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Characterization of biofilm distribution in hollow fiber membranes using Compressed Sensing Magnetic Resonance Imaging

Biofilm formation during ultrafiltration membrane operation was investigated by Compressed Sensing Magnetic Resonance Imaging (MRI), with tryptic soy broth included in the feed stream to stimulate microbial growth. Biofilm development was visualized as growing layer characterized by reduced T1 relax...

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Bibliographic Details
Published in:Journal of membrane science 2020-01, Vol.594, p.117437, Article 117437
Main Authors: Simkins, J.W., Schuhmann, S., Guthausen, G., Heijnen, M., Codd, S.L., Seymour, J.D.
Format: Article
Language:English
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Summary:Biofilm formation during ultrafiltration membrane operation was investigated by Compressed Sensing Magnetic Resonance Imaging (MRI), with tryptic soy broth included in the feed stream to stimulate microbial growth. Biofilm development was visualized as growing layer characterized by reduced T1 relaxation time, and its progression as monitored by MRI was compared with classical integral filtration parameters such as permeate flux J, transmembrane pressure Δp and permeability Lp to document fouling behavior. Over three days of growth a change in the filtration process could be observed in both measurements, with Lp decreasing dramatically over time as the surface-associated biofilm increased in thickness. Following cessation of filtration and the associated drop in Δp, the biofilm detached from the lumen wall and dispersed throughout the feed channel. Compressed Sensing MRI velocity and intensity measurements facilitate fast imaging during filtration processes, providing new possibilities for the investigation of biofouling in filtration membranes. [Display omitted] •Biofouling in multichannel hollow fiber membranes is characterized in-situ by MRI.•Biofouling was stimulated with tryptic soy broth in the feed solution.•T1-contrast images track biofilm development inside the membrane channels.•Velocity images allow the characterization of flow during filtration.•Compressed Sensing (CS) considerably reduces measurement time.
ISSN:0376-7388
1873-3123
DOI:10.1016/j.memsci.2019.117437