Density functional theory study of the {\alpha} --> {\omega} martensitic transformation in titanium induced by hydrostatic pressure

The martensitic {\alpha} --> {\omega} transition was investigated in Ti under hydrostatic pressure. The calculations were carried out using the density functional theory (DFT) framework in combination with the Birch-Murnaghan equation of state. The calculated ground-state properties of {\alpha} and {\omega} phases of Ti, their bulk moduli and pressure derivatives are in agreement with the previous experimental data. The lattice constants of {\alpha} and {\omega}-phase at 0 K were modeled as a function of pressure from 0 to 74 GPa and 0 to 119 GPa, respectively. It is shown that the lattice constants vary in a nonlinear manner upon compression. The calculated lattice parameters were used to describe the {\alpha} --> {\omega} transition and show that the phase transition can be obtained at 0 GPa and 0 K.Comment: 6 pages, 5 figure

Modeling the Drying Kinetics of Green Bell Pepper in a Heat Pump Assisted Fluidized Bed Dryer

In this research, green bell pepper was dried in a pilot plant fluidized bed dryer equipped with a heat pump humidifier using three temperatures of 40, 50 and 60C and two airflow velocities of 2 and 3m/s in constant air moisture. Three modeling methods including nonlinear regression technique, Fuzzy Logic and Artificial Neural Networks were applied to investigate drying kinetics for the sample. Among the mathematical models, Midilli model with R=0.9998 and root mean square error (RMSE)=0.00451 showed the best fit with experimental data. Feed-Forward-Back-Propagation network with Levenberg-Marquardt training algorithm, hyperbolic tangent sigmoid transfer function, training cycle of 1,000 epoch and 2-5-1 topology, deserving R=0.99828 and mean square error (MSE)=5.5E-05, was determined as the best neural model. Overall, Neural Networks method was much more precise than two other methods in prediction of drying kinetics and control of drying parameters for green bell pepper. Practical Applications: This article deals with different modeling approaches and their effectiveness and accuracy for predicting changes in the moisture ratio of green bell pepper enduring fluidized bed drying, which is one of the most concerning issues in food factories involved in drying fruits and vegetables. This research indicates that although efficiency of mathematical modeling, Fuzzy Logic controls and Artificial Neural Networks (ANNs) were all acceptable, the modern prediction methods of Fuzzy Logic and especially ANNs were more productive and precise. Besides, this report compares our findings with previous ones carried out with the view of predicting moisture quotients of other food crops during miscellaneous drying procedures. © 2016 Wiley Periodicals, Inc

Crocin loaded nano-emulsions: Factors affecting emulsion properties in spontaneous emulsification

Spontaneous emulsification may be used for encapsulating bioactive compounds in food and pharmaceutical industry. It has several advantages over high energy and other low energy methods including, protecting sensitive compounds against severe conditions of high energy method and its ability to minimize surfactant, removal of cosurfactant and thermal stability compared with other low energy methods. In this study, we examined possibility of encapsulating highly soluble crocin in W/O micro-emulsions using spontaneous method which further could be used for making double emulsions. Nonionic surfactants of Span 80 and polyglycerol polyricinoleate (PGPR) were used for making micro-emulsions that showed the high potential of PGPR for spontaneous method. Surfactant to water ratio (SWR) was evaluated to find the highest amount of aqueous phase which can be dispersed in organic phase. Droplet size decreased by increasing SWR toward the SWR = 100 which had the smallest droplet size and then increased at higher levels of surfactant. By increasing SWR, shear viscosity increased which showed the high effect of PGPR on rheological properties. This study shows in addition to W/O micro-emulsions, spontaneous method could be used for preparing stable O/W micro-emulsions. © 2015 Elsevier B.V