierData in Brief2352-34092022-10-0144108538Dataset of reverse osmosis membrane transport properties calculated with and without assumptions about concentration polarization and solute rejection and the errors associated with each assumptionMikayla D. Armstrong0Riley Vickers1Orlando Coronell2Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USADepartment of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USACorresponding author.; Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USAThe data shared in this work represent aspects of the performance of reverse osmosis membranes during filtration. We present pressure, permeate flux, and solute rejection data gathered during cross-flow filtration experiments, which were used to (i) model water and solute permeation through the membranes and (ii) calculate concentration polarization moduli and a suite of transport properties, including water permeance, solute permeance, and water-solute selectivity. Membrane transport properties were calculated with the different approaches commonly used to simplify transport property calculations. Typical calculations of these transport properties often use simplifying assumptions (e.g., negligible concentration polarization and solute rejection close to 100%). However, the extent of the errors associated with using simplifying assumptions in this context were not previously known or quantified. This publication and corresponding dataset pertain to figures presented in the accompanying work (Armstrong et al., 2022) [1].http://www.sciencedirect.com/science/article/pii/S2352340922007454PermeanceSelectivityDiffusive transportFluxOsmotic pressureCross-flow |
spellingShingle | Mikayla D. Armstrong Riley Vickers Orlando Coronell Dataset of reverse osmosis membrane transport properties calculated with and without assumptions about concentration polarization and solute rejection and the errors associated with each assumption Data in Brief Permeance Selectivity Diffusive transport Flux Osmotic pressure Cross-flow |
title | Dataset of reverse osmosis membrane transport properties calculated with and without assumptions about concentration polarization and solute rejection and the errors associated with each assumption |
title_full | Dataset of reverse osmosis membrane transport properties calculated with and without assumptions about concentration polarization and solute rejection and the errors associated with each assumption |
title_fullStr | Dataset of reverse osmosis membrane transport properties calculated with and without assumptions about concentration polarization and solute rejection and the errors associated with each assumption |
title_full_unstemmed | Dataset of reverse osmosis membrane transport properties calculated with and without assumptions about concentration polarization and solute rejection and the errors associated with each assumption |
title_short | Dataset of reverse osmosis membrane transport properties calculated with and without assumptions about concentration polarization and solute rejection and the errors associated with each assumption |
title_sort | dataset of reverse osmosis membrane transport properties calculated with and without assumptions about concentration polarization and solute rejection and the errors associated with each assumption |
topic | Permeance Selectivity Diffusive transport Flux Osmotic pressure Cross-flow |
url | http://www.sciencedirect.com/science/article/pii/S2352340922007454 |
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