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模拟离子强度对中空纤维纳滤膜传质的影响。

Modeling Ionic Strength Effects on Hollow-Fiber Nanofiltration Membrane Mass Transfer.

作者信息

Yonge David T, Biscardi Paul G, Duranceau Steven J

机构信息

Jones Edmunds & Associates, 324 S. Hyde Park Ave, Suite 250, Tampa, FL 33606, USA.

Hazen and Sawyer, 10002 Princess Palm Avenue, Suite 200, Tampa, FL 33619, USA.

出版信息

Membranes (Basel). 2018 Jul 4;8(3):37. doi: 10.3390/membranes8030037.

DOI:10.3390/membranes8030037
PMID:29973499
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6161266/
Abstract

In this research, we investigated the influence of feedwater ionic strength on diffusion of divalent ions through a hollow-fiber nanofiltration membrane. The results indicated that solute flux of magnesium was increased as a result of elevating the ionic strength in the feedwater. Specifically, the feedwater ionic strength was observed to have a nonlinear impact on the diffusion of magnesium during the nanofiltration process, which was under-predicted by the homogeneous solution diffusion (HSD) model. This result suggested that elevating the feedwater ionic strength had reduced the strength of the electrostatic double layer at the membrane surface. We then developed a modification of the HSD model (referred to as the HSD-IS model) which incorporated an empirical term related to the effect of feedwater ionic strength (IS) on diffusion of magnesium. The root mean squared error of the HSD-IS model was improved by 77% as compared to the HSD model, which did not incorporate a term related to feedwater ionic strength. This improvement suggested that feedwater ionic strength should be considered when modeling hardness removal during nanofiltration.

摘要

在本研究中，我们调查了给水离子强度对二价离子通过中空纤维纳滤膜扩散的影响。结果表明，由于提高了给水中的离子强度，镁的溶质通量增加。具体而言，观察到给水离子强度对纳滤过程中镁的扩散有非线性影响，这一影响被均相溶液扩散（HSD）模型预测不足。该结果表明，提高给水离子强度降低了膜表面静电双层的强度。然后，我们对HSD模型进行了修正（称为HSD-IS模型），该模型纳入了一个与给水离子强度（IS）对镁扩散影响相关的经验项。与未纳入与给水离子强度相关项的HSD模型相比，HSD-IS模型的均方根误差提高了77%。这一改进表明，在模拟纳滤过程中的硬度去除时应考虑给水离子强度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/4bca5e45edd2/membranes-08-00037-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/63d504755084/membranes-08-00037-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/dd37e3afde1a/membranes-08-00037-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/27f1bc3930f1/membranes-08-00037-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/181681412c49/membranes-08-00037-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/90d72ddb7707/membranes-08-00037-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/4b41bd59e56d/membranes-08-00037-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/f45775bdc508/membranes-08-00037-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/755b23f8ee39/membranes-08-00037-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/4bca5e45edd2/membranes-08-00037-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/63d504755084/membranes-08-00037-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/dd37e3afde1a/membranes-08-00037-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/27f1bc3930f1/membranes-08-00037-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/181681412c49/membranes-08-00037-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/90d72ddb7707/membranes-08-00037-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/4b41bd59e56d/membranes-08-00037-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/f45775bdc508/membranes-08-00037-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/755b23f8ee39/membranes-08-00037-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fea2/6161266/4bca5e45edd2/membranes-08-00037-g009.jpg

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本文引用的文献

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STATISTICAL EVALUATION OF SIEVE CONSTANTS IN ULTRAFILTRATION.超滤中筛常数的统计评估。
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Hydrodynamic modeling of NOM transport in UF: effects of charge density and ionic strength on effective size and sieving.超滤中天然有机物（NOM）传输的流体动力学建模：电荷密度和离子强度对有效尺寸和筛分的影响
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