Improvement of Giant Magnetoimpedance and Sensitivity in Co68.5-xFe4WxSi16.5B11 (x = 0.8, 2) Ribbons Sandwiched in PVA/Fe3O4 Nanocomposite Films

Journal of Superconductivity and Novel Magnetism - In this work, giant magnetoimpedance (GMI); magnetic hysteresis loop; and sensitivity of Co68.5Fe4Si16.5B11 (S), Co67.7Fe4W0.8Si16.5B11 (W1), and...     

Numerical simulation of a falling droplet surrounding by air under electric field using VOF method: A CFD study

This is a numerical study of a falling droplet surrounding by air under the electric field modeled with finite volume method by means of CFD. The VOF method has been employed to model the two-phase flow of the present study. Various capillary numbers are investigated to analyze the effects of electric field intensity on the falling droplet deformation. Also, the effects of electric potential on the heat transfer coefficient have been examined. The obtained results showed that by applying the electric field at a capillary number of 0.2 the droplet tends to retain its primitive shape as time goes by, with a subtle deformation to an oblate form. Intensifying the electric field to a capillary number of 0.8 droplet deformation is almost insignificant with time progressing; however, further enhancement in capillary number to 2 causes the droplet to deform as a prolate shape and higher values of this number intensify the prolate form deformation of the droplet and result in pinch-off phenomenon. Ultimately, it is showed that as the electric potential augments the heat transfer coefficient increases in which for electric potential values higher than 2400 V the heat transfer coefficient enhances significantly.     

Experimental characterization of the small strain shear modulus of soft clay stabilized with cement and nano-SiO2 using bender element tests

Bulletin of Engineering Geology and the Environment - The accurate and efficient modification of the static and dynamic properties of problematic soils is a primary concern in geotechnical...     

Sustainable optimization of waste management network over extended planning time horizon

This study proposes a multiperiod mixed integer linear programming model for the management of a single municipal solid waste (MSW) treatment plant with sustainability as the objective. Discrete and continuous variables define the capacity selections for diverse MSW technologies, and the operation of the MSW network, respectively. The economic target is considered to maximize the net present value. The environmental impact is the minimization of a normalized environmental objective function (NEOF). The social target is the maximization of jobs. An interesting feature about the research work is the requirement of biodrying technologies for MSW moisture content control. Due to the conflicted nature among the sustainability components, a multiobjective optimization (MO) is carried out to find the Pareto optimal solutions. The MO results show that the Pareto optimal solutions vary around profit range of $4.9–8.5 billion, NEOF impact range of 3.2–3.6 units, and social benefit range of 2700–4828 jobs.     

Nonmonotonic Coupled Dissolution-Precipitation Reactions at the Mineral–Water Interface

Dissolution is inherent to fluid-mineral systems. Yet its impact on minerals reacting with electrolytes is overlooked. Here, a novel nonmonotonic behavior for the surface interactions of carbonates (calcite and Mg-calcite) with organic acids is reported. Applying a bioinspired approach, Mg-calcite sensors via amorphous precursors, avoiding any preconditioning with functional groups are synthesized. A quartz crystal microbalance is used to study the mass changes of the mineral on contact with organic acids under varying ionic conditions, temperatures, and flow velocities. Supported by confocal Raman microscopy and potentiometric titrations, nonmonotonous mass developments are found as a function of Ca²⁺ concentration and flowrate, and attributed to three coupled chemical reactions: i) carbonate dissolution via Ca²⁺ ion complexation with organic molecules, and the formation of organo-calcium compounds as ii) a surface phase at the mineral–water interface, and iii) particles in the bulk fluid. These processes depend on local ion contents and the precipitation onset (i.e., saturation index) of organo-calcium salts, both of which substantially differ in the bulk fluid and in the fluid boundary layer at mineral interfaces. This continuum between dissolution and precipitation provides a conceptual framework to address reactions at mineral interfacial across disciplines including biomineralization, ocean acidification and reservoir geochemistry.     

