ABSTRACT In the present work, the use of microextraction methods for the separation and pre-concentration of narcotic drugs in urine and vitreous samples is presented. These simple and eco-friendly methods are used to measure tramadol and methadone, which are used to relieve pain and treat addiction to other drugs. Urine and vitreous samples from 54 corpses referenced to legal medicine were analyzed by high performance liquid chromatography. Extraction of tramadol and methadone was performed separately using 200 μl chloroform, 700 μl methanol at pH 10. Under the optimum conditions, the detection limit linear range were obtained 4.5 µg L−1 and 1.2 µg L−1, 4.5-1000 µg L−1 and 1-1000 µg L−1 for determination of tramadol and methadone, respectively. According to the results, for accurate interpretation of the methadone and tramadol concentration in the bodies, its measurement in vitreous fluid is very useful and practical.

In this study, a highly sensitive and reliable microextraction method, known as in tube ultrasonic and air assisted liquid-liquid microextraction (IT-UAA-LLME), was developed for the preconcentration of some phthalate esters, such as dimethyl phthalate, diethyl phthalate (DEP), di-butyl-phthalate (DBP), bis(2-ethylhexyl) phthalate (BEHP), butyl benzyl phthalate (BBP), and di n-octyl-phthalate (DNOP), prior to their determination using gas chromatography-mass spectrometry (GC-MS). In this technique, the extraction solvent was dispersed into the aqueous sample solution using an ultrasonic bath. The effects of solvent type, aeration time and salt concentration were investigated. After extraction, an organic solvent was injected into the GC-MS instrument for quantification. Under optimum conditions, the enrichment factors ranged from 100 to 330. The calibration curves showed good linearity (r2 > 0.99) and limit of detections were obtained in the range of 0.1-2.1 ng mL-1 in the working concentration ranges. The method was successfully applied for determination of six phthalate esters in real samples with complex matrices with relative standard deviation less than 8%, recovery 88-112% and thus, satisfactory results were obtained.

For the first time, artificial neural network (ANN) and genetic algorithm (GA) have been employed to modeling and optimization of in syringe magnet stirring assisted dispersive liquid-liquid microextraction (IS-MSA-DLLME) method for extraction of cadmium from food samples and determined by flame atomic absorption spectrometry. Based on one factor at a time optimization method, the different input variables for modeling were chosen as pH of the solution, extraction volume, stirring rate and extraction time. The ANN techniques fitted a model for extraction of cadmium with 8, 0.9988 and 6.4x10-4 neurons, correlation coefficient and mean standard error (MSE), respectively. By using the GA technique, the optimal conditions were achieved at pH 7, extraction volume at 250 μL, stirring rate of 500 rpm and extraction time of 10 min. Under the optimum conditions, the calibration graph was linear over the range of 0.05 - 1.00 μg L-1 and the limits of detection (LOD) were as small as 0.015 μg mL-1. The relative standard deviation was ±2.11% (n = 7) and the enrichment factor was 280. The developed method was successfully applied to the extraction and determination of cadmium in food samples.

A new simple and rapid dispersive liquid-liquid microextraction has been applied to preconcentration trace levels of bismuth as a prior step to its determination by spectrophotometric detection. In the proposed method, dithizone was used as a chelating agent, and tetrachloride carbon and ethanol are selected as extraction and dispersive solvent. The optimization strategy is carried out by using two level full factorial designs. Results of the two level full factorial design (2(4)) based on an analysis of variance demonstrated that the pH, concentration of dithizone, amount of dispersive and extraction solvents were statistically significant. Optimal condition for four variables: pH, concentration of dithizone, amount of dispersive and extraction solvents are obtained by using Box-Behnken design. Under the optimum conditions, the calibration graphs were linear in the range of 5-300 ng mL-1 with detection limit of 1.6 ng mL-1 (3δB/m) and the enrichment factor of this method for bismuth reached at 150. The relative standard deviation (R.S.D.) is 2.3% (n = 5, c = 50 ng mL-1). The method is successfully applied to the determination of trace amount of bismuth in water samples.