Fabrication of core–shell nanocomposites with enhanced photocatalytic efficacy

The current study establishes the unprecedented involvement in the evolution and production of novel core–shell nanocomposites composed of nanosized titanium dioxide and aniline‐o‐phenylenediamine copolymer. TiO₂@copoly(aniline and o‐phenylenediamine) (TiO₂@PANI‐o‐PDA) core–shell nanocomposites were chemically synthesized in a molar ratio of 5:1 of the particular monomers and several weights of nano‐TiO₂ via oxidative copolymerization. The construction of the TiO₂@PANI‐o‐PDA core–shell nanocomposites was ascertained from Fourier transform IR spectroscopy, UV–visible spectroscopy and XRD. A reasonable thermal behavior for the original copolymer and the TiO₂@PANI‐o‐PDA core–shell nanocomposites was investigated. The bare PANI‐o‐PDA copolymer was thermally less stable than the TiO₂@PANI‐o‐PDA nanocomposites. The core–shell feature of the nanocomposites was found to have core and shell sizes of 17 nm and 19–26 nm, respectively. In addition, it was found that the addition of a high ratio of TiO₂ nanoparticles increases the electrical conductivity and consequently lowers the electrical resistivity of the TiO₂@PANI‐o‐PDA core–shell nanocomposites. The hybrid photocatalysts exhibit a dramatic photocatalytic efficacy of methylene blue degradation under solar light irradiation. A plausible interpretation of the photocatalytic degradation results of methylene blue is also demonstrated. Our setup introduces a facile, inexpensive, unique and efficient technique for developing new core–shell nanomaterials with various required functionalities and colloidal stabilities. © 2018 Society of Chemical Industry     

Thermal induced transformations in glassy chalcogenides SixTe60−xAs30Ge10

Temperature-induced transformations are considered to be interesting characteristic properties of amorphous materials including the Si _x Te_60–x As₃₀Ge₁₀ system, withx=5, 10, 12 and 20. Density (), X-ray diffraction and differential thermal analysis (DTA) were used to characterize the compositions. DTA traces of each glass composition at different heating rates from 5 to 30° C min^–1 were obtained and interpreted. Fast and slow cooling cycles were used to determine the rate of structure formation. Cycling studies of materials show no memory effect but only ovonic switching action. The compositional dependence of the crystallization activation energy (E) and the coefficient of glass-forming tendency (K _gl) have been calculated. The thermal transition temperatures and associated changes in specific heat have been examined as a function of the Te/Si ratio by differential scanning calorimetry. It was found that andE increase linearly with increasing tellurium content, while the heat capacity (c _p) andK _gl, decrease with increasing tellurium content.E=1.54 eV andc _p=0.246 J g^–1 K^–1 forx=20 whileE=2.74eV andc _p=0.22 J g^–1 K^–1 forx=5.     

Effect of the Te/Si ratio on the electrical characteristics of the amorphous chalcogenide switches

The effect of composition on amorphous chalcogenide threshold switches of the system Si _x Te_60-x As₃₀Ge₁₀, wherex = 5, 10, 12 and 20, has been studied. The compositionx = 5 shows the best switching characteristics, e.g. the smallest holding voltage (V _h = 0.4V), the highest ON state current (I _h = 45A) and smallest threshold voltage (V _s = 1.5V). Applying the three mechanisms of conductance of Mottet al. (Phil. Mag. 37 (1975) 961), it is found that for a particular composition ₂ < ₁ < ₀ (the pre-exponential factors) andW ₂ < (E _a –E ₁ +W ₁) < (E _c –E _f) (whereE _a,E _c andE _e = activation energies at band edge, fermi level and conduction band;W ₁ andW ₂ = activation energy for hopping). It was found that the density of states at the fermi levelN(E _f) increases with the decrease of silicon content. The results provided further evidence against thermal interpretations and thereby support electronic models of threshold switching for these glass systems.     

