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White tea is valuable for having a high antioxidant content, which is considered to possess numerous beneficial effects on health. This study investigated the application of microwave-assisted extraction (MAE) for the extraction of total phenolic compounds from white tea. The experimental setup included four independent variables: microwave power (ranging from 100 to 300 W), extraction time (ranging from 10 to 40 min), temperature (ranging from 35 to 50 °C), and the ratio of food to solvent (ranging from 0.25 to 0.5 g/10 mL). The responses that were evaluated were IC50 (ppm) and total phenolic content (mg/g). The experimental design consisted of thirty runs conducted within the MAE system. The group method of data handling (GMDH) models were used to predict important efficiency measures (IC50 and total phenol content) in the extraction process. The models were assessed based on their ability to capture the relationships between input conditions and efficiency outputs. Three GMDH variants were compared: baseline GMDH, GMDH optimized with a genetic algorithm (GMDH-GA), and GMDH optimized with a harmony search algorithm (GMDH-HS). While all models achieved high predictive ability on a test set, GMDH-HS emerged as the superior performer. It achieved near-perfect agreement with observations (d-index > 0.998), minimal errors (NRMSE < 0.02), and effectively captured data variance (NSE > 0.99) for both outputs. Correlation diagrams and Taylor diagrams confirmed the superior performance of GMDH-HS in terms of linearity, correlation, and error minimization. This study demonstrates the effectiveness of hybridizing GMDH with a harmony search algorithm for complex modeling tasks, paving the way for improved efficiency and yield optimization in extraction processes. [ABSTRACT FROM AUTHOR]

Organophosphorous (OP) pesticides can cause many human diseases. In this study, the separation and determination of two organophosphorous pesticides (diazinon and methyl-parathion) in biological samples using solid-phase extraction method prior to their measurements by high‐performance liquid chromatography (HPLC) were investigated. Herein, a new functionalized cerium-based metal–organic framework (MOF) bearing oxime moiety, denoted here UiO-66(Ce)-MO, was synthesized through two-synthetic steps from the pristine UiO-66(Ce) and then applied as an efficient porous adsorbent for the extraction of pesticides from biological samples. Various techniques including Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and Brunauer–Emmett–Teller (BET) analysis were used for the description of adsorbent. The optimization of variables was performed by Box–Behnken design combined with response surface methodology. The factors' effects including pH, eluent volume (EV), sample flow rate (SF) and eluent flow rate (EF) were also examined. The optimum conditions for both compounds were pH 5.5, eluent volume 0.6 mL, SF 2 mL min−1, and EF 0.2 mL min−1, leading to 97.1% and 96.0% removal of diazinon and methyl-parathion, respectively. Under the optimum conditions, the maximum adsorption capacity was obtained 454.5 mg g−1 for methyl-parathion and 476.2 mg g−1 for diazinon. The limit of detection (LOD) was found to be 0.04 μgL−1 for diazinon and 0.06 μgL−1 for methyl-parathion. Sensitivity analysis showed that pH plays a significant role on the efficiency of both organic pollutants. Remarkably, the results showed that this adsorbent outperforms the other UiO-66(Ce) samples and is suitable for separation and determination of these organic materials from water and biological real samples (blood plasma and urine). A porous oxime-functionalized Ce-MOF, UiO-66(Ce)-MO, was synthesized and applied for efficient extraction and determination of trace amounts of methyl-parathion and diazinon from water and biological samples. [ABSTRACT FROM AUTHOR]

