Stretchable strain sensors based on polyaniline/thermoplastic polyurethane blends

Polymer Bulletin - Thermoplastic polyurethane/polyaniline-based stretchable strain sensors were prepared via in situ polymerization of aniline in the TPU solution in the form of thin films. The...     

Synthesis and Characterization of Anionic Polymeric Surfactants Based on Sulfonated Styrene

A novel series of three anionic polymeric surfactants was prepared by polymerization of sulfonated styrene and allyl esters of long chain fatty acid chlorides (decanoyl, lauroyl and palmitoyl chloride). The unique structural features of these surfactants were confirmed by different spectroscopic tools (IR and H-NMR). The surface properties of these compounds such as surface tension, interfacial tension, emulsion stability, wetting power, foam height, solubilization and dispersant properties in disperse dye systems were determined and evaluated. A comparative study was done between the chemical structures and surface properties of these compounds. Biodegradability and stability to hydrolysis in acidic and alkaline medium were also determined and evaluated.     

Engineering multi-dimensional nanocarbons with enhanced electrochemical activity as high-performance bifunctional electrocatalyst

Environment-friendly metal-free electrocatalysts with high performance and stability are highly desirable for energy conversion and storage instead of noble metal materials. Here we report a three dimensional carbon-based porous aerogel as a bifunctional electrocatalyst by combining carbon nanostructures of various dimensionalities such as carbon onions, carbon nanotubes and graphene oxide. Notably, this all-carbon composite without any transition-metal or heteroatom doping exhibits excellent performance towards both oxygen evolution and oxygen reduction reactions. Our characterizations reveal that the enhancement can be ascribed to the porous-rich structure and large specific surface areas in the integrated nanocarbons architectures. This strategy represents a step toward the design of all-carbon bifunctional catalysts with high performance and low cost.     

First‐Principle Study of Structural,Electronic, and Magnetic Properties of Strontium Mono Ferrite Ceramic

In this research, structural, electronic, and magnetic properties of Strontium mono ferrite ceramic were studied. The calculations were performed by Full‐Potential‐Linearized Augmented Plane Wave method in the framework density functional theory with different approximations. The results suggest that among the four states of nonmagnetic, ferromagnetic, antiferromagnetic, and ferrimagnetic of SrFe₂O₄, ferrimagnetic is the most stable state. “Generalized Gradient” and “Local Spin Density” approximations were not an appropriate approach to calculate the band gap and magnetic moment of the compound. Therefore, other approximations such as GGA+U, LSDA+U, and modified Becke–Johnson were used. Band gap and lattice constants improved using these approximations. The Hubbard parameter was calculated (U_eff = 4.5 eV) by an ab initio method. Then, the electronic properties of SrFe₂O₄ such as band gap, exchange constant, and magneto crystalline anisotropy as well as the influence of pressure on these properties were investigated by using GGA+U approximation. Calculated magnetic moment for strontium mono ferrite is equal to 2.72 μ_B in the semiconductor state. Lattice constant results are in consistent with experimental studies. However, the amounts for bulk modulus, magnetic moment, and band gap have been not estimated experimentally.     

Optimising multi-product multi-chance-constraint inventory control system with stochastic period lengths and total discount under fuzzy purchasing price and holding costs

While the usual assumptions in multi-periodic inventory control problems are that the orders are placed at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this article, we relax these assumptions and assume that the periods between two replenishments of the products are independent and identically distributed random variables. Furthermore, assuming that the purchasing price are triangular fuzzy variables, the quantities of the orders are of integer-type and that there are space and service level constraints, total discount are considered to purchase products and a combination of back-order and lost-sales are taken into account for the shortages. We show that the model of this problem is a fuzzy mixed-integer nonlinear programming type and in order to solve it, a hybrid meta-heuristic intelligent algorithm is proposed. At the end, a numerical example is given to demonstrate the applicability of the proposed methodology and to compare its performance with one of the existing algorithms in real world inventory control problems.     

A Finite Difference Method and Effective Modification of Gradient Descent Optimization Algorithm for MHD Fluid Flow Over a Linearly Stretching Surface

Present contribution is concerned with the construction and application of a numerical method for the fluid flow problem over a linearly stretching surface with the modification of standard Gradient descent Algorithm to solve the resulted difference equation. The flow problem is constructed using continuity, and Navier Stoke equations and these PDEs are further converted into boundary value problem by applying suitable similarity transformations. A central finite difference method is proposed that gives third-order accuracy using three grid points. The stability conditions of the present proposed method using a Gauss-Seidel iterative procedure is found using VonNeumann stability criteria and order of the finite difference method is proved by applying the Taylor series on the discretised equation. The comparison of the presently modified optimisation algorithm with the Gauss-Seidel iterative method and standard Newton’s method in optimisation is also made. It can be concluded that the presently modified optimisation Algorithm takes a few iterations to converge with a small value of the parameter contained in it compared with the standard descent algorithm that may take millions of iterations to converge. The present modification of the steepest descent method converges faster than Gauss-Seidel method and standard steepest descent method, and it may also overcome the deficiency of singular hessian arise in Newton’s method for some of the cases that may arise in optimisation problem(s).