Resources / Publications
Helene Roberge (1,2), Philippe Moreau (1), Estelle Couallier (2), Patricia Abellan (1)
SSRN, December 2021. DOI: 10.2139/ssrn.3978510
3D FIB/SEM; 3D Reconstruction; Filtration Membrane; Selective Layer; Flow Calculation
Microfiltration (MF) and ultrafiltration (UF) processes are well known in water treatment or separation of valuable biomolecules. They have recently been adapted for microalgae valorization, where filtration employing nanoporous polymer membranes is used to separate and recover lipids and proteins from microalgae extracts. As the design of novel MF and UF membranes with optimized filtration performance (reduced fouling of molecules and increased filtrate fluxes) is leading to increasingly complex pore structures new characterization methods of filtration membranes are needed. A detailed, nanometer scale, characterization of the three-dimensional pore structure of the membranes and the precise elucidation of the membrane structure-performance relationship is thus essential for advancing the development of efficient filtration process operating but also novel MF and UF membranes. In this work, the structural features determining the filtration performance of commercially available polyacrylonitrile (PAN) UF and polyethersulfone (PES) MF membranes are determined using scanning electron microscopy (SEM) coupled with a focused ion beam (FIB) at low electron-fluences to produce 3D reconstructions with up to 5nm resolution. We present methods to identify key structural parameters of the selective layer or skin of the membranes and to estimate the percentage of blind (dead-end) pores communicating with the membrane surface but not crossing the membrane. Furthermore, we demonstrate that 3D FIB/SEM provides a reliable estimation of the intrinsic permeability, in the case of membranes characterized by the presence of a finite selective layer. This work opens up the possibility of providing detailed information, useful not only to illustrate novel filtration membrane designs, but also as input data for nanometer-scale based predictive models.
Dragonfly was used to reconstruct and analyse different stacks of FIB/SEM images.
(1) Nantes Université, CNRS, Institut des Matériaux Jean Rouxel, IMN, F-44000 Nantes, France.
(2) Nantes Université, CNRS, ONIRIS, Laboratoire de Génie des Procédés, Environnement et Agroalimentaire, GEPEA, F-44600 Saint Nazaire.
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