Quantitative analysis of cake characteristics based on SEM imaging during coagulation-ultrafiltration process

Autor: Jun Nan, Zhenbei Wang, Shaoyin Peng, Zilin Wang
Rok vydání: 2019
Předmět:
Zdroj: Environmental Science and Pollution Research. 26:36296-36307
ISSN: 1614-7499
0944-1344
Popis: Cake formed by flocs is a crucial factor to affect membrane fouling during coagulation-ultrafiltration process. To investigate the role of floc properties on cake, cake characteristics under various coagulant dosage conditions were calculated by scanning electron microscope (SEM) imaging. Results found that one SEM image with × 5000 magnification could accurately estimate cake porosity with relative error lower than 5.00% for all conditions, whereas more SEM images with × 10,000 magnification or × 20,000 magnification should be applied to calculate cake porosity precisely. This could be explained by different pore information of SEM images with various magnifications. Compared to single SEM image with × 10,000 magnification and × 20,000 magnification, single SEM image with × 5000 magnification contained the most comprehensive pore information and slightly overestimated pore area for pore smaller than 0.4 μm2 due to lower resolution. To verify feasibility by SEM image evaluating cake characteristics, cake porosity calculated by SEM image and Carman-Kozeny equation were analyzed. The results showed that cake porosity estimated by these two methods were nearly the same, proving the feasibility of this method. Moreover, with the increase of coagulant dosage, cake porosity presented similar variation with floc average size, indicating that floc average size was likely to dominate cake porosity in this study. For pore characteristics, pore average characteristic length and pore average area were in accordance with floc fractal dimension, whereas pore fractal dimension and pore amount were consistent with floc average size. This gives specific information about the relation between floc properties and cake characteristics.
Databáze: OpenAIRE