Feature extraction and ML techniques for static gesture recognition

The main objective of this study is to explore the utility of a neural network-based approach in hand gesture recognition. The proposed system presents two recognition algorithms to recognize a set of six specific static hand gestures, namely open, close, cut, paste, maximize, and minimize. The hand gesture image is passed through three stages: preprocessing, feature extraction, and classification. In the first method, the hand contour is used as a feature that treats scaling and translation of problems (in some cases). However, the complex moment algorithm is used to describe the hand gesture and to treat the rotation problem in addition to scaling and translation. The back-propagation learning algorithm is employed in the multilayer neural network classifier. The second method proposed in this article achieves better recognition rate than the first method.     

Corrosion inhibition of triethanolammonium bromide mono- and dibenzoate as cationic inhibitors in an acidic medium

A weight loss technique was used to determine the corrosion inhibition efficiency of synthesized alkyl mono-and dibenzoate triethanolammonium bromide derivatives (TEAMB, TEADB) in an acidic medium (2 N HCl) at different doses (50, 100, and 200 ppm). The results showed that monoderivatives had a higher corrosion inhibition efficiency than diderivatives. The results were correlated with several factors, including the alkyl chain length of the hydrophobic chains, interfacial tension (IT), critical micelle concentration (CMC), and adsorption free energy of these inhibitors. Increasing the geometric length of the alkyl chains in the synthesized inhibitors had an increasing effect on their corrosion inhibition efficiency, whereas decreasing the CMC and IT had an increasing effect on their tendency toward corrosion inhibition. The number of hydrophobic chains attached to the inhibitor molecules had a vital influence on their efficiency as corrosion inhibitors.     

Sorption of uranium from waste effluent solutions by mesoporous carbon impregnated with trioctylamine

A new mesoporous adsorbent for uranium removal from waste effluents was prepared, characterized, and impregnated with trioctylamine. The adsorption efficiency was investigated as a function of pH, contact time, initial uranium concentration, competing ions, solid/liquid ratio, and temperature using batch sorption techniques. The maximum adsorption capacity was 21.9 mg g^–1 at pH 5. The equilibrium data fit well with the Langmuir adsorption isotherm. Kinetic study showed that the process was fast and reached equilibrium within 60 min. The kinetic data fit well with the pseudo-second-order law. Thermodynamic data show that the process is spontaneous and exothermic.     

Uranium extraction from nitric acid liquors using 4-methylpentan-2-one

Solvent extraction of uranium ions with 4-methylpentan-2-one was examined. The diluent, extractant concentration, aqueous to organic phase ratio, and contact time were varied. Different stripping agents were examined to reach the optimum stripping conditions. The results obtained show that uranium can be quantitatively extracted from 5 M nitric acid with 7% 4-methylpentan-2-one dissolved in refined kerosene and stripped from the organic phase with 5% Na₂CO₃. The equilibrium is attained within 10 min. Uranium can be efficiently separated from a large number of elements by adding EDTA salt to the stripping solution before uranium precipitation.     

Real-time quality authentication of honey using atmospheric pressure chemical ionisation mass spectrometry (APCI-MS)

The aim of this study was to use gas chromatography-mass spectrometry (GC-MS) and APCI-MS techniques to detect adulteration in honey. The key volatile compounds in the headspace of the adulterated honey were marked by GC-MS and their representative fragment ions were utilised in scanning honey samples using the real-time APCI-MS system. The PLS models validated using independent data sets resulted in coefficient of the determination () of 0.97 and 0.96 and root mean square error in prediction (RMSEP) of 2.62 and 2.45 for the GC-MS and APCI-MS data sets respectively. The most efficient volatiles from GC-MS analysis and their corresponding fragment ions m/z from APCI-MS data analysis were then identified and used to develop new PLS models to predict the level of adulteration. The best PLS model gave of 0.95 and RMEP of 2.60% in the independent validation set indicating that the model was very accurate in predicting the level of adulteration.