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        TiO2 nanoparticle stability via polyacrylic acid-binding on the surface of polyethersulfone membrane: Long-term evaluation

        Farima Damavandi,Abdolreza Aroujalian,Parisa Salimi 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.117 No.-

        Immobilization of photocatalysts on the membrane surface is a promising approach that produces photocatalyticmembranes that could help advance wastewater treatment. This work examined the stabilityof TiO2 nanoparticles binding to the PES membrane surface via polyacrylic acid. For this aim, the coronainducedgrafting technique was used for graft polymerization of PAA to introduce strong binding sites forTiO2 deposition on the PES surface. The stability test was performed in a cross-flow system, which indicatedminimal leaching after 72 h of filtration. The results evidenced the firm attachment of TiO2 on themembrane surface after long-term operation. PAA grafted membranes with TiO2-deposited membranesshowed better hydrophilicity and higher water flux. Compared to the unmodified PES membrane, themaximum flux of the TiO2 deposited membrane increased by 85 %. Moreover, the photocatalytic abilityof the photocatalytic membranes to remove phenol was evaluated under UV irradiation. The preparedmembranes showed good photocatalytic performance after three hours of continuous operation. Thehighest phenol degradation was achieved by PES-PAA-TiO2-0.1 %wt, indicating 62 % removal of the pollutantafter three hours. With its remarkable stability during filtration and outstanding photocatalyticperformance, the prepared membrane illustrates the excellent potential for long-term processes thatcould minimize nanoparticles leaching.

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        A comparative study on pomegranate juice concentration by osmotic distillation and thermal evaporation processes

        Atefeh Roozitalab,Ahmadreza Raisi,Abdolreza Aroujalian 한국화학공학회 2019 Korean Journal of Chemical Engineering Vol.36 No.9

        A comparative study was performed on the concentration of pomegranate juice by the osmotic distillation (OD) and thermal evaporation processes. Nanofibrous polyether-block-amid (PEBA) membrane was prepared by the electrospinning technique, and the influence of operating parameters on the performance of the OD process was studied. The experimental results indicated that an increase in the temperature difference led to higher water flux, while a higher feed temperature resulted in undesirable color changes in the concentrate product. A comparison between the OD and evaporation processes revealed that the OD concentrate product had better quality than the evaporation product in terms of aroma and phenolic compounds retention. Furthermore, an economic analysis was performed by COMFAR ΙΙΙ software to compare the OD and evaporation processes for the concentration of the pomegranate juice. It was also found that both OD and evaporation processes were feasible, although the evaporation process was more favorable in terms of the economic efficiency

      • KCI등재

        An artificial neural network approach to determine the rheological behavior of pickering-type diesel-in-water emulsion prepared with the use of β-cyclodextrin

        Alireza Monazzami,Farzaneh Vahabzadeh,Abdolreza Aroujalian,Azadeh Mogharei 한국화학공학회 2018 Korean Journal of Chemical Engineering Vol.35 No.4

        With the use of β-cyclodextrin (β-CD), Pickering-type diesel-in-water emulsions were prepared based on the inclusion complex formed between diesel and β-CD which acted as an emulsifier. By using the artificial neural network (ANN), the rheological behavior of the emulsions was characterized using three input variables: diesel-to-water ratio, β-CD concentration, and shear rate and one-output variable as shear stress. Gradient descent (GD), conjugate gradient (CG), and quasi Newton (QN) were used as three different methods in the feed-forward back-propagation algorithm for network training. Hyperbolic tangent sigmoid and pure linear were the transfer functions used for transforming information between input and output through one hidden layer containing ten neurons. By dividing the experimental data into three sets of training, validation, and testing, the QN method in predicting shear stress was found to have performed better than the other two network learning techniques (R2=0.994 and MSE=0.006).

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