Chemical vapor deposition of poly(3‐alkylthiophene) nanoparticles on fabric: Chemical and electrochemical characterization

Chemical vapor deposition of poly(3‐methylthiophene) and poly (3‐hexylthiophene) as conductive polymers on the surface of polyester fabrics was successfully obtained. Fourier transform infrared spectroscopy confirmed the formation of polymers on surface of fabrics (the fingerprint of polythiophenes, υ 600–1500 cm^?1). The uniformity of deposition and nanoparticles (average size of 60 nm) were proved with scanning electron microscopy. Electrochemical impedance spectroscopy showed that P3HT‐coated samples offer higher conductivity in compared to P3MT‐coated samples. The impedance modulus of P3HT‐coated samples was lowered nine times to that of row materials and reached to c8000 Ω. The samples have also shown electrochromic properties under electrical current, changing its color from yellowish green at 0 V to dark green at +12 V for poly (3‐hexylthiophene) samples and from brown at 0 V to red at +12 V for poly(3‐methylthiophene)‐coated fabrics (V = 0 V, λ = 450 nm; V = 12 V, λ = 650 nm). © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40673.     

Genomics and Epigenomics of Gestational Diabetes Mellitus: Understanding the Molecular Pathways of the Disease Pathogenesis

One of the most common complications during pregnancy is gestational diabetes mellitus (GDM), hyperglycemia that occurs for the first time during pregnancy. The condition is multifactorial, caused by an interaction between genetic, epigenetic, and environmental factors. However, the underlying mechanisms responsible for its pathogenesis remain elusive. Moreover, in contrast to several common metabolic disorders, molecular research in GDM is lagging. It is important to recognize that GDM is still commonly diagnosed during the second trimester of pregnancy using the oral glucose tolerance test (OGGT), at a time when both a fetal and maternal pathophysiology is already present, demonstrating the increased blood glucose levels associated with exacerbated insulin resistance. Therefore, early detection of metabolic changes and associated epigenetic and genetic factors that can lead to an improved prediction of adverse pregnancy outcomes and future cardio-metabolic pathologies in GDM women and their children is imperative. Several genomic and epigenetic approaches have been used to identify the genes, genetic variants, metabolic pathways, and epigenetic modifications involved in GDM to determine its etiology. In this article, we explore these factors as well as how their functional effects may contribute to immediate and future pathologies in women with GDM and their offspring from birth to adulthood. We also discuss how these approaches contribute to the changes in different molecular pathways that contribute to the GDM pathogenesis, with a special focus on the development of insulin resistance.     

Development of High Strength and Toughness Non-Heated Al–Mg–Si Alloys for High-Pressure Die-Casting

Based on the 3 factors and 3 levels orthogonal experiment method, compositional effects of Mg, Si, and Ti addition on the microstructures, tensile properties, and fracture behaviors of the high-pressure die-casting Al-x Mg-y Si-z Ti alloys have been investigated. The analysis of variance shows that both Mg and Si apparently infl uence the tensile properties of the alloys, while Ti does not. The tensile mechanical properties are comprehensively infl uenced by the amount of eutectic phase(α-Al + Mg_2Si), the average grain size, and the content of Mg dissolved into α-Al matrix. The optimized alloy is Al-7.49 Mg-3.08 Si-0.01 Ti(wt%), which exhibits tensile yield strength of 219 MPa, ultimate tensile strength of 401 MPa, and elongation of 10.5%. Furthermore, contour maps, showing the relationship among compositions, microstructure characteristics, and the tensile properties are constructed, which provide guidelines for developing high strength and toughness Al–Mg–Si–Ti alloys for high-pressure die-casting.     

Mechanochemical sulfidization of a mixed oxide-sulphide copper ore by co-grinding with sulfur and its effect on the flotation efficiency

Mechanochemical sulfidization of a mixed sulfide/oxide copper ore by co-grinding with sulfur and additives including Mg(NO₃)₂ and Fe(NO₃)₃ salts and iron, aluminum and magnesium powders was investigated for the first time. Also, the influence of sulfidization during the wet-milling process was examined on the separation efficiency and recovery of copper in detail. The results demonstrated that co-grinding with sulfur solely had the best flotation performance at the value of 0.5 wt.% and it was attributed to the possible existence of S-O bonding on copper oxides surfaces. In addition, adding magnesium nitrate salt, magnesium powder, iron nitrate salt and aluminum powder as additive associated with 0.5 wt% sulfur into ball milling caused the flotation improvement at the amounts of 0.2 wt%, 0.2 wt%, 0.5 wt% and 0.5 wt%, respectively. Also, the effect of grinding time and sulfidization pH with 0.5 wt% sulfur solely was determined and pHs of 7.5 to 8.5 gave the best results. The highest recovery (75.76%) and separation efficiency (63.44%) were achieved at pH of 7.5 and 8.5, respectively.     

