Polystyrene latex particles bearing primary amine groups via soap‐free emulsion polymerization

Polystyrene latexes were prepared in the presence of an amino‐containing functional comonomer, N‐(3‐aminopropyl)methacrylamide hydrochloride (APMH), via soap‐free batch emulsion polymerization initiated by the cationic initiator 2,2′‐azobis(2‐amidinopropane) dihydrochloride. These latexes were characterized by studying the influence of the ionic comonomers on the polymerization kinetics, particle size, surface charge density and colloidal properties. The synthesized latexes were monodisperse with a final size between 100 and 600 nm depending on the APMH concentration. The initial polymerization rate and the particle number increased in accordance with the Smith–Ewart theory for soap‐free styrene emulsion polymerization with a hydrophilic functional comonomer. The final functionalization rate of the particles has been particularly studied with the intention of fitting the prepared latexes to be used in the immobilization of biological molecules for biological sample preparation and diagnostic applications. © 2020 Society of Chemical Industry     

A new video magnification technique using complex wavelets with Radon transform application

Magnifying micro-movements of natural videos that are undetectable by human eye has recently received considerable interests, due to its impact in numerous applications. In this paper, we use dual tree complex wavelet transform (DT-CWT), to analyze video frames in order to detect and magnify micro-movements to make them visible. We use DT-CWT, due to its excellent edge-preserving and nearly-shift invariant features. In order to detect any minor change in object’s spatial position, the paper proposes to modify the phases of the CWT coefficients decomposition of successive video frames. Furthermore, the paper applies Radon transform to track frame micro-movements without any temporal band-pass filtering. The paper starts by presenting a simple technique to design orthogonal filters that construct this CWT system. Next, it is shown that modifying the phase differences between the CWT coefficients of arbitrary frame and a reference one results in image spatial magnification. This in turn, makes these micro-movements seen and observable. Several simulation results are given, to show that the proposed technique competes very well to the existing micro-magnification approaches. In fact, as it manages to yield superior video quality in far less computation time.     

Effect of graphene loading on thermomechanical properties of poly(vinyl alcohol)/starch blend

Polymer nanocomposites based on poly(vinyl alcohol) (PVA)/starch blend and graphene were prepared by solution mixing and casting. Glycerol was used as a plasticizer and added in the starch dispersion. The uniform dispersion of graphene in water was achieved by using an Ultrasonicator Probe. The composites were characterized by FTIR, tensile properties, X‐ray diffraction (XRD), thermal analysis, and FE‐SEM studies. FTIR studies indicated probable hydrogen bonding interaction between the oxygen containing groups on graphene surface and the –OH groups in PVA and starch. Mechanical properties results showed that the optimum loading of graphene was 0.5 wt % in the blend. XRD studies indicated uniform dispersion of graphene in PVA/starch matrix upto 0.5 wt % loadings and further increase caused agglomeration. Thermal studies showed that the thermal stability of PVA increased and the crystallinity decreased in the presence of starch and graphene. FE‐SEM studies showed that incorporation of graphene increased the ductility of the composites. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41827.     

Instant Cyclohexene Epoxidation Over Ni-TUD-1 Under Ambient Conditions

Catalysis Letters - To avoid the aggregation problem and activity loss of nickel oxide (NiO) nanoparticles (NPs) in organic reactions, NiO NPs were incorporated into TUD-1 mesoporous material....     

Precipitation Behavior of Modified as Cast High Nitrogen Super Hard High‐Speed Tool Steel

The properties of high‐speed tool steels can be improved by modifying their chemical composition or the technology of production. Nitrogen alloying is an attractive technology to enhance the mechanical and physical properties of tool steels. In this work, modified super hard high‐speed tool steel was produced through nitrogen alloying and decreasing the level of cobalt content in investigated steels. This work aims to study the effect of nitrogen as alloying element on carbides and carbo‐nitrides precipitates type, shape, and size for investigated steels. From the results obtained from Thermo‐Calc, it was concluded that nitrogen alloying produced large amount of stable austenite, also eutectic carbides precipitates (M₆C and M₇C₃) were stable at room temperature. Transmission electron microscope (TEM) images for traditional grade showed that the as cast structure contains beside the carbides network other single carbides precipitates. While on the other hand the selected area diffraction pattern (SADP) images of nitrogen alloyed grade shows fine carbides and carbo‐nitrides precipitates with more amount of retained austenite in the ferrite matrix, they showed also the presence of the eutectic precipitates as well as the dislocations.     

The influence of low- and high-linear energy transfers on some physical properties of poly(methyl-methacrylate) samples

Clear poly(methyl-methacrylate)—PMMA—dosimeter is widely used in food irradiations. Positron annihilation lifetime spectroscopy (PALS) is one of the unique tools used for studying free-volumes and open-volume type defects in solid media. The Vicker's microhardness measurements offer a simple and nondestructive tool for investigating the mechanical behavior of polymer materials. PALS as well as microhardness measurements were carried out for PMMA samples, irradiated with low- and high-linear energy transfers (LET). The low-LET irradiations were provided at lethal doses of gamma radiations for vegetative bacteria. Such irradiations showed a chain scission in the PMMA samples. High-LET irradiations showed behavior different from the low-LET ones. The observed behavior depends on the alpha particle fluence. The microhardness testing was carried out for virgin and irradiated PMMA samples at high-LET. A negative correlation was found between PALS measurements and microhardness results. The optical characteristics and structural studies for the virgin and irradiated PMMA samples were in agreement with the PALS and microhardness measurements. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Compressibility factor model of sweet,sour, and condensate gases using genetic programming

Gas compressibility factor (z-factor) is necessary in most petroleum engineering calculations. The most common sources of z-factor values are experimental measurements, equations of state (EOS) and empirical correlations. There are more than twenty correlations available with two variables for calculating the z-factor from fitting Standing–Katz chart values in an EOS or just through fitting techniques. However, these correlations are too complex, which require initial value and longer computations, and have significant error. This work presents a new model for estimating z-factors of sweet gases, sour gases and gas condensates using genetic programming (GP). The z-factor model was developed using pseudo-reduced pressure, and pseudo-reduced temperature. Moreover, two new models of pseudo-critical pressure and temperature were built as a function of the gas composition (mol percent of C₁–C₇₊, H₂S, CO₂, and N₂) and the specific gravity of the C₇₊. The developed new GP-based model yields a more accurate prediction of gas z-factor compared to the commonly used correlations and EOS's.     

Development of artificial neural network models for supercritical fluid solvency in presence of co-solvents

This paper presents the application of artificial neural networks (ANN) to develop new models of liquid solvent dissolution of supercritical fluids with solutes in the presence of cosolvents. The neural network model of the liquid solvent dissolution of CO₂ was built as a function of pressure, temperature, and concentrations of the solutes and cosolvents. Different experimental measurements of liquid solvent dissolution of supercritical fluids (CO₂) with solutes in the presence of cosolvents were collected. The collected data are divided into two parts. The first part was used in building the models, and the second part was used to test and validate the developed models against the Peng-Robinson equation of state. The developed ANN models showed high accuracy, within the studied variables range, in predicting the solubility of the 2-naphthol, anthracene, and aspirin in the supercritical fluid in the presence and absence of co-solvents compared to (EoS). Therefore, the developed ANN models could be considered as a good tool in predicting the solubility of tested solutes in supercritical fluid.