Design and development of a simple and highly sensitive anthocyanin-based sensing device for colorimetric urea determination

We introduce a rapid anthocyanin-based paper sensor with very high sensitivity and optical visibility for colorimetric detection of urea. The working principle is based on a colour change from purple to blue upon sensor exposure to ammonia generated from urea hydrolysis in the presence of urease as a catalyst. To improve sensor sensitivity and optical visibility, anthocyanin storage, urease solvent, urea hydrolysis time, and temperature were investigated. The results indicated that the anthocyanin extracted from red cabbage and stored in dark and low-temperature conditions, urease extracted into water₅₅ + glycerol₄₅ (Aq₅₅ + G₄₅), and urea hydrolysis time of 40 min and temperature of 45°C offer the best detection condition. The fabricated sensor showed exceptional sensitivity of 0.018 pixel/mg urea-N/L with a very low limit of detection (2.01 mg urea-N/L) and a limit of quantification (6.71 mg urea-N/L). Moreover, the sensor reaction zone is optically visible for urea concentration as low as 5 mg urea-N/L, making it a promising tool for urea screening in diverse applications. The unique analytical features and accuracy of the sensor compared to the spectrophotometry method also suggest that it can be used as a replacement for environmentally unfriendly spectrophotometry methods for on-site urea determination.     

Novel NGR anchored pullulan micelles for controlled and targeted delivery of doxorubicin to HeLa cancerous cells

Doxorubicin (DOX) is used to treat different kinds of cancers, including cervix carcinoma. However, it has various side effects such as cardiotoxicity. Nano-sized controlled releasing carriers such as polymeric micelles are of interesting approaches to overcome these side effects of doxorubicin in cancer chemotherapy. Regarding the up-regulation of CD13/APN receptors on the cervix carcinoma cells, which can bind to peptide sequences specially NGR (asparagine–glycine–arginine) with high affinity, peptide sequence (NGR) targeted micelles would lead to effective treatment of this carcinoma. In this study, the NGR peptide sequence was synthesized using the solution-phase strategy from asparagine, glycine, and arginine residues. The pullulan–retinoic acid conjugate and pullulan–retinoic acid–NGR conjugate were prepared by the amide and ester bond formation between the hydroxyl groups of pullulan and carboxylic acid groups of retinoic acid and peptide sequence. Pullulan–retinoic acid–NGR micelles were prepared by the direct dissolution method. The optimized micelles, according to their particle size (124.5 nm), zeta potential (? 3.65 mV), entrapment efficiency (85%), and release of DOX (70%, within 72 h) were assessed for their cytotoxicity on HeLa cells using MTT assay. NGR-targeted pullulan/retinoic acid micelles had higher cytotoxicity than the free DOX in cell culture studies on the HeLa cell line, and this can be a promising result in the treatment of cervix carcinoma.     

Prediction of phosphorus content of electroless nickel–phosphorous coatings using artificial neural network modeling

A multilayer feedforward neural network with two hidden layers was designed and developed for prediction of the phosphorus content of electroless Ni–P coatings. The input parameters of the network were the pH, metal turnover, and loading of an electroless bath. The output parameter was the phosphorus content of the electroless Ni–P coatings. The temperature and molar rate of the bath were constant ( 91^° \textC, 0.4 \textNi^{\text + +} /\textH₂ \textPO₂ ^{- -} 91^\circ {\text{C}},\:0.4\,{\text{Ni}}^{{{\text{ + + }}}} /{\text{H}}_{2} {\text{PO}}_{2}^{{ - - }} ). The network was trained and tested using the data gathered from our own experiments. The goal of the study was to estimate the accuracy of this type of neural network in prediction of the phosphorus content. The study result shows that this type of network has high accuracy even when the number of hidden neurons is very low. Some comparison between the network’s predictions and own experimental data are given.