Investigation of structural,optical, electrical,and magnetic properties of Fe-doped La0.7Sr0.3MnO3 manganites

In this work, the physical properties of nanocrystalline samples of La_0.7Sr_0.3Mn_1−xFe_xO₃ (0.0 ≤ x ≤ 0.20) perovskite manganites synthesized by the reverse micelle (RM) technique were explored in detail. The phase purity, crystal structure, and crystallite size of the samples were determined using X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy. All the samples had rhombohedral crystal structure and crystallite size increased with increase in Fe content in La_0.7Sr_0.3MnO₃. The scanning electron micrographs (SEMs) exhibited smooth surface morphology and nonuniform shape of the particles. The optical properties studied using UV-visible absorption spectroscopy revealed a decrease in the absorbance and optical band gap with an increase in Fe content in La_0.7Sr_0.3MnO₃ compound. The temperature-dependent resistivity measurements revealed semiconducting nature of x = 0 and 0.1 samples up to the studied temperature range, while a metal-to-insulator transition was observed at higher Fe doping. Magnetic studies revealed weak ferromagnetism in all the samples and a reduction in the maximum magnetization with an increase in Fe content. A close correlation between electrical transport and magnetic properties was observed with the doping of Fe ion in La_0.7Sr_0.3MnO₃ at Mn site. These results advocate strong interactions associated with the double exchange mechanism among Fe³⁺ and Mn³⁺ ions.     

Molecular weight averages as criteria for quality assessment of heated oils and fats

A simple method for quality assessment of heated oils and fats is described. The proposed method involves precise determination of molecular weight averages (MWA)viz., the weight average molecular weight ( ), the number average molecular weight ( ) and the Z-average molecular weight ( ) by high performance size exclusion chromatography (HPSEC) and their quantitative correlation to percent polar material obtained by column chromatography (CC). Change in MWA on heat treatment of fourteen different edible oils and fats at 180° ± 2°C for eight 8-hr days is studied. Relative standard deviations and regression coefficients of correlation between MWA and their ratios ( , { }, { }, { }, { } and { )vs percent polar material have been reported. Probable discard time was predicted for all the oils based on the above-mentioned correlations and also from the percent of high molecular weight (H. Mwt) species formed. It was observed that the oils which are generally recommended for coronary patients deteriorated faster. A possibility of extending this methodology to the frying oils is suggested. Part of the work was presented at “40th Pittsburgh Conference on Analytical Chemistry and Applied Spectroscopy” at Georgia World Congress Centre, USA, 1989. IICT Communication No. 2630.     

Lipid Class and Fatty Acid Composition of Psoralia corylifolia Seed

The purified crude lipid of Psoralia corylifolia seeds was subjected to lipid class and fatty acid analysis by thin layer and gas chromatography. The lipid classes identified were triacyl glycerol, free fatty acid, diacyl glycerol, mono acyl glycerol, hydrocarbon-waxester and polar lipid fractions. Most of the fractions were found to contain high level of C_18:1 while C_18:0, C_18:3 and C_20:0 were also found to be present in all the lipid fractions. It has been observed that the diacyl and monoacyl glycerol fractions contain significant amounts of C_14:0 and C_18:0 while the hydrocarbon-waxester fraction was rich in C_22:0. The polar lipids contain high level of C_18:3 and low level of C_18:1 as compared to other lipid fractions. The fatty acid composition of the whole oil was also determined and found to be similar to other fractions. Unidentified long chain fatty acids were also present in significant amounts in all the lipid fractions.     

CFD and artificial neural network modeling of two-phase flow pressure drop

A large number of experiments in a 2 cm diameter and 6 m length tube were carried out in order to study the two-phase flow regimes and pressure drops in it. The two-phase flow in the experimental tube was modeled using commercial CFD code, Fluent 6.2. An Artificial Neural Network (ANN) with three inputs including gas and liquid velocities and tube slope was designed and trained to predict average pressure drop across the tube. The comparison between CFD and ANN predictions of pressure drops with experimental measurements shows that the CFD results are more accurate than the ANN evaluations for new conditions.     

A hybrid lithium‐ion battery model for system‐level analyses

We describe an advanced lithium‐ion battery model for system‐level analyses such as electric vehicle fleet simulation or distributed energy storage applications. The model combines an empirical multi‐parameter model and an artificial neural network with particular emphasis on thermal effects such as battery internal heating. The model is fast and can accurately describe constant current charging and discharging of a battery cell at a variety of ambient temperatures. Comparison to a commonly used linear kilowatt‐hour counter battery model indicates that a linear model overestimates the usable capacity of a battery at low temperatures. We highlight the importance of including internal heating in a battery model at low temperatures, as more capacity is available when internal heating is taken into account. Copyright © 2016 John Wiley & Sons, Ltd.