Spiro[4H‐pyran‐3,3′‐oxindoles] Derived from 1,2,3,4‐Tetrahydroquinoline

Three‐component reactions of 5,6‐dihydro‐4H‐pyrrolo[3,2,1‐ij]quinoline‐1,2‐dione with malononitrile, or ethyl cyanoacetate, and cyclic six‐membered or a five‐membered 1,3‐diketone, produce spiro[4H‐pyran‐3,3′‐oxindoles].     

A novel method to estimate derailment probability due to track geometric irregularities using reliability techniques and advanced simulation methods

Track irregularities have a dramatic impact on the response and vibration of a railway vehicle and on the interaction between wheel and rail. The random nature of the track structure and constituent materials and the effects of other factors such as maintenance conditions and transit traffic give rise to the random nature of track irregularities. This research provides a method to estimate the derailment probability of a railway vehicle where track irregularities are assumed to be random, and the interaction of the track and the moving train is considered using advanced dynamic analysis. For this purpose, the limit state function of derailment was estimated using the response surface method and advanced simulation. The probability of derailment was then estimated using a Level 3 reliability method.     

Reaction of perfluoroalkyl grignard reagents with phosphorus trihalides: a new route to perfluoroalkyl-phosphonous and -phosphonic acids

The reaction of perfluoroalkyl Grignard reagents with phosphorus(III) halides was explored. In the process a new convenient, one-pot, high yield method for the synthesis of (perfluoroalkyl)phosphonic acids has been developed. Perfluoroalkyl Grignard reagents react with phosphorus trichloride or phosphorus tribromide to form (perfluoroalkyl)phosphonous dihalides. Hydrolysis gives the corresponding (perfluoroalkyl)phosphonous acids. Oxidation of the phosphonous acids with H(2)O(2) produces (perfluoroalkyl)phosphonic acids in 60-78% overall yields, based on the corresponding perfluoroalkyl iodide. The X-ray crystal structures of the toluidinium salts, [MeC(6)H(4)NH(3)](2)[C(2)F(5)PO(3)] and [MeC(6)H(4)NH(3)][C(8)F(17)P(O)(2)OH], are reported.     

Conductometric study of complexation reaction between 15-crown-5 and Cr3+, Mn2+ and Zn2+ metal cations in pure and binary mixed organic solvents

The stability constants (K_f) for the complexation reactions of Cr³⁺, Mn²⁺ and Zn²⁺ metal cations with macrocyclic ligand, 15-crown-5 (15C5), in acetonitrile (AN), ethanol (EtOH) and also in their binary solutions (AN–EtOH) were determined at different temperatures, using conductometric method. 15C5 forms 1:1 complexes with Cr³⁺, Mn²⁺ and Zn²⁺ cations in solutions. A non-linear behaviour was observed for changes of logK_f of the metal ion complexes versus the composition of the mixed solvent. The order of stability of the metal–ion complexes in pure AN and in a binary solution of AN–EtOH (mol% AN?=?52) at 25?°C was found to be: (15C5Zn)²⁺?>?(15C5·Mn)²⁺?>?(15C5·Cr)³⁺, but in the case of pure EtOH at the same temperature, it changes to: (15C5·Zn)²⁺?>?(15C5·Cr)³⁺?>?(15C5·Mn)²⁺. The results also show that the stability sequence of the complexes in the other binary solutions of AN–EtOH (mol% AN?=?26 and mol% AN?=?76) varies in order: (15C5·Cr)³⁺?~?(15C5·Zn)²⁺?>?(15C5·Mn)²⁺. The values of the standard thermodynamic quantities (ΔH_C°, ΔS_C°) for formation of (15C15-Cr³⁺), (15C5-Mn²⁺) and (15C5-Zn²⁺) complexes were obtained from the temperature dependence of the stability constants and the results show that the thermodynamics of complexation reactions is affected by nature and composition of the solvent systems and in most solution systems, the complexes are enthalpy stabilized but entropy destabilized.     

Application of artificial neural networks for the prediction of roll force and roll torque in hot strip rolling process

This paper introduces an artificial neural network (ANN) application to a hot strip mill to improve the model’s prediction ability for rolling force and rolling torque, as a function of various process parameters. To obtain a data basis for training and validation of the neural network, numerous three dimensional finite element simulations were carried out for different sets of process variables. Experimental data were compared with the finite element predictions to verify the model accuracy. The input variables are selected to be rolling speed, percentage of thickness reduction, initial temperature of the strip and friction coefficient in the contact area. A comprehensive analysis of the prediction errors of roll force and roll torque made by the ANN is presented. Model responses analysis is also conducted to enhance the understanding of the behavior of the NN model. The resulted ANN model is feasible for on-line control and rolling schedule optimization, and can be easily extended to cover different aluminum grades and strip sizes in a straight-forward way by generating the corresponding training data from a FE model.     

