Large Ultrathin Shelled Drops Produced via Non‐Confined Microfluidics

We present a facile approach for producing large and monodisperse core–shell drops with ultrathin shells using a single‐step process. A biphasic compound jet is introduced into a quiescent third (outer) phase that ruptures to form core–shell drops. Ultrathin shelled drops could only be produced within a certain range of surfactant concentrations and flow rates, highlighting the effect of interfacial tension in engulfing the core in a thin shell. An increase in surfactant concentrations initially resulted in drops with thinner shells. However, the drops with thinnest shells were obtained at an optimum surfactant concentration, and a further increase in the surfactant concentrations increased the shell thickness. Highly monodisperse (coefficient of variation smaller than 3 %) core–shell drops with diameter of ～200 μm–2 mm with shell thickness as small as ～2 μm were produced. The resulting drops were stable enough to undergo polymerisation and produce ultrathin shelled capsules.     

Fabrication and Application of a Sensitive and Highly Stable Copper Hexacyanoferrate Modified Carbon Ionic Liquid Paste Electrode for Hydrogen Peroxide and Glucose Detection

A three‐factor mixture design and response surface methodology were employed to find the optimal weight ratio of graphite powder, n‐dodecylpyridinium hexafluorophosphate and paraffin for the fabrication of a copper hexacyanoferrate modified carbon ionic liquid paste electrode (CuHCFe‐CILPE). The fabricated sensor showed electrocatalytic activity towards oxidation and reduction of hydrogen peroxide. It also was observed that the electrocatalytic activity for hydrogen peroxide oxidation was much higher than the electrocatalytic activity for hydrogen peroxide reduction. Glucose oxidase was then successfully immobilized on the surface of the proposed sensor to examine the possibility of using CuHCFe‐CILPE for the biosensor fabrication.     

Fabrication and Morphological Characterization of Polyurethane Foam Reinforced with TiO2 Nanoparticles

Polyurethane foams with various isocyanate/polyol ratios, reinforced with various amounts of nanosized TiO₂, were prepared and their morphological properties were investigated. The nanoparticles were dispersed into the polyol component by stirring and then heating during ultrasonication to avoid particle agglomeration. Both scanning electron and transmission optical microscopes were used to evaluate the role of the nanosized TiO₂ on the porous structure of the polyurethane foams. Cell size distributions were obtained by measuring the average cell diameters of the cells in the micrographs. To have a better assessment of nanoparticle effects on the foam morphology sample densities were measured using Archimedes law. For better understanding of microstructure evolution the heat release rate during the foaming process was characterized. The results showed that the values of cell size, cell density, apparent density and heat release rate depended on the ratio of isocyanate/polyol as well as TiO₂ content.     

Particle formation and coagulation in the seeded semibatch emulsion polymerization of butyl acrylate

Particle formation and coagulation in the seeded semibatch emulsion polymerization of butyl acrylate were studied under monomer‐starved conditions. To investigate the importance of the kinetics of the water phase in the nucleation process, the monomer feed rate was used as a variable to alter the monomer concentration in the aqueous phase. The emulsifier concentration in the feed was employed to alter the particle stability. Particle formation and coagulation were discussed in terms of critical surface coverage ratios. Particle coagulation occurred if the particle surface coverage dropped below θ_cr1 = 0.25 ± 0.05. The secondary nucleation occurred above a critical surface coverage of θ_cr2 = 0.55 ± 0.05. The number of particles remained approximately constant if the particle surface coverage was within θ_cr1 = 0.25 < θ < θ_cr2 = 0.55. This surface coverage band is equivalent to the surface tension band of 42.50 ± 5.0 dyne/cm that is required to avoid particle formation and coagulation in the course of polymerization. The kinetics of the water phase was shown to play an important role during homogeneous and micellar nucleations. For any fixed emulsifier concentration in the feed and above θ_cr2, the number of secondary particles increased with monomer concentration in the aqueous phase. Moreover, the presence of micelles in the reaction vessel is not the only perquisite for micellar nucleation to occur, a sufficient amount of monomer should be present in the aqueous phase to enhance the radical capture by partially monomer‐swollen micelles. The rate of polymerization increased with the surfactant concentration in the aqueous phase. © 2000 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 38: 3612–3630, 2000     

