Viscosities (η) and densities (ρ) of atenolol and propranolol hydrochloride in water and in concentrations (0.05 M) and (0.1 M) aqueous solution of threonine have been used to reform different important thermodynamic parameters like apparent molal volumes fv partial molal volumes at infinite dilution fvo , transfer volume fvo (tr), the slop Sv , Gibbs free energy of activation for viscous flow of solution ΔG*1,2 and the B-coefficient have been calculated using Jones-Dole equation. These thermodynamic parameters have been predicted in terms of solute-solute and solute-solvent interaction.

mixtures of cyclohexane + n-decane and cyclohexane + 1-pentanol have been measured at 298.15, 308.15, 318.15, and 328.15 K over the whole mole fraction range. From these results, excess molar volumes, VE , have been calculated and fitted to the Flory equations. The VE values are negative and positive over the whole mole fraction range and at all temperatures. The excess refractive indices nE and excess viscosities ?E have been calculated from experimental refractive indices and viscosity measurements at different temperature and fitted to the mixing rules equations and Heric – Coursey equation respectively to predict theoretical refractive indices, we found good agreement between them for binary mixtures in this study. The variation of th

The densities and visconsities of solutions of poly(vinyl alcohol)(PVA) molccuar weight (14)kg.mol-1in water up to 0.035%mol.kg-1

Densities ρ and viscosities η for several concentrations of amino acids (Serine, Cysteine and Threonine) at different temperatures (298.15, 303.15 and 308.15K) have been measured. On the basis of these data, the apparent molal volumes v , partial molal volumes at infinite dilution v , slope Sv , Gibbs free energy of activation for viscous flow of solution ∆G1,2 and Jones – Dole Bcoefficients were calculated the nature of solute-solvent and solute-solute interactions have been discussed in terms of the values of v , v , Sv and B-coefficents

Iraqi calcium bentonite was activated via acidification to study its structural and electrical properties. The elemental analysis of treated bentonite was determined by using X-ray fluorescence while the unit crystal structure was studied through X-ray diffraction showing disappearance of some fundamental reflections due to the treatment processes. The surface morphology, on the other hand, was studied thoroughly by Scanning Electron microscopy SEM and Atomic Force Microscope AFM showing some fragments of montmorillonite sheets. Furthermore, the electrical properties of bentonite were studied including: The dielectric permittivity, conductivity, tangent loss factor, and impedance with range of frequency (0.1-1000 KHz) at different temperatu

The electric quadrupole moments for some scandium isotopes (41, 43, 44, 45, 46, 47Sc) have been calculated using the shell model in the proton-neutron formalism. Excitations out of major shell model space were taken into account through a microscopic theory which is called core polarization effectives. The set of effective charges adopted in the theoretical calculations emerging about the core polarization effect. NushellX@MSU code was used to calculate one body density matrix (OBDM). The simple harmonic oscillator potential has been used to generate the single particle matrix elements. Our theoretical calculations for the quadrupole moments used the two types of effective interactions to obtain the best interaction compared with the exp

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and