Toward the prediction of porous membrane permeability from morphological data |
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| Authors: | Claudia Nurra Luizildo Pitol‐Filho Raphaelle Carraud Said Pertuz Domènec Puig Miguel A García Joan Salvadó Carles Torras |
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| Affiliation: | 1. Bioenergy and Biofuels Division, Catalonia Institute for Energy Research, Tarragona, Catalunya, Spain;2. Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Catalunya, Spain;3. Centro de Ciências Tecnológicas da Terra e do Mar, Universidade do Vale do Itajaí, Itajaí, (SC), Brazil;4. Intelligent Robotics and Computer Vision Group, Department Of Computer Science and Mathematics, Universitat Rovira i Virgili, Tarragona, Catalunya, Spain;5. Department of Electronic and Communications Technology, Universidad Autónoma De Madrid, Madrid, Spain |
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| Abstract: | One of the challenges in membrane technology is predicting permeability in porous membranes for liquid applications in an easy and inexpensive way. This is the aim of this work. To achieve this objective, several techniques can be considered. In this study, a morphological approach from two‐dimensional scanning electron micrographs is proposed. First, numerical membrane morphological parameters have been determined from micrographs by using the QUANTS tool, which applies a texture recognition process. Second, the obtained data have been fit to the Darcy's and Hagen–Poiseuille models to calculate permeations. The QUANTS results have also been compared with the ones obtained through a mercury porosimeter, which is a classic and well‐known methodology. Each parameter of the Hagen–Poiseuille model has been analyzed. A comparison between experimentally measured permeations and calculated ones has been performed. An even easier approach is proposed to predict flow rate with the only knowledge of membrane surface mean pore size. This method is based on cross‐section pore size interpolation by using function fits from surface mean pore sizes. The obtained results show a reasonable agreement between measured and computed results, making this technique a valid approach for predicting membrane permeability. POLYM. ENG. SCI., 56:118–124, 2016. © 2015 Society of Plastics Engineers |
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