In this research, a new porphyrin-based porous organic polymer (POP), named here PPOP-UOZ-1 (UOZ stands for the University of Zabol), was synthesized through a solvothermal condensation reaction between 5,10,15,20- t etrakis(4- a mino p henyl) p orphyrin (TAPP, Porph-NH 2) and 2,2'-[ethane-1,2-diylbis(oxy)] d ibenz a ldehyde (Dialdehyde, DA). The chemical structure, morphology, and surface properties of the PPOP-UOZ-1 were assessed using numerous techniques, including TGA, BET, FT- IR, PXRD, and SEM/EDX. The nominal PPOP-UOZ-1 was then used as an adsorbent for selective (better than 92 %) extraction of Pd(II) from aqueous solutions. The adsorption process was optimized by studying the effect of various factors such as pH, the type and volume of eluent, adsorption and desorption time, and the amount of adsorbent. The results exhibited that the maximum adsorption capacity of PPOP-UOZ-1 for Pd(II) was 208.3 mg/g at a pH of 3.0, based on the Langmuir isotherm model (a determination coefficient of 0.9887). The adsorbent showed excellent selectivity for Pd(II) over other coexisting metal ions, with a recovery rate higher than 92 %. Furthermore, the PPOP-UOZ-1 could be reused for at least six adsorption-desorption cycles without substantial loss of efficiency. This proposed adsorbent and approach was further applicable for the efficient extraction of Pd(II) from environmental water samples. [Display omitted] • A novel porphyrin-based porous organic polymer UOZ-PPOP-1, is designed and synthesized. • The adsorption of palladium ions was done in acidic media. • The PPOP contains high coordinating sites towards Pd. • Palladium has been widely used in modern industrial technologies. • Maximum adsorption uptakes were found to be 208.3 mg/g. [ABSTRACT FROM AUTHOR]

With the rapid development of the global dye industry, a series of environmental problems affecting the ecosystem and human health has been perceived. In this work, a porous porphyrin catecholate iron‐based metal–organic framework (MOF) (PorphCat‐Fe) has been prepared and evaluated for the first time for adsorptive removal of azo‐dye methyl orange (MO) pollutant from aqueous media. Consequently, various MO adsorption factors using PorphCat‐Fe MOF were studied and optimized. PorphCat‐Fe was able to remove about 98% of the pollutant from the water within 20 min in the batch experiments with maximum adsorption capacity of 232.5 mg g−1. Under optimum conditions, the limit of detection (LOD) was found to be 0.8 μg L−1. The MOF could maintain its adsorption efficiency toward MO in the real samples. The combination of electrostatic attractions, hydrophobic and π–π interactions, and iron‐organic coordination bonding make PorphCat‐Fe able to show the superior MO adsorption capacity. Remarkably, the removal efficiency of MO was nearly unchanged after five regeneration sequences on PorphCat‐Fe. This effort offers the ability for application of MOFs beyond metal‐carboxylate linkers in wastewater remediation. [ABSTRACT FROM AUTHOR]

In this paper, a novel modeling based on nonparametric logit was developed for optimization of the electromembrane extraction of gold from water samples. A penalty term was considered to adjust the best fit in the proposed nonparametric logit modeling. The input variables including pH of acceptor phase, extraction time (t), volume of sample solution (V), stirring rate (S) and voltage (E) were transferred into normal space. A normalized nonparametric logit model was then calibrated based on the input of normal variable for electromembrane extraction of gold. The obtained results showed that the proposed mathematical expansions based on the nonparametric logit modeling, i.e. nonparametric and normalized nonparametric model had better performance than the original logit model. After designing the models, the input parameters (i.e. pH, t, V, S, and E) were optimized by nonparametric and normalized nonparametric logit model. The optimized conditions were found to be as follows: pH 9.8; S = 421 rpm; V = 10.0 mL; t = 22.7 min and E = 30.0 V for the nonparametric logit model, and pH 9.7, S = 583 rpm, V = 10.8 mL, t = 33.0 min, E = 23.0 V for normalized nonparametric logit model. The predicted and actual extraction efficiencies were obtained by nonparametric model as 91.2 and 93.5%, and by normalized nonparametric model as 94.0 and 94.7%, respectively. These results showed that the error of the normalized nonparametric logit model was less than the nonparametric logit model. Thus, normalized nonparametric logit model can be efficiently used to approximate the optimum conditions for gold extraction. [ABSTRACT FROM AUTHOR]

Ternary NiCuZr layered double hydroxide (LDH)/MIL-101(Fe)-NH2 (MOF), as a tetrametalic porous composite, was synthesized for the first time by an easy solution casting technique and assessed for catalytic photodegradation of methylene blue dye. The new photocatalyst was characterized by different procedures including PXRD, FTIR, SEM/EDS, UV–Vis DRS, and BET measurements. The photocatalyst activity was investigated under numerous conditions such as pH, amount of photocatalyst, and concentration of methylene blue. Under the optimum conditions, the photocatalytic degradation efficiency of the composite was > 98% after 10 min radiation that was greater than that of former solids. Quenching assessments showed that the holes (h+) done a major effect on the degradation of the analyte under LED illumination. [ABSTRACT FROM AUTHOR]

