Transformer oils as a potential source of environmental exposure to polychlorinated biphenyls (PCBs): an assessment in three central provinces of Iran

Environmental Science and Pollution Research - Polychlorinated biphenyl (PCB) contamination of oils from all transformers of the national electrical grid in Tehran, Qom, and Alborz, three central...     

Room temperature synthesis of 2H-1,4-benzoxazine derivatives using a recoverable ionic liquid medium

2H-1,4-Benzoxazines are major heterocyclic compounds with interesting biological and synthetic applications. Therefore, it would be very interesting to develop new efficient methods for their synthesis. Here, we synthesized 2H-1,4-benzoxazines in one pot using K₂CO₃/H₂O in the ionic liquid of choice, [omim][BF₄]. After reactions, products are extracted from [omim][BF₄] by Et₂O and the ionic liquid is recovered and successfully reused over several recycles. Results show that high yields of 3-aryl-2H-1,4-benzoxazine derivatives are obtained chemoselectively at room temperature from their corresponding o-aminophenols and phenacyl bromides. To our knowledge, our method represents the most efficient and straightforward route for the synthesis of 3-aryl-2H-1,4-benzoxazine derivatives in short times and under environmentally benign conditions.     

A detailed kinetic investigation on the effects of hydrogen enrichment on the performance of gas-fueled SI engine

This study investigates the effects of hydrogen enrichment on formation of pollutants and greenhouse gases in gas-fueled spark ignition engines. To this end, a previously validated detailed mechanism is embedded with a comprehensive one-dimensional engine model and the results are verified with experimental observations at different compression ratios and engine loads. The simulations are then performed for different mixtures of hydrogen and natural gas. The results indicate that adding hydrogen increases the cylinder peak pressure at different loads and compression ratios, despite the fact that reduces the amount of carbon monoxide, carbon dioxide, and methane in all the conditions.     

Parametric study along with selection of optimal solutions in dry wire cut machining of cemented tungsten carbide (WC-Co)

This work deals with parametric study of dry wire EDM (WEDM) process of cemented tungsten carbide. Experiments have been conducted using air as dielectric medium to investigate effects of pulse on time, pulse off time, gap set voltage, discharge current and wire tension on cutting velocity (CV) surface roughness (SR) and oversize (OS). Firstly, a series of exploratory experiments were carried out to identify appropriate gas and its pressure. Afterward, preliminary experiments were conducted to investigate effects of process parameters on dry WEDM characteristics and find appropriate ranges for each factor. Then a central composite rotatable method was employed to design experiments based on response surface methodology (RSM). Empirical models were developed to create relationships between process factors and responses by considering to analysis of variances (ANOVA). To increase the predictability of the process, intelligent models have been developed based on back-propagation neural network (BPNN) and accuracy of these models was compared with mathematical models based on root mean square error (RMSE) and prediction error percent (PEP). In order to select optimal solutions in the cases of single-objective and multi-objectives optimization problems, optimization includes two main approaches. First approach was based on mathematical model and desirability function. Also second approach was designed based on neural network and particle swarm optimization. These approaches were applied in both cases of single-objective and multi-objectives optimization problems and their results were compared with together. Results indicated that selection of air at inlet pressure of 1.5 bar is really appropriate for conducting experiments of next stages. Also, the BPNN creates more accurate prediction rather than mathematical model. Moreover, the BPNN-PSO approach was more efficient in optimization of process rather than mathematical model-desirability function in respect with validation tests.