A numerical study of turbulent flow over a two‐dimensional hill

Calculations of mean velocities and Reynolds stresses are reported for the recirculating flow established in the wake of two‐dimensional polynomial‐shaped obstacles that are symmetrical about a vertical axis and mounted in the water channel downstream of a fully developed channel flow for Re=6×10⁴. The study involves calculations of mean and fluctuating flow properties in the streamwise and spanwise directions and include comparisons with experimental data [Almeida GP, Durão DFG, Heitor MV. Wake flows behind two‐dimensional model hills. Experimental Thermal and Fluid Science 1993; 7: 87–101] for flow around a single obstacle with data resulting from the interaction of consecutive obstacles, using two versions of the low‐Reynolds number differential second‐moment (DSM) closure model. The results include analysis of the turbulent stresses in local flow co‐ordinates and reveal flow structure qualitatively similar to that found in other turbulent flows with a reattachment zone. It is found that the standard isotropization of production model (IPM), based on that proposed by Gibson and Launder [Ground effects on pressure fluctuations in the atmospheric boundary layer. Journal of Fluid Mechanics 1978; 86(3): 191–511], with the incorporation of the wall reflection model of Craft and Launder [New wall‐reflection model applied to the turbulent impinging jet. AIAA Journal 1992; 32(12): 2970–2972] predicts the mean velocities quite well, but underestimates the size of the recirculation region and turbulent quantities in the shear layer. These inadequacies are circumvented by adopting a new cubic Reynolds stress closure scheme based on that more recently developed by Craft and Launder [A Reynolds stress closure designed for complex geometries. International Journal of Heat and Fluid Flow 1996; 17: 245–254] which satisfies the two component limit (TCL) of turbulence. In this model the geometry‐specific quantities, such as the wall‐normal vector or wall distance, are replaced by invariant dimensionless gradient indicators. Also, the model captures the diverse behaviour of the different components of the stress dissipation, ε_ij, near the wall and uses a novel decomposition for the fluctuating pressure terms. Copyright © 2001 John Wiley & Sons, Ltd.     

Exhaustive investigation of drug delivery systems to achieve optimal condition of drug release using non-linear generalized artificial neural network method: feedback from the loading step of drug

Drug delivery systems are potential systems with ability to release drugs with a variety of mechanisms. Some mechanisms may consist of multiple steps, where the release rate of each step can vary from the others. Moreover, a drug release is a kinetic process intrinsically and the initial amount of the loaded drug may influence the amount of the release. Therefore, to achieve the desirable release, the loading and release processes should be investigated simultaneously, while researchers have considered these processes independently so far. Considering the fact that functional dependence between loading and release is not obvious, we proposed the combination of experimental design and powerful non-linear generalized artificial neural network (G-ANN) methods for the simultaneous optimization of these processes. Here, the functionalized PEGylated KIT-6 ([β-CD@PEGylated KIT-6]) NPs and curcumin were selected as a nano-carrier and drug, respectively. The curcumin release was optimized by G-ANN by considering the the feedback from the loading step. The obtained optimal parameters were as follows: (in the release process) 1.80 of the weight ratio of drug to nano-carrier, 5.70 of pH and 120 h of release time; and (in the loading process) 43 h of loading time and 2.2 of weight ratio of drug/nano-carrier.     

