A new method for predicting the heats of combustion of polynitro arene, polynitro heteroarene, acyclic and cyclic nitramine, nitrate ester and nitroaliphatic compounds

A new method is presented for estimating the gross and net heats of combustion of important classes of energetic compounds including polynitro arene, polynitro heteroarene, acyclic and cyclic nitramine, nitrate ester and nitroaliphatic compounds. Elemental compositions as well as the presence of some specific polar groups and molecular fragments are important parameters in the new model. The novel method can be easily used for any complex organic compounds with at least one nitro, nitramine or nitrate functional groups by which the predictions of their heats of combustion by the available methods are inaccurate or difficult. The predicted results show that this method gives reliable predictions of heats of combustion with respect to group additivity method and computed values based on atom-type electrotopological state indices for several energetic compounds where the models can be applied.     

Analysis of the essential oils of two Thymus species from Iran

The essential oils obtained from the aerial parts of Thymus daenensis subsp. daenensis and Thymus kotschyanus were analyzed by using GC and GC/MS. Twenty six compounds representing 99.7% of T. daenensis subsp. daenensis oil were identified. The main ones were thymol (74.7%), p-cymene (6.5%), β-caryophyllene (3.8%) and methyl carvacrol (3.6%). Thirty one components accounting for 98.7% of T. kotschyanus oil were identified. The major constituents were thymol (38.6%), carvacrol (33.9%), γ-terpinene (8.2%) and p-cymene (7.3%). Both oils were found to be rich in monoterpene phenols, especially thymol and carvacrol.     

Chromatographic Fingerprinting with Multivariate Data Analysis for Detection and Quantification of Apricot Kernel in Almond Powder

Adulteration of almond powder samples with apricot kernel was solved by gas chromatographic fatty acid fingerprinting combined with multivariate data analysis methods (principal component analysis (PCA), PCA-linear discriminant analysis (PCA-LDA), partial least squares (PLS), and LS support vector machine (LS-SVM). Different almond and apricot kernel samples were mixed at concentrations ranging from 10 to 90% w/w. PCA and PCA-LDA methods were applied for the classification of almonds, apricot kernels, and mixtures. PLS and LS-SVM were used for the quantification of adulteration ratios of almond. Models were developed using a training data set and evaluated using a validation data set. The root mean square error of prediction (RMSEP) and coefficient of determination (R ²) of validation data set obtained for PLS and LS-SVM were 5.01, 0.964 and 2.29, 0.995, respectively. The results showed that the methods can be applied as an effective and feasible method for testing almond adulteration.     

Photonics and lasing in liquid crystal materials

Owing to fundamental reasons of symmetry, liquid crystals are soft materials. This softness allows long length-scales, large susceptibilities and the existence of modulated phases, which respond readily to external fields. Liquid crystals with such phases are tunable, self-assembled, photonic band gap materials; they offer exciting opportunities both in basic science and in technology. Since the density of photon states is suppressed in the stop band and is enhanced at the band edges, these materials may be used as switchable filters or as mirrorless lasers. Disordered periodic liquid crystal structures can show random lasing. We highlight recent advances in this rapidly growing area, and discuss future prospects in emerging liquid crystal materials. Liquid crystal elastomers and orientationally ordered nanoparticle assemblies are of particular interest.     

A new dynamic model for accurate prediction of asphaltene precipitation process in petroleum reservoirs

A novel dynamic model for accurate evaluation of the effects of different process variables on the asphaltene precipitation process in petroleum reservoirs is presented. Different deposition mechanisms such as surface deposition, pore throat plugging, deposits entrainment, and asphaltene adsorption are properly incorporated in the proposed multiphase model. The variations of porosity, permeability, and pressure profiles are in good agreement with the available experimental data. The presented approach can have potential application for evaluation of the asphaltene precipitation process in petroleum reservoirs at different operating conditions.