A model of nonlinear electrodynamics

A new model of nonlinear electrodynamics with two parameters is investigated. We also consider a model with one dimensional parameter. It was shown that the electric field of a point-like charge is not singular at the origin and there is the finiteness of the static electric energy of point-like charged particle. We obtain the canonical and symmetrical Belinfante energy–momentum tensors and dilatation currents. It is demonstrated that the dilatation symmetry and dual symmetry are broken in the models suggested. We have calculated the static electric energy of point-like particles.     

Covalent Functionalization of Pristine and Ga-Doped Boron Phosphide Nanotubes with Imidazole

Abstract

Density functional theory (DFT) calculations at the B3LYP/6–31G* level were performed to investigate covalent functionalization of imidazole on pristine (in gas and H₂O phases) and Ga-doped BPNT models in terms of energetic, geometric, and electronic properties. The results show that imidazole, as a functional group, prefers to be adsorbed via its nitrogen atom on the pristine, Ga_B, and Ga_P nanotube models. The adsorption energy of imidazole on the (6,0) zigzag BPNT in gas and solvent phases is ?0.76 and ?1.11 eV, respectively, and about 0.38 and 0.43 electron are transferred from the imidazole to nanotube in the phases. The presence of a polar solvent increases the electron donor of imidazole molecule. The results show that Ga doping can significantly enhance the adsorption energy of imidazole on the nanotube models to about 95%.

Moreover, the imidazole adsorption on the pristine and Ga-doped BPNT models has not significant changes in the energy gap of the nanotube models and it is slightly changed after covalent functionalization process. This study may provide new insight to the development of functionalized boron phosphide nanotubes for generation of the new hybrid compounds especially in drug delivery systems for virtual applications.     

Kinetics of Alkaline Hydrolysis of Quaternary Phosphonium Salts. The Influence of Protic and Aprotic Solvents on the Hydrolysis of Alkyl Phenylphosphonium Salts

Abstract

Third order rate constants have been determined for the alkaline hydrolysis of four series of alkylphenylphosphonium salts and alkylphenylbenzylphosphonium salts at various temperatures in 50%–70% ^v/_v aqueous tetrahydrofuran and 70% ^v/_v aqueous methanol. Thermodynamic activation parameters have been calculated for the reactions of each substrate and the effects of varying the ratio of alkyl to phenyl groups have been compared, as well as the effects of changes in the nature of the alkyl group. Solvation, as revealed by trends in entropy of activation, plays a largely counter-balancing role with respect to enthalpy and energy of activation. The role of the isokinetic effect is discussed. In aqueous tetrahydrofuran, solvation effects on the hydrolyses of phosphonium salts change as the mole fraction of water changes, and for aqueous methanol the trends in the thermodynamic activation parameters actually reverse.     

Phosphorus and Energy Recovery from Manure and Digestion Residues

Abstract

Human and animal excrements, in particular manure, stand for a significant and undisputable source of plant nutrients and renewable energy. In Europe, only 36% of P-inputs to soils originate from primary resources (rock phosphate) whereas 63% come from animal and human excretions applied to cropland as manure, digestion residues and sewage sludge. Simultaneously these waste flows represent a potential hazard to human health and aquatic bodies because of pathogens and eutrophication. Management of these waste flows is far from being sustainable, in part due to the lack of efficient processing technologies. A cooperative InnoEnergy—EIT financed KIC Knowledge and Innovation Community—research project pursues development and demonstration of highly efficient technologies to overcome the constraints and to yield renewable phosphate fertilizers and energy from waste flows that may have a combined technical energy potential of 3,600 PJ/year and an annual phosphate recovery potential of 4.5–5.5 million tonnes (as P₂O₅) in Europe.     

Recovery performance and characteristics in shape memory effects of aliphatic polyether urethane

The analysis on the recovery performance and characteristics in shape memory effects is helpful for the optimal design and engineering applications of shape memory polymers and their composites. To investigate the relationships among recovery performance, material parameters, and loading conditions, by taking aliphatic polyether urethane as an example, the researchers simulate the shape memory behaviors numerically using a three‐dimensional viscoelastic model. The material parameters for this model are taken from stress relaxation tests, rather than dynamic mechanical analysis tests. Both the unconstrained and the constrained recovery behaviors during strain‐controlled shape memory processes are analyzed. The results reveal that the unconstrained recovery occurs at the same temperature regardless of the applied strain values. Another interesting result is that the shape recovery temperature in unconstrained recovery situations increases and the maximum recovery stress under constrained recovery conditions decreases with the increase of heating rates. Copyright © 2013 John Wiley & Sons, Ltd.     

QM/MM Studies on Cyclodextrin-Alcohol Interaction

The main objective of this study is to provide an insight into the interactions involved during adsorption of the alcohols on β-CD composite nanostructured membrane. Interactions between β-cyclodextrin (β-CD) and alcohols (methanol, ethanol and butanol) are studied using the QM/MM method. Magnitude of interaction energies show that the alcohols are adsorbed on the membrane. In addition, the thermochemical analysis suggests that the formation of these host-guest complexes is enthalpy driven.     

Prediction of High Performance Fibers Strength Using Back Propagation Neural Network

Nowadays, quantification of the effects of basic parameters such as precursor, temperature oxidation, residence time, low temperature carbonization (LTC) and high temperature carbonization (HTC) on production process polyacrylonitrile based carbon fibers is not completely understood. In this way, there is not a completely theoretical model that accomplishes to quantitatively describe production process carbon fibers very accurately which needs to be used by engineers in design, simulation and operation of that process. This paper presents the development of a back propagation neural network model for the prediction of carbon fibers produced from PAN fibers. The model is based on experimental data. The precursors, temperature oxidation, residence time, LTC and HTC have been considered as the input parameters and the strength as output parameter to develop the model. The developed model is then compared with experimental results and it is found that the results obtained from the neural network model are accurate in predicting the strength of carbon fibers.