Buckling of 2D-FG Cylindrical Shells under Combined External Pressure and Axial Compression

This paper presents the stability of two-dimensional functionally graded (2D-FG) cylindrical shells subjected to combined external pressure and axial compression loads, based on classical shell theory. The material properties of functionally graded cylindrical shell are graded in two directional (radial and axial) and determined by the rule of mixture. The Euler's equation is employed to derive the stability equations, which are solved by GDQ method to obtain the critical mechanical buckling loads of the 2D-FG cylindrical shells. The effects of shell geometry, the mechanical properties distribution in radial and axial direction on the critical buckling load are studied and compared with a cylindrical shell made of 1D-FGM. The numerical results reveal that the 2D-FGM has a significant effect on the critical buckling load.     

What is the correct form of BET isotherm for modeling liquid phase adsorption?

In this work subtleties of application of BET isotherm for liquid phase adsorption is presented. It has been shown that direct use of the classical BET equation (which was developed for gas phase adsorption) to liquid phase adsorption leads to ambiguous and erroneous results. Some cases of misuse of BET equation for liquid phase adsorption have been revisited. By close examination of the development of the classical equation, the causes of misunderstandings were elucidated and the suitable form of the BET equation for liquid phase adsorption was developed. As case studies, the classical form of the BET equation along with the correct form of the equation for liquid phase have been applied for modeling liquid phase adsorption of methyl tert-butyl ether (MTBE) on perfluorooctyl alumina, phenol on activated carbon and pentachlorophenol on carbonized bark. It has been shown that direct application of the classical BET isotherm to liquid phase adsorption results in poor and erroneous estimation of the equation parameters. For example, in aqueous phase adsorption of MTBE on perfluorooctyl alumina, the monolayer adsorption capacity of the adsorbent was calculated as 9.7 mg/g instead of 3.3 mg/g or the saturation concentration of MTBE in water was calculated as 1212 mg/L instead of 42000 mg/L.     

Electrically conductive epoxy‐based nanocomposite adhesives loaded with silver‐coated copper and silver‐coated reduced graphene oxide nanoparticles

In this research, a conductive adhesive based on epoxy resin as the polymer matrix and silver‐coated copper powder and silver‐coated reduced graphene oxide as conductive fillers was synthesized. Graphene oxide was synthesized by modified Hummer's method. It was reduced and modified by silver powder. Copper particles were coated with silver using the electroless plating method. Finally, conductive nanocomposite adhesives were prepared using conductive fillers with different weight fractions. The structural properties of fillers were identified by Fourier‐transform infrared (FTIR) and induced coupled plasma (ICP) analysis and the morphology of the samples by scanning electron microscopy (SEM). Finally, conductive properties, lap shear strength, and thermal stability of adhesive were evaluated. The conductive adhesive prepared with optimized properties have 70% weight percentage silver‐coated copper powder and 1% weight percentage silver‐coated reduced graphene oxide. The bulk resistivity of the optimum sample was 1.6 × 10^‐2 Ω.cm, and the lap shear strength was 7.10 MPa. Also, thermogravimetric analysis showed that the weight loss of adhesive decreased from 88.72% to 30.55% during heating, which showed the addition of fillers improves the thermal stability of adhesive.     

Gaussian free field in the background of correlated random clusters,formed by metallic nanoparticles

The effect of metallic nano-particles (MNPs) on the electrostatic potential of a disordered 2D dielectric media is considered. The disorder in the media is assumed to be white-noise Coulomb impurities with normal distribution. To realize the correlations between the MNPs we have used the Ising model with an artificial temperature T that controls the number of MNPs as well as their correlations. In the T → 0 limit, one retrieves the Gaussian free field (GFF), and in the finite temperature the problem is equivalent to a GFF in iso-potential islands. The problem is argued to be equivalent to a scale-invariant random surface with some critical exponents which vary with T and correspondingly are correlation-dependent. Two type of observables have been considered: local and global quantities. We have observed that the MNPs soften the random potential and reduce its statistical fluctuations. This softening is observed in the local as well as the geometrical quantities. The correlation function of the electrostatic and its total variance are observed to be logarithmic just like the GFF, i.e. the roughness exponent remains zero for all temperatures, whereas the proportionality constants scale with T ? T _c . The fractal dimension of iso-potential lines (D _f ), the exponent of the distribution function of the gyration radius (τ _r ), and the loop lengths (τ _l ), and also the exponent of the loop Green function x _l change in terms of T ? T _c in a power-law fashion, with some critical exponents reported in the text. Importantly we have observed that D _f (T) ? D _f (T _c ) ~ 1/√ξ(T), in which ξ(T) is the spin correlation length in the Ising model.