Empirical modeling coupled with pore blocking for predicting cake formation of electric field effects on oily waste water cross-flow microfiltration

Improved water purification by PVDF ultrafiltration membrane modified with GO-PVA-NaAlg hydrogel

This work presents a modified polyvinylidene fluoride (PVDF) ultrafiltration membrane blended with graphene oxide-polyvinyl alcohol-sodium alginate (GO-PVA-NaAlg) hydrogel (HG) and polyvinylpyrrolidone (PVP) prepared by the immersion precipitation induced phase inversion approach. Characteristics of the membranes with different HG and PVP concentrations were analyzed by field emission scanning electron microscopy (FESEM), Atomic force microscopy (AFM), contact angle measurement (CA), and Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). The FESEM images showed an asymmetric structure of the fabricated membranes, and possessing a thin dense layer over the top and a layer finger-like. With increasing HG content, membrane surface roughness increases so that highest surface roughness for the membrane containing 1wt% HG is with a Ra value of 281.4 nm. Also, the contact angle of the membrane reaches from 82.5° in bare PVDF membrane to 65.1° in the membrane containing 1wt% HG. The influences of adding HG and PVP to the casting solution on pure water flux (PWF), hydrophilicity, anti-fouling ability, and dye rejection efficiency were evaluated. The highest water flux reached 103.2 L/m² h at 3 bar for the modified PVDF membranes containing 0.3 wt% HG and 1.0wt% PVP. This membrane exhibited a rejection efficiency of higher than 92%, 95%, and 98% for Methyl Orange (MO), Conge Red (CR), and Bovine Serum Albumin (BSA), respectively. All nanocomposite membranes possessed a flux recovery ratio (FRR) higher than bare PVDF membranes, and the best anti-fouling performance of 90.1% was relevant to the membrane containing 0.3 wt% HG. The improved filtration performance of the HG-modified membranes was due to the enhanced hydrophilicity, porosity, mean pore size, and surface roughness after introducing HG.

Membrane Fabrication and Modification by Atomic Layer Deposition: Processes and Applications in Water Treatment and Gas Separation

Membrane-based separation processes are part of most water purification plants worldwide. Industrial separation applications, primarily water purification and gas separation, can be improved with novel membranes or modification to existing ones. Atomic layer deposition (ALD) is an emerging technique that is proposed to upgrade certain kinds of membranes independent of their chemistry and morphology. ALD deposits thin, defect-free, angstrom-scale, and uniform coating layers on a substrate's surface by reacting with gaseous precursors. The surface-modifying effects of ALD are described in the present review, followed by a description of various types of inorganic and organic barrier films and how these can be used in combination with ALD. The role of ALD in membrane fabrication and modification is categorized into different membrane-based groups according to the treated medium, i.e., water or gas. In all membrane types, the ALD-based direct deposition of inorganic materials, mainly metal oxides, on the membrane surface can improve antifouling, selectivity, permeability, and hydrophilicity. Therefore, the ALD technique can broaden the applications of membranes to the treatment of emerging contaminants in water and air. Finally, the advancement, limitations, and challenges of ALD-based membrane fabrication and modification are compared to provide a comprehensive guideline for developing next-generation membranes with improved filtration and separation performance.

High-Resolution Numerical Simulation of Microfiltration of Oil-in-Water Emulsion Permeating through a Realistic Membrane Microporous Structure Generated by Focused Ion Beam Scanning Electron Microscopy Images

Owing to the limitations of visualization techniques in experimental studies and low-resolution numerical models based on computational fluid dynamics (CFD), the detailed behavior of oil droplets during microfiltration is not well understood. Hence, a high-resolution CFD model based on an in-house direct numerical simulation (DNS) code was constructed in this study to analyze the detailed dynamics of an oil-in-water (O/W) emulsion using a microfiltration membrane. The realistic microporous structure of commercial ceramic microfiltration membranes (mullite and α-alumina membranes) was obtained using an image processing technique based on focused ion beam scanning electron microscopy (FIB-SEM). Numerical simulations of microfiltration of O/W emulsions on the membrane microstructure obtained by FIB-SEM were performed, and the effects of different parameters, including contact angle, transmembrane pressure, and membrane microporous structure, on filtration performance were studied. Droplet deformation had a strong impact on filtration behavior because coalesced droplets with diameters larger than the pore diameter permeated the membrane pores. The permeability, oil hold-up fraction inside the pores, and rejection were considerably influenced by the contact angle, while the transmembrane pressure had a little impact on the permeability and oil hold-up fraction. The membrane structure, especially the pore size distribution, also had a significant effect on the microfiltration behavior and performance.

Parametric analysis of lignocellulosic ultrafiltration in lab scale cross flow module using pore blocking and artificial neural network model

In this study, fouling mechanism and modelling analysis of synthetic lignocellulose biomass and agricultural palm oil effluent was studied using polyethersulfone (PES) ultrafiltration (UF) 10 kDa membrane. The impact of process variables (transmembrane pressure (TMP), pH and concentration of feed solution) on lignocellulosic flux was analysed using pore blocking model. The feasible approaches on utilising deep learning artificial neural network (ANN) to predict smaller flux datasets are studied. Among the input variables, pH of lignin feed solution has significant control towards flux and lignin rejection coefficient for both lignin and lignocellulosic solution. Alteration in the structure of lignin at different pH conditions contributed in the improvement of lignin rejection coefficient to 0.98 at the feed pH of 9. A maximum steady state flux of 52.03 L/m²h was observed at the lower lignin concentration (0.25 g/L), TMP of 200 kPa and feed pH of 3. At high TMP and concentration, lignin rejection decreased due to enhancement of feed concentration on membrane surface. The mechanistic model exhibited that cake layer phenomena was dominant in both lignin and lignocellulosic solution. The proposed ANN model showed good correlation (R²-1.00) with experimental non-linear flux dynamic data of both lignin and synthetic lignocellulosic solution. In ANN analysis, activation function, algorithm and neuron effect have significant effect in design of accurate model for prediction of small flux datasets. Aerobically-treated palm oil mill filtration analysis also showed that cake layer phenomenon was dominant. A water recovery of 82 % was achieved even at low TMP under short durations.