[Display omitted] • Air-plasma pre-treatment as a facile method to set active sites for sedimentation of UiO-66-NH 2 and GQDs. • The GQDs/UiO-66-NH 2 MOF/non-woven polypropylene (NW-PP) membrane. • The membrane can act as both a photocatalytst and an adsorbent for removal of dye. • GQDs increased the photocatalytic performance due to inhibition of electron/hole recombination. The UiO-66-NH 2 and graphene quantum dot suspension were synthesized through hydrothermal and electrochemical methods, respectively. The prepared species were assembled on a non-woven polypropylene substrate (NW-PP). The obtained microstructure and the efficiency of the assembling methods were compared to each other. The results showed that plasma treatmentof NW-PP, as the pre-treating procedure, was the most liable strategy concerning the homogenous distribuation of MOF (mass loading percentage of ~19.5 wt% of UiO-66-NH 2) and improved filtering performance. Next, the photocatalytic performance against methylene blue was increased through addition of graphene quantum dot (GQD) to the NW-PP. The photoluminescence results confirmed that the presence of GQDs effectively inhibited the recombination of photogenerated electron/hole pairs. In addition, the photocatalytic constant rate was increased up to ~three times in the presence of GQDs. Quenching tests proved that the photo-generated O 2 − played a major role in the photodegradation of the dye. [ABSTRACT FROM AUTHOR]

• A new functionalized porous Ce-metal-organic framework is designed and synthesized. • Cu(II)/Sal@UiO-66(Ce) material contains dual-metal sites (Ce and Cu). • A superior MOF-based adsorbent for the removal of methyl orange dye is introduced. • A maximum extraction capacity of 454.5 mg/g is achieved. Herein, a copper(II) Schiff-base complex derived from the condensation of salicylaldehyde (Sal) with amino groups of a cerium-based metal-organic framework of type, UiO-66-NH 2 (Ce), denoted here Cu(II)/Sal@UiO-66(Ce), has been prepared and characterized by EDX, SEM, FT-IR, BET and XRD, as well as thermal gravimetric analysis (TGA) techniques. The nominal nanostructure including dual-metal sites (Ce and Cu) was considered as a novel adsorbent for removing methyl orange (MO, as an organic contaminant) dye from aqueous media. Accordingly, various key experimental factors such as the pH, mass of adsorbent, contact time, and eluent type were tested and optimized. Based on experimental outcomes, the adsorption of MO for Cu(II)/Sal@UiO-66(Ce) reaches a maximum of 98.8 % efficiency at a pH of 6 and a maximum extraction capacity of 454.5 mg/g. Also, the limit of detection (LOD) and relative standard deviation (RSD%) were 0.63 μg/L and 2.4 %, respectively, under the optimum condition. Reusability, short adsorption time, and low-cost cerium-based MOF are the other advantages of the corresponding adsorbent. In addition, the porous adsorbent was applicable for the MO adsorption from environmental water samples. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract A 3D urea-based porous organic polymer (Urea-POP) was prepared via the reaction of tetrakis (4-aminophenyl)methane and 1,4-Phenylene diisocyanate. The polymer was subsequently reacted with 2D layered nanosheets of graphene oxide (GO) to prepare Urea-POP/GO as a novel and highly efficient sorbent for pre-concentration and extraction of serum albumin samples, prior to spectrophotometric determination. The hybrid material combines advantages of both POP and GO such as hydrophilicity, high dispersion stability, porosity, and having a large number of nitrogen- and oxygen-containing functional groups. Parameters which influence the extraction efficiency such as the amount of the adsorbent, pH of sample solution, ionic strength, adsorption and desorption time were investigated and optimized. For the method, detection limit of 0.068 mg L−1 and determination coefficient (R2) of 0.9991 were obtained. The intra- and inter-day was calculated with five replicates in the same day and seven consecutive days, respectively. Intra-day and inter-day precisions were 1.7% and 5.9%, respectively. The maximum sorption capacity was 357.1 mg g−1, which is higher than the other reported sorbents. The proposed method was demonstrated to be sensitive enough for determination of serum albumin from bio-samples. Graphical Abstract Unlabelled Image Highlights • A hybrid sorbet, graphene oxide/three-dimensional urea-based porous organic polymer, was prepared. • The hybrid material combines advantages of both POP and GO. • The hybrid material was successfully used as a sorbent for pre-concentration and extraction of serum albumin samples. • The maximum sorption capacity was obtained 357.1 mg g−1. [ABSTRACT FROM AUTHOR]

