Background: Methadone abuse and dependence are a growing concern in some countries. The present study developed and validated a rapid, simple, easy, and sensitive method for analyzing methadone in urine specimens. This approach was intended for use in clinical and forensic toxicology and drug screening laboratories. Methods: We determined methadone in urine samples by Gas Chromatography / Mass Spectrometry (GC / MS). Besides, we used Ultrasound-Assisted Liquid-Liquid Extraction (UALLE) method for the extraction and preconcentration of methadone before analysis. Results: The detection limit was 2. 1 ng/mL and the limit of quantification equaled 7 ng/mL. The methadone calibration curve was linear and ranged from 7 to 10000 ng/mL, and the correlation coefficient was calculated as 0. 9984. The tested method was accurate and precise. Recovery fell in the range of 81. 3% to 97. 4% and the enrichment factor was measured as 8. 7. The method was successfully used for determining methadone in real clinical and postmortem urine samples. Conclusion: The presented method was a rapid, easy, simple, and sensitive procedure; thus, it could be applied in clinical and forensic toxicology laboratories as a routine approach for analyzing methadone.

The main objective of this paper is to examine the effect of nanomaterials on mass transfer coefficient in bubble type absorption of carbon dioxide by experiment. The absorption process is carried out in a bubble column and in room temperature. Mass transfer coefficient, saturated concentration of CO2, and gas holdup are determined in this system. The kinds of nanomaterials, the concentrations of each one and the gas superficial velocity are considered as the key parameters. The results show that the mass fraction of nanomaterials has an optimum value to the mass transfer coefficient and saturated concentration of CO2.0.07% CNT nanofluid increases the mass transfer coefficient up to 78%. The superficial velocity of CO2 enhances mass transfer coefficient and gas holdup within the experimental range, whilst it has no effect on saturated concentration of CO2. In addition, nanomaterials in solution increase the gas holdup.

A steady state model was developed for a hollow fiber membrane contactor to describe gas absorption performance. Countercurrent absorption of pure CO2, pure SO2, CO2-N2 and SO2-N2 mixtures in diethanolamine solution (DEA), and water as the absorbent were investigated. The model is able to predict gas phase concentration and the velocity profile in the axial direction inside the shell, as well as the liquid concentration profile in both the axial and radial direction inside the fibers. A numerical scheme was proposed to solve the simultaneous mathematical expressions that were obtained based on concepts of mass transfer, and the results were validated with experimental data found in the literature. Axial variations of gas velocity, gas concentration and a two dimensional concentration profile of the liquid phase were compared for three absorbing systems, including low (CO2-water), moderate (CO2-DEA) and high (SO2-water) absorption rates. The effect of chemical reaction on the importance of external resistance was also studied using this model. It was found that the shell side and membrane resistances are negligible in comparison with the liquid resistance in low absorption rates, for example in a CO2-water system, however they have significant effects when the chemical reaction is fast and the absorption rate is high, such as SO2-water system.

Equilibrium ratios for the mixture of different components are very important for many engineering application processes. Different numerical methods were explored and applied to ensure efficient estimation of gas-liquid equilibrium ratio. In this paper, the Artificial Neural Network (ANN) approach along with data of experiments performed on 25 gas condensate reservoirs has been utilized to obtain a relationship of gas-liquid equilibrium ratios in gas condensate reservoirs. The relationship between the gas-liquid equilibrium ratio and parameters of components of a mixture (critical temperature, critical pressure, and acentric factor) has been derived. Finally, the results of ANN have been compared to the proposed correlations in the literature and results of the equation of state. This investigation demonstrated that the result of ANN is more precise than the equation of state and existing empirical correlations. Whereas comparison between experimental data of 3 gas condensate samples by ANN, EOS, and existing empirical correlation show that the average absolute error for ANN was between 7. 82 to 13. 74% and for others was between 29. 99 to 94. 99%.