Melt intercalation/exfoliation of polystyrene-sodium-montmorillonite nanocomposites using sulfonated polystyrene ionomer compatibilizers

Quaternary ammonium salts of sulfonated polystyrene (SPS) were used as compatibilizers for melt intercalation of PS and pristine Na-montmorillonite. Tetra-octyl ammonium SPS and tetra-decyl ammonium SPS ionomeric compatibilizers produced significant exfoliation and a homogeneous dispersion of the polymer-clay nanocomposites. Wide angle X-ray diffraction and transmission electron microscopy were primarily used to characterize the morphology of the nanocomposites. Image analysis was used to measure the percentage exfoliation. Exfoliation increased with the increasing length of the alkyl chain of the ammonium counter-ion of the SPS ionomer. The nanocomposites containing ionomers exhibited higher storage moduli compared to nanocomposites without the compatibilizer.     

Esterification of acrylic acid with methanol by reactive chromatography: Experiments and simulations

The esterification of acrylic acid with methanol using Amberlyst 15 as a stationary phase has been investigated using a chromatographic reactor. Several experimental runs at various operating conditions have been conducted on a batch column. A classical reactive chromatography model including lumped kinetics, a linear driving force transport model and a heterogeneous kinetic model for the catalytic reaction has been developed. The additional dispersion of concentration fronts due to density gradient effects has been accounted for in the model. The model parameters have been determined in a fast and reliable way by directly fitting the batch column experiments. In general, a good agreement between experimental and calculated results is obtained. The evaluation of the covariance of the fitted model parameters reveals important insights about the system behavior.Based on the detailed batch column model, a complete model of a simulated-moving-bed reactor has been implemented and its optimal point of operation for the synthesis of methyl acrylate from acrylic acid has been determined. Particularly when considering the low-operating temperature, we can regard this process as a possible competition for current technologies.     

Oxidation of hydrosulphide ions on gold Part I: A cyclic voltammetry study

The results of an investigation to determine the mechanism(s) of oxidation of sulphide ions on a gold electrode are discussed. The cyclic voltammetry results are presented in Part I and characterization results after various electrochemical pretreatments are to follow in Part II. The cyclic voltammetry studies show that several stages are involved in oxidation of sulphide ions to form elemental sulphur. Initially, sulphide ions undergo underpotential deposition to form chemisorbed sulphur as isolated atoms. As oxidation proceeds, a monolayer of chemisorbed atoms is formed which reacts with sulphide ions in solution to form polysulphides at higher potentials. As the potential for oxidation is further increased elemental sulphur is produced. The reduction of polysulphide to hydrosulphide ions occurs by a 2-electron transfer process whereas the reduction of elemental sulphur occurs by a l-electron transfer process. The latter reaction involves the formation of an activated complex which is a relatively slow process.     

An Authentication Based Approach for Prevention of Spectrum Sensing Data Falsification Attacks in Cognitive Radio Network

Wireless Personal Communications - This is the era of Intelligent Cognitive Radio Network (CRN) technology that provides the available spectrum with efficient utilization. Cognitive Radio (CR)...     

Experimental investigations in powder mixed electric discharge machining of Ti–35Nb–7Ta–5Zrβ-titanium alloy

The present research is the first type of study in which the application of powder mixed electrical discharge machining (PMEDM) for the machining of β-phase titanium (β-Ti) alloy has been proposed. β-Ti alloys are new range of titanium alloys, which has a wide-spread application in dental, orthopedics, shape memory, and stents. The aim of the present study is to fabricate submicro- and nanoscale topography by PMEDM process to enhance the biocompatibility without affecting machining efficiency. The effect of Si powder concentration along with pulse current and duration on the surface and machining characteristics has been investigated. A significant decrease in surface crack density on the machined surface with 4 g/l Si powder concentration was observed. When β-Ti alloy was modified at 15 A pulse current, longer pulse interval with 8 g/l concentration of Si powder particles, the interconnected surface porosities with pore size 200–500 nm was observed. Moreover, at Si powder concentrations of 2 g/l and 4 g/l, the recast layer thickness is 8 µm and 2–3 µm, respectively. Elemental mapping analysis confirmed that PMEDM also generated carbides and oxides enriched surface, a favorable surface chemistry to enhance the biocompatibility of β-Ti alloy. Furthermore, PMEDM also enhances the machining performance by improving material removal rate and reducing tool wear rate.     

Self-nanoemulsifying drug delivery system of docosahexanoic acid: development,in vitro,in vivo characterization

Context: Docosahexanoic acid (DHA) is an essential omega-3 fatty acid for normal brain development and its use has increased considerably in recent years.

Objective: The aim of this study is to develop and evaluate self-nanoemulsifying drug delivery systems (SNEDDS) of DHA for improved palatability, dispersibility and bioavailability.