In this research, an efficient, fast, low-cost and easy-to-use liquid-phase microextraction method was established to measure quercetin in onion and tomato before analysis by HPLC instrument. Herein, a rotatable central composite design-response surface methodology and artificial neural network were applied to model, optimize and predict the affecting factors on the microextraction procedure. Here, a minimal level of extractant was applied in the absence of a disperser. The cloudy state was formed by repeatedly suctioning and injecting the mixture of the aqueous solution and extractant with a glass syringe. Due to this procedure, a turbid solution composed of the very fine droplets of extractant dispersed in the aqueous solution was created, the contact surface was significantly enlarged and the quercetin was promptly extracted. The optimum values for the proposed method included 284 μL of 1-undecanol as the organic extractive solvent, pH of sample 3.3, the number of air injected nine times and speed and duration of centrifugation 4,000 rpm and 5 min. The linear range and detection of limit were achieved at 20–4,000 and 6 μg L −1 , respectively. RSD% was obtained ˂4.93% (n  = 5). This model was applied to monitor quercetin in tomato and onion samples. [ABSTRACT FROM AUTHOR]

In this work, an electromembrane extraction (EME) technique was used for the extraction and determination of gold from water samples prior to UV-Vis spectrophotometry. An artificial neural network (ANN) combined with imperialist competitive algorithm (ICA) has been applied to optimize the EME. The effective parameters including pH of acceptor phase, extraction time (t), volume of sample solution (V), stirring rate (S), and voltage (E) were chosen as input variables and the extraction recovery of gold was considered as output variable. The mean of squared error (i.e., 0.0009) and determination coefficient (i.e., 0.9821) were applied to estimate the performance of the ANN model. The limit of detection was 4.5 µg L−1(S/N = 3) on the optimized variables. The intra- and interday precisions (%) were found to be 6.7% and 2.6%, respectively. This technique was then applied for analysis of gold from environment water samples. [ABSTRACT FROM PUBLISHER]

• A PTFE-based support was post-synthetically decorated by UiO-66-NH 2 and tannins. • The new bio-based multifunctional membrane used for extraction of Hg(II). • The post-modified PTFE showed higher total mercury uptake (380.6 mg/g). • Polyphenols (tannins) used in this effort were extracted from the green tea. In this study, we have designed and synthesized a porous membrane by functionalizing the polytetrafluoroethylene (PTEF) support with natural biomass polyphenols (tannins) grafted on amino-functionalized UiO-66 metal–organic framework to give a robust, environmentally friendly polyphenol/metal–organic framework/PTFE membrane, namely PPG-UiO-66@PTFE. Then, the nominal solid was used for the efficient extraction of mercury ions from water samples before ICP-Mass measurements. The effects of some parameters such as pH, type, and volume of eluent, eluent, sample flow rate, and co-existent ions were explored and optimized. Under optimum conditions, the limit of detection was obtained at 1.5 ng/L. The results exhibited that the presence of the co-existing ions does not affect the experimental results. The PPG-UiO-66@PTFE demonstrated superior performance compared to individual materials. This bio-based porous membrane had benefits such as a wide linear range, selectivity, renewability, and real applications in laboratory settings. [ABSTRACT FROM AUTHOR]

BACKGROUND A novel technique using maghemite nanoparticle-decorated hollow fibers to assist electromembrane extraction is proposed. Electromembrane extraction combined with dispersive liquid-liquid microextraction ( EME-DLLME) was applied for the extraction of thymol from Carum copticum, followed by gas chromatography with flame ionization detection ( GC-FID). RESULTS The use of maghemite nanoparticle-decorated hollow fibers was found to improve the extraction efficiency of thymol significantly. Important operational parameters, including pH of acceptor phase, extraction time, voltage and temperature, were investigated and optimized. At the optimal conditions, linearity in the range 4-1800 µg L−1 with a determination coefficient of 0.9996 was obtained. The limit of detection was 0.11 µg L−1 (S/N = 3) and the pre-concentration factor was 200. The intra- and inter-day precision was 5.9 and 2.2% respectively. The intra- and inter-day accuracy was higher than 93.6%. CONCLUSION The results indicated that EME-DLLME/ GC-FID is a useful technique for the extraction and determination of thymol in C copticum. © 2016 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Cadmium (Cd) is a toxic element that can damage human organs. Determination of Cd in vegetables is often difficult because of low concentration and matrix effects. A simple, fast, flotation-assisted homogenous liquid–liquid microextraction (FA-HLLME) was developed for determination of Cd in vegetables prior to flame atomic absorption spectrometry (FAAS), in which 1-(2-pyridylazo)-2-naphthol (PAN) was used as a complexing agent. The process was carried out based on fast extraction of Cd from an acetic acid sample solution in which cyclohexane was the extracting solvent. Effects of pH, type and volume of extraction and homogeneous solvents, concentration of PAN, extraction time, and ionic strength on the extraction method were optimized. Under optimum conditions, the limit of detection and preconcentration factor were 0.6 µg·L−1and 38, respectively. The relative standard deviation was less than 3.1%. Extraction recovery was 94.3%–100.9%. [ABSTRACT FROM PUBLISHER]