Comparative study of monomer droplet nucleation in the seeded batch and semibatch miniemulsion polymerisation of styrene

Monomer droplet nucleation in the seeded miniemulsion polymerisation of styrene under monomer-flooded and monomer-starved conditions was studied. The miniemulsion feeds were added to the reactor either batchwise or semibatchwise. The droplets preserved longer under flooded conditions. As a result, the batch operation led to a larger number of particles (N_p) than the semibatch operation. For the miniemulsion droplets containing predissolved polymer, the final N_p was independent of the way that the feed was added to the reactor and was equivalent to the number of monomer droplets in the original miniemulsion feed. The size distribution of the final latexes, however, was influenced by the operation type. For the batch operation, the rate of polymerisation (R_p) with the miniemulsion feeds was higher than that with the conventional monomer emulsion feed because of the monomer droplet nucleation. But for the semibatch operation, the opposite was true because of R_p controlled by the rate of monomer diffusion from rather stable miniemulsion droplets to the growing polymer particles.     

Application of generalized artificial neural networks coupled with an orthogonal design to optimization of a system for the kinetic spectrophotometric determination of Hg(II)

A simple and sensitive kinetic method for the determination of traces of mercury (70-760 ng ml⁻¹) based on its inhibitory effect on the addition reaction between methyl green and sulfite ion is proposed. The reaction was monitored spectrophotometrically by measuring the decrease in absorbance of methyl green at 596 nm between 2 and 4 min using a fixed time method. Artificial neural networks with back propagation algorithm coupled with an orthogonal array design were applied to the modeling of the proposed kinetic system and optimization of experimental conditions. An orthogonal design was utilized to design the experimental protocol, in which pH, concentration of sulfite, temperature, and concentration of methyl green were varied simultaneously. Optimum experimental conditions in term of sensitivity were generated by using ANNs. The rate of decrease in absorbance is inversely proportional to the concentration of Hg(II) over entire concentration range tested (100-550 ng ml⁻¹) with a detection limit of 45 ng ml⁻¹ and a relative standard deviation at 200-400 ng ml⁻¹ Hg(II) of 3.2% (n=5). A simple preconcentration step improved the limit of detection and linear dynamic range of the method to about 8 and 12-760 ng ml⁻¹, respectively, by about 10 times enrichment of mercury between 12 and 75 ng ml⁻¹. The method was based on enrichment of Hg(II) from dilute samples on an anionic ion exchanger fixed on a plastic strip and was applied to the determination of Hg(II) in environmental samples with satisfactory results.     

Effect of MWCNT–Fe3O4/water hybrid nanofluid on the thermal performance of ribbed channel with apart sections of heating and cooling

Journal of Thermal Analysis and Calorimetry - A two-dimensional (2D) numerical simulation is performed to simulate the laminar forced convection of a nanofluid in a ribbed channel with apart...     

Resolving of Voltammetric Data for the Ni–Glycine and Cu–Glycine Complexation Systems with Reversible and Irreversible Electrochemical Response Using MCR-ALS

The Ni?Cglycine and Cu?Cglycine systems, which form successive complexes, were studied by differential pulse polarography. The Ni?Cglycine complexes were inert while the Cu?Cglycine system showed labile behavior. An irreversible electrochemical response was found for the Cu?Cglycine system. The data were analyzed both by conventional methods (hard modeling) and the multivariate curve resolution method with alternating least-squares optimization (MCR-ALS, soft modeling approach). Resolving titration data for Cu²⁺ and Ni²⁺ with glycine as the complexing ligand shows that this method is a powerful tool for the determination of stability constants of metal complexes, especially when the conventional methods involve complicated and time consuming approaches such as for systems with an irreversible reduction process. Although for labile complexes the current is not always linear with respect to the concentrations, the results obtained by the two approaches are similar, so the variation from linearity of the signals is small and can be neglected. Also, the analysis of the labile complex data by a Gaussian peak adjustment (GPA) algorithm showed that this system has a small deviation from bilinearity. Thus, the MCR method provided good estimations of the complexation parameters, and is suitable for use as a complementary tool for studying systems with successive labile or inert complexes with both reversible and irreversible responses. Differential pulse polarograms were measured at room temperature for buffer solutions with pH = 7.5 and 0.1?mol?L^?1 ionic strength.