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Accepted ManuscriptThis is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. AbstractIn this work, four ultrafiltration (UF) membranes with molecular weight cut-offs (MWCOs) of 5, 15, 30 and 50 kDa, respectively, were fouled with 1 % BSA aqueous solutions and cleaned with different saline solutions. The influence of MWCO, membrane material and operating conditions on the cleaning efficiency was investigated. Saline solutions were able to clean the 5, 15 and 30 kDa membranes, but not the 50 kDa membrane. NaCl, NaNO 3 , NH 4 Cl and KCl were the most effective salts. The cleaning tests demonstrated that the higher the temperature of the saline solution was, the higher the cleaning efficiency was also. In addition, an increase in the crossflow velocity resulted in an increase in the hydraulic cleaning efficiency (HCE). However, there was an optimum value of salt concentration to clean the membrane effectively. Response Surface 2 Methodology was used to investigate the relationship between salt concentration and temperature in the cleaning process.

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Forward osmosis is a low-energy water treatment emerging technology, which has demonstrated improved solute rejection and low fouling propensity. In this study, the applicability of aquaporinbased forward osmosis membranes during separation of biogas digestate liquid fractions was investigated. The results showed that Total Ammonia-Nitrogen rejection was higher than 95.5% in all experiments, independently of the type of draw solution (NaCl and hide preservation effluents), experimental period and the use of feed acidification. The results also confirmed that high draw osmotic pressures (i.e. 3.5M sodium chloride and hide preservation wastewater) combined with feed acidification had a negative effect on the membrane water permeability. Membrane rinsing after fouling was also successful in recovering the membrane initial water flux as well as removing 2 the remaining foulants on the membrane surface. The membrane inspection results from Scanning-Electron Microscope, Energy-Dispersive X-Ray analysis and Fourier Transform Infrared-Attenuated Total Reflectance showed that fouling in this application was mild and reversible after membrane rinsing. The applicability of aquaporin-based forward osmosis membranes during separation of biogas digestate liquid fractions has been demonstrated. The results showed the potential of this technology to achieve enhanced ammonia-nitrogen rejections and low-fouling propensity.

In this work, flux decline during crossflow ultrafiltration of macromolecules with ceramic membranes has been modeled using artificial neural networks. The artificial neural network tested was the multilayer perceptron. Operating parameters (transmembrane pressure, crossflow velocity and time) and dynamic fouling were used as inputs to predict the permeate flux. Several pretreatments of the experimental data and the optimal selection of the parameters of the neural networks were studied to improve the fitting accuracy. The fitting accuracy obtained with artificial neural networks was compared with Hermia pore blocking models adapted to crossflow ultrafiltration. The artificial neural networks generate simulations whose performance was comparable to that of Hermia's models adapted to crossflow ultrafiltration. Considering the computational speed, high accuracy and the ease of the artificial neural networks methodology, they are a competitive, powerful and fast alternative for dynamic crossflow ultrafiltration modeling.