Iranian journal of chemical engineering
Volume:15 Issue: 3, Summer 2018

The nitrogen doped TiO2 as heterogeneous photocatalyst via sol-gel method were successfully synthesized. The physicochemical, morphological and textural characteristics of the obtained TiO2 samples were characterized by advanced analysis techniques. The photocatalytic activity of the samples were evaluated for degradation of 4-CP under solar irradiation. The as-synthesized photocatalysts were characterized with X-ray diffraction (XRD), surface area measurements (BET and BJH), Fourier transform infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FE-SEM), energy dispersive spectroscopy (EDS) and energy dispersive X-ray spectrum (EDX). The activities of as-prepared TiO2 photocatalysts were examined for the degradation of 4-Chlorophenol aqueous solution under solar irradiation in a photoreactor and photocatalytic degradation mechanism and pathway have been investigated. The results show that the 3% wt. N-doped TiO2 nanoparticles under conditions (solution pH of 4.0, catalyst loading of 2 g/L, initial 4-CP concentration of 10 mg/L, Time of 8 h) exhibits much higher photocatalytic degradation efficiency (91%) as compared with that of 5% wt. N-doped (83%), 1% wt. N-doped (71%), and pure TiO2 (35%).

In this study, extraction of tannic acid using microchannel was investigated. Affective parameters were optimized. Different solvents including buthanol, ethylacetate and n-hexane as organic phase, methanol, propanol, ethanol and water as aqueous phase investigated. Microchannels with different confluence angles and diameters were examined. Microchannels with different confluence angles and diameters were examined. The effects of pH, temperature, and volumetric flow ratio and contact time of the two phases were investigated. The response surface methodology was used to optimize extraction yield of tannin from Quercus leaves in the employed microchannels. Based on this optimization, maximum yield was achieved at pH=2, temperature=33.1℃, volumetric flow ratio =1.2 and contact time of 25.35s. Results show that extraction-using microchannel has many advantages over traditional methods, including shorter time and higher economic efficiency. Moreover, microchannel provides smaller volume of fluids resulting in lower solvent consumption, lower waste production, shorter analytical times, smaller space requirements, and lower energy consumption.

This paper presents using the fractional PImDn controller module which manipulates insulin infusion rate to maintain normoglycemia in subjects with type 1 diabetes. To prevent severe hypoglycemia, a conventional proportional controller is used to regulate glucagon infusion rate when the blood glucose levels fall below a threshold. Two sets of controller parameters are obtained and evaluated. For the first tuning set, clinical data from an oral glucose tolerance test taken from a group of healthy subjects are used to obtain the controller parameters such that it can mimic a real healthy pancreas. To obtain the second tuning set, the controller parameters are optimized through a sequential quadratic programming algorithm. Using the second tuning set, the in silico 2-hour postprandial test result and comparing it with the glucose concentration trajectory of the healthy subjects show that the controller performs well in returning the blood sugar levels into the glucose homeostasis while keeping the plasma insulin concentration within the acceptable physiological range. It is indicated that the manipulation of glucagon infusion rate is effective in hypoglycemia prevention if more aggressive controller settings are chosen or dysfunctional insulin infusion occurs.

The effect of the solid–wall boundary condition on the segregation behavior of a sand ternary mixture differing in size but having the same proportion has been investigated in a gas–solid bubbling fluidized bed. A multi-fluid computational fluid dynamics model incorporating the kinetic theory of granular flow has been used. The mass fraction profiles of the different-sized particles along the bed height have been experimentally measured by 'freeze–sieving' method. The simulation results of mass fraction distribution and segregation index have been compared against our experimental data in order to evaluate solid–wall boundary conditions in terms of specularity and particle-wall restitution coefficients. The analysis indicates that, the specularity coefficients in range 0.5 to 0.9 lead to the satisfactory results and the best agreement is obtained for =0.9 which corresponds to partial–slip wall boundary condition while the particle–wall restitution coefficient has only a negligible effect on the results. Also maximum segregation index occurs at specularity coefficient of 0.9 at which the segregation pattern may be affected by simultaneous mechanisms of particles circulation and bubbles rising. The effects of superficial gas velocity on the segregation behavior in bubbling regime have also been studied and a significant reduction in segregation index has been observed with increasing gas velocity from 1.1Umf to 1.3Umf.

The effect of temperature (25, 40, 55 and 70°C) and weight fraction of MWCNTs (0.125, 0.25 and 0.5 %wt) on the viscosity of nanofluids containing pristine and functionalized MWCNTs have been investigated. For this purpose, all of the measurements were carried out in triplicate and were analyzed using two factors completely randomized design and comparison of data means is carried out with Duncan’s multiple range test. The level of statistical significance was determined at 95%. The experimental and statistical results show that the viscosity of the both nanofluids increases with respect to the weight fraction and by decreasing the temperature. Statistical analysis of viscosity shows that temperature, weight fraction and interaction effect of them have a significant influence on the viscosity of nanofluids containing pristine and functionalized MWCNTs (α=0.05). Meanwhile, the results show that there was a significant difference at different levels of temperature on the viscosity of the both nanofluid.

A three-layer artificial neural network (ANN) model was developed to predict the remained DO (deoxygenation) in water after DO removal with an enzymatic granular biocatalyst (GB), based on the experimental data obtained in a laboratory stirring batch study. The effects of operational parameters such as initial pH, initial glucose concentration and temperature on DO removal were investigated. On the basis of batch reactor test results, the optimum value of operating temperature, glucose concentration and pH were found to be 30oC, 80 mM and 7, respectively. After back-propagation training, the ANN model was able to predict the remained DO with a tangent sigmoid function (tansig) at hidden layer with 7 neurons and a linear transfer function (purelin) at the output layer. The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of 0.995 for three model variables used in this study.

The catalytic reduction of sulfur dioxide with methane to form elemental sulfur has been studied. Al2O3, Cu-Al2O3 and Ni-Al2O3 were examined as catalysts and their performances were compared in terms of SO2 conversion and selectivity. Performance of the catalyst extremely enhanced when nickel and copper were added as promoters. The effects of temperature, SO2/CH4 molar ratio, and reaction time on SO2 reduction were studied. The operating temperature range was 550–800 °C and it was observed that the reaction is strongly temperature dependent. At temperatures lower than 700 °C, Al2O3-Cu (10%) catalyst showed the best performance of all the catalysts. But, at 700° and higher, performances of Al2O3-Cu (10%) and Al2O3-Ni(10%) catalysts were similar. Complete conversion and selectivity (more than 99.5%) was achieved by Al2O3-Cu (10%) and Al2O3-Ni(10%) catalyst, at 750 °C. Effect of molar feed ratio of SO2/CH4= 1-3 was studied and stoichiometric feed ratio showed the best performance. Also, investigation of reaction time for Al2O3-Cu(10%) and Al2O3-Ni(10%) catalysts showed a good long-term stability for SO2 reduction with methane