Literature DB >> 25379759

Novel approach to characterizing the growth of a fouling layer during membrane filtration via optical coherence tomography.

Yiben Gao1, Sanna Haavisto, Weiyi Li, Chuyang Y Tang, Juha Salmela, Anthony G Fane.   

Abstract

Fouling control is one of the critical issues in membrane filtration and plays a very important role in water/wastewater treatment. Better understanding of the underlying fouling mechanisms entails novel characterization techniques that can realize a real-time noninvasive observation and provide high resolution images recording the formation of a fouling layer. This work presents a characterization method based on optical coherence tomography (OCT), which is able to detect the internal structures and motions by analyzing the interference signals. An OCT system was incorporated with a laboratory-scale membrane filtration system, and the growth of the fouling layer was observed by using the structural imaging. Taking advantage of the Doppler effects, the OCT-based characterization also provided the velocity profiles of the fluid field, which are of great value in analyzing the formation of the cake layer. The characterization results clearly reveal for the first time the evolution of the morphology of the cake layer under different microhydrodynamic environments. This study demonstrates that OCT-based characterization is a powerful tool for investigating the dynamic processes during membrane fouling.

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Year:  2014        PMID: 25379759     DOI: 10.1021/es503326y

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  2 in total

1.  Dynamic Modeling of Fouling in Reverse Osmosis Membranes.

Authors:  Bowen Ling; Peng Xie; David Ladner; Ilenia Battiato
Journal:  Membranes (Basel)       Date:  2021-05-10

2.  Electrospun Membranes as a Porous Barrier for Molecular Transport: Membrane Characterization and Release Assessment.

Authors:  Weiyi Liu; Greg Walker; Sally Price; Xiangdong Yang; Juan Li; Craig Bunt
Journal:  Pharmaceutics       Date:  2021-06-21       Impact factor: 6.321

  2 in total

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