In this research, a novel magnetic zirconium-based metal-organic framework (Fe3O4@SiO2@MIP-202, MMOF), was fabricated, fully characterized, and applied for the batch-mode solid phase extraction of trace amounts of Pd2+ ions from water and wastewater samples before its spectrophotometric detection. Pd2+ ions were desorbed from MMOF by nitric acid and were complexed by treating with KI solution to have a maximum absorbance at 410 nm. The synthesized MMOF composite showed a very large surface area (65 m2.g− 1), good magnetization (1.7 emu.g− 1) and a large pore volume (0.059 cm3.g− 1) with adsorption capacity of 194.5 mg of Pd2+ ions/g of the adsorbent. This nanosorbent boasts chemo-mechanical stability, high adsorption capacity due to its vast active sites, and facile recovery facilitated by its magnetic properties. Parameters affecting the extraction efficiency of the method were optimized as pH of the sample 7.4, volume of the sample 25 mL, 15 mg adsorbent, 1 mL of 0.1 M HNO3 eluent, with 10 and 15 min as the extraction and desorption times, respectively. The calibration curve was found to be linear across the 10.0–1500.0 µg.L− 1 range with a limit of detection of 1.05 µg.L− 1. The obtained extraction efficiency and enrichment were 98% and 245, respectively. The total analysis time was less than 30 min. This MMOF has never been used for the extraction of Pd2+ ions before. [ABSTRACT FROM AUTHOR]

The aim of this research was to develop a low price and environmentally friendly adsorbent with abundant of source to remove methylene blue (MB) from water samples. Sawdust solid-phase extraction coupled with high-performance liquid chromatography was used for the extraction and determination of MB. In this study, an experimental data-based artificial neural network model is constructed to describe the performance of sawdust solid-phase extraction method for various operating conditions. The pH, time, amount of sawdust, and temperature were the input variables, while the percentage of extraction of MB was the output. The optimum operating condition was then determined by genetic algorithm method. The optimized conditions were obtained as follows: 11.5, 22.0 min, 0.3 g, and 26.0°C for pH of the solution, extraction time, amount of adsorbent, and temperature, respectively. Under these optimum conditions, the detection limit and relative standard deviation were 0.067 μg L−1 and <2.4%, respectively. The Langmuir and Freundlich adsorption models were applied to describe the isotherm constant and for the removal and determination of MB from water samples. [ABSTRACT FROM AUTHOR]

Dispersive liquid–liquid microextraction (DLLME) coupled with gas chromatography was applied for the extraction and determination of essential oil constituents of the Borago officinalis L. In this study, an experimental data-based artificial neural network (ANN) model was constructed to describe the performance of DLLME method for various operating conditions. The volume of extraction and dispersive solvents, extraction time and salt effect were the input variables of this process, whereas the extraction efficiency was the output. The ANN method was found to be capable of modeling this procedure accurately. The overall agreement between the experimental data and ANN predictions was satisfactory showing a determination coefficient of 0.982. The optimum operating conditionwas then determined by the genetic algorithm method. The optimal conditions were 248 μL volume of extraction solvent, 260 μL volume of dispersive solvent, 2.5 min extraction time and 0.16 mol L-1 of salt. The limit of detection and linear dynamic range were 0.15–24.0 and 1.2–1,800 ng mL-1, respectively. The main components of the essential oil were δ-cadinene (31.02%), carvacrol (24.91%), α-