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The aim of this work was to synthesize nanocomposite membranes based on chitosan (CS) and cellulose acetate (CA) blends containing titanium dioxide (TiO2) nanoparticles and investigate their morphological, structural, mechanical, and thermal properties along with dye affinity ligand content for using potentially as bioadsorption applications. The samples were characterized by means of scanning electronic microscopy (SEM), energy dispersive X‐ray (EDX), Fourier transform infrared spectroscopy (FTIR), tensile, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and water contact angle (WCA). The SEM micrograph images showed a uniform and microporous morphology of the prepared membranes. FTIR analysis confirmed the presence of CA and TiO2 nanoparticles through the CS matrix in which the components used had good compatibility. The mechanical and thermal studies emphasized that strong interactions occurred between CS, CA, and TiO2 nanoparticles. Blending CS with CA and the addition of TiO2 nanoparticles enhanced the hydrophilic property of CS membranes, significantly. The CS/CA based nanocomposite containing 1.5 wt% of TiO2 nanoparticles showed the remarkable improvements in ultimate tensile strength values and an increase in stiffness more than three times compared to the neat CS membrane sample. Finally, considering the results of tensile test and immobilized Cibacron Blue F3G‐A (CB) content measurement, the nanocomposite samples denoted by (50/50) CS/CA/TiO2 (1.5%) were nominated as the promising material used for potentially bioadsorptive membrane. POLYM. COMPOS., 39:4452–4466, 2018. © 2017 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]

ABSTRACT In the present study, bubble size distribution (BSD) within a bubble column reactor was modeled using an artificial neural network (ANN). The fluids tested in the bubble column consisted of 11 different oil mixtures, each containing two different oils. Pure water was also tested. BSD was determined for various superficial gas velocities by photographing the state of the fluid. It was found that bubble size as well as distribution depended on parameters, such as gas flow rate, liquid properties, sparger pore diameter and distance from the sparger in the column. The proposed ANN model is based on more than 4500 data points collected for BSD estimation. Through statistical testing, it was found that the model has a correlation coefficient greater than 70% and upon experimental testing was found to better predict BSD than currently used correlations found in the literature. Copyright © 2011 Curtin University of Technology and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]