Methods: The SNEDDS were prepared and evaluated for miscibility, employing different combinations of olive oil and soyabean oil as oil phase, Span 80, Span 20, soya phosphatidylcholine, Labrafil M 1944 CS as surfactants while Tween 80, PEG 400, Cremophor RH40 and propylene glycol as cosurfactants. Thermodynamically stable SNEDDS were characterized for dispersibility, self-emulsification time, droplet size, zeta potential along with sensory analysis. The optimized formulation was subjected to ex vivo and in vivo evaluation such as intestinal permeability, memory performance test, brain concentration and histopathology studies.

Results: The optimized SNEDDS formulation showed emulsification time of 27?±?4.7?s with droplet size of 17.6?±?3.5?nm and zeta potential of??37.6?±?0.5?mV. Intestinal absorption study depicted 18.3%, 21.5%, 41.5%, 98.7% absorption of DHA with SNEDDS-based formulation in comparison to 8.2%, 15.1%, 28.8%, 46.1% absorption of DHA with oil-based marketed formulation after 0.5, 1, 2 and 4?h. DHA concentration in brain homogenate was found to be increased to 2.6-fold in comparison to DHA-marketed formulation. This could be ascribed to enhanced dispersibility and bioavailability of DHA from nanosized formulation.

Conclusion: The developed formulation led to enhanced dispersibility and bioavailability of DHA due to the formation of nanodroplets.     

Machine Learning-Informed Predictive Design and Analysis of Electrohydrodynamic Printing Systems

Electrohydrodynamic (EHD) processes are promising techniques for manufacturing nanoscopic products with different shapes (such as thin films, nanofibers, 2D/3D nanostructures, and nanoparticles) and materials at a low cost using simple equipment. A key challenge in their adoption by nonexperts is the requirement of enormous time and resources in identifying the optimum design/process parameters for the underlying material and EHD system. Machine learning (ML) has made exciting advancements in predictive modeling of different processes, provided it is trained on high-quality datasets at appropriate volumes. This article extends the suitability of such ML-enabled approaches to a new technological domain of EHD spraying and drop-on-demand printing. Different ML models like ridge regression, random forest regression, support vector regression, gradient boosting regression, and multilayer perceptron are trained and their performance using evaluation metrics like RMSE and R2_score is examined. Tree-based algorithms like gradient boosting regression are found to be the most suitable technique for modeling EHD processes. The trained ML models show substantially higher accuracy (average error < 5%) in replicating these nonlinear processes as compared to previously reported scaling laws (average error ≈ 42%) and are well suited for predictive modeling/analysis of the underlying EHD system and process.     

In2O3 + xBaO (x = 0.5-5 at.%) - A novel material for trace level detection of NOx in the ambient

Indium oxide (In₂O₃) doped with 0.5-5 at.% of Ba was examined for their response towards trace levels of NO_x in the ambient. Crystallographic phase studies, electrical conductivity and sensor studies for NO_x with cross interference for hydrogen, petroleum gas (PG) and ammonia were carried out. Bulk compositions with x ≤ 1 at.% of Ba exhibited high response towards NO_x with extremely low cross interference for hydrogen, PG and ammonia, offering high selectivity. Thin films of 0.5 at.% Ba doped In₂O₃ were deposited using pulsed laser deposition technique using an excimer laser (KrF) operating at a wavelength of (λ) 248 nm with a fluence of ∼3 J/cm² and pulsed at 10 Hz. Thin film sensors exhibited better response towards 3 ppm NO_x quite reliably and reproducibly and offer the potential to develop NO_x sensors (Threshold limit value of NO₂ and NO is 3 and 25 ppm, respectively).     

A new social and momentum component adaptive PSO algorithm for image segmentation

In this paper, we present a new variant of Particle Swarm Optimization (PSO) for image segmentation using optimal multi-level thresholding. Some objective functions which are very efficient for bi-level thresholding purpose are not suitable for multi-level thresholding due to the exponential growth of computational complexity. The present paper also proposes an iterative scheme that is practically more suitable for obtaining initial values of candidate multilevel thresholds. This self iterative scheme is proposed to find the suitable number of thresholds that should be used to segment an image. This iterative scheme is based on the well known Otsu’s method, which shows a linear growth of computational complexity. The thresholds resulting from the iterative scheme are taken as initial thresholds and the particles are created randomly around these thresholds, for the proposed PSO variant. The proposed PSO algorithm makes a new contribution in adapting ‘social’ and ‘momentum’ components of the velocity equation for particle move updates. The proposed segmentation method is employed for four benchmark images and the performances obtained outperform results obtained with well known methods, like Gaussian-smoothing method (Lim, Y. K., & Lee, S. U. (1990). On the color image segmentation algorithm based on the thresholding and the fuzzy c-means techniques. Pattern Recognition, 23, 935–952; Tsai, D. M. (1995). A fast thresholding selection procedure for multimodal and unimodal histograms. Pattern Recognition Letters, 16, 653–666), Symmetry-duality method (Yin, P. Y., & Chen, L. H. (1993). New method for multilevel thresholding using the symmetry and duality of the histogram. Journal of Electronics and Imaging, 2, 337–344), GA-based algorithm (Yin, P. -Y. (1999). A fast scheme for optimal thresholding using genetic algorithms. Signal Processing, 72, 85–95) and the basic PSO variant employing linearly decreasing inertia weight factor.