Use of axial dispersion model for determination of Sherwood number and mass transfer coefficients in a perforated rotating disc contactor

The mass transfer process in a perforated rotating disk contactor (PRDC) using a toluene-acetone-water system was investigated.The volumetric overall mass transfer coefficients are calculated in a PRDC column.Both mass transfer directions are considered in experiments.The influences of operating variables containing agitation rate,dispersed and continuous phase flow rates and mass transfer in the extraction column are studied.According to obtained results,mass transfer is significantly dependent on agitation rate,while the dispersed and continuous phase flow rates have a minor effect on mass transfer in the extraction column.Furthermore,a novel empirical correlation is developed for prediction of overall continuous phase Sherwood number based on dispersed phase holdup,Reynolds number and mass transfer direction.There has been great agreement between experimental data and predicted values using a proposed correlation for all operating conditions.     

A new manufacturable filter design approach for spectral reflectance estimation

Selection of the best possible filter set among a set of available filters is the obvious method of increasing dimension of camera signals for spectral reflectance reconstruction. There are also methods that are focusing on the filter design regardless of noticing to the constructability of the designed filters. This study shows that direct optimization of physical variables of filter manufacturing technique is more reliable than indirect approach of designing and then physical manufacturing of the designed filters. Direct optimization of the transmission‐controlling primaries in filter manufacturing process would guarantee having the designed filters in reality. Combination of some solvent dyes was used as the spectral transmission matching system for filter manufacturing. As a conventional technique, filters were designed and best possible dye concentrations that match the desired filters were calculated. As an alternative approach, filters were also designed using direct optimization of dyes concentrations. The results showed that direct optimization of dye concentrations exhibits better performance in comparison with the conventional technique. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 316–326, 2017     

High‐performance carboxylate superplasticizers for concretes: Interplay between the polymerization temperature and properties

Polycarboxylate superplasticizers based on acrylic acid (AA) and maleic anhydride (MAn) were synthesized via free‐radical copolymerization with an ethylene glycol monomer and characterized. The copolymerization temperature (ranging from 50 to 90 °C) appeared to be the key operating factor governing the chemical structure of the superplasticizers. The chemical structures of the products were analyzed by gel permeation chromatography, whereas an optimized sample was further analyzed by Fourier transform infrared spectroscopy and ¹H‐NMR. Superplasticizers of the AA and MAn classes were then incorporated into concrete, and their performances were measured by slump and slump loss tests, where a large dependency of the microstructure on the synthesis temperature was recognized. The optimum temperatures were found to be 50 and 80 °C for the AA and MAn modifiers, respectively. At their own optimum temperatures, the AA and MAn superplasticizer revealed slump losses from 23 to 4 cm and 15 to 5 cm, respectively, after 45 min. The chemical structures of the plasticizers were patterned illustratively to speculate the performance of each superplasticizer according to changes that took place in the backbone length and side‐chain density. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44908.     

Fabricating and robust artificial neural network modeling nanoscale polyurethane fiber using electrospinning method

With regard to the fact that currently there is no comprehensive method to predict diameter of polyurethane/solvent fiber from electrospinning, in this study, diameter prediction of polyurethane/solvent fiber was conducted using neural networks and an error of 166 nm was observed. This error shows that artificial neural networks (ANNs) can predict diameter of electrospinning polyurethane fibers well. Then, considering weak repeatability nature of electrospinning in fabricating fibers with desired diameter, least mean square is used to improve stability of neural network model that shows an error of 113 nm, which represented better results compared to common ANN. To investigate the effect of each one of parameters affecting fiber diameter, sensitivity analysis was conducted. Along with this predicting model, sensitivity analysis can be used to reduce parameters space before conducting future studies. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 45116.     

Induction time,storage capacity,and rate of methane hydrate formation in the presence of SDS and silver nanoparticles

In this communication, the kinetic parameters of methane hydrate formation (induction time, quantity and rate of gas uptake, storage capacity (SC), and apparent rate constant) in the presence of sodium dodecyl sulfate (SDS), synthetized silver nanoparticles (SNPs), and mixture of SDS?+?SNPs have been studied. Experimental measurements were performed at temperature of 273.65?K and initial pressure of 7?MPa in a 460?cm³ stirred batch reactor. Our results show that adding SDS, SNPs and their mixture increases the quantity of gas uptake, water to hydrate conversion, and SC of methane hydrate formation, noticeably. Using 300?ppm SDS increases the SC and the quantity of methane uptake 615, and 770%, respectively, compared with pure water. Investigating the hydrate growth rate at the start of hydrate formation process shows that, using SNPs, SDS, and their mixture increases the initial apparent rate constant of hydrate rate, considerably. Our results show that the system of methane?+?water?+?SDS 500?ppm?+?SNPs 45?µM represents the maximum value of initial apparent rate constant, compared with other tested systems.     

Various nano-particles influences on structure,viscoelastic, Vulcanization and mechanical behaviour of EPDM nano-composite rubber foam

ABSTRACT

In this study, the effect of various nano-particle type and concentration on the structure, curing, viscosity variation during vulcanisation, and mechanical characteristics of ethylene–propylene–diene monomer (EPDM) rubber foam is reported. Three types of nanoparticle with various dimensional aspects (1D carbon nanotubes, 2D nano clay, and 3D nano silica) are employed to investigate their effect on the fabrication of EPDM rubber foam. It is observed that the properties of the foams were efficiently influenced by the nano-particle shapes and content in the matrix. Nanoparticles may increase cell density and change cell structures. In addition, they can change the curing behaviour of foam rubber by affecting curing rate and scorch time of rubber. In the end, mechanical properties of EPDM foam rubbers investigated by experimental tests and implementing few empirical and constitutional mechanical models. It is very helpful to use suitable nanoparticle to achieve desired properties out of fabricated foams.     

Batch and fixed‐bed column adsorption of Cu(II), Pb(II) and Cd(II) from aqueous solution onto functionalised SBA‐15 mesoporous silica

Functionalised SBA‐15 mesoporous silica with polyamidoamine groups (PAMAM‐SBA‐15) was successfully prepared with the structure characterised by X‐ray diffraction, nitrogen adsorption–desorption, Fourier transform infrared spectra and thermogravimetric analysis. PAMAM‐SBA‐15 was applied as adsorbent for Cu(II), Pb(II) and Cd(II) ions removal from aqueous solution. The effects of the solution pH, adsorbent dosage and metal ion concentration were studied under the batch mode. The Langmuir model was fitted favourably to the experimental data. The maximum sorptive capacities were determined to be 1.74 mmol g^?1 for Cu(II), 1.16 mmol g^?1 for Pb(II) and 0.97 mmol g^?1 for Cd(II). The overall sorption process was fast and its kinetics was fitted well to a pseudo‐first‐order kinetic model. The mean free energy of sorption, calculated from the Dubinin–Radushkevich isotherm, indicated that the sorption of lead and copper, with E > 16 kJ mol^?1, followed the sorption mechanism by particle diffusion. The adsorbent could be regenerated three times without significant varying its sorption capacity. A series of column tests were performed to determine the breakthrough curves with varying bed heights and flow rates. The breakthrough data gave a good fit to the Thomas model. Maximum sorption capacity of 1.6, 1.3 and 1.0 mmol g^?1 were found for Cu(II), Pb(II) and Cd(II), respectively, at flow rate of 0.4 mL min^?1 and bed height of 8 cm, which corresponds to 83%, 75% and 73% of metallic ion removal, respectively, which very close to the value determined in the batch process. Bed depth service time model could describe the breakthrough data from the column experiments properly. © 2012 Canadian Society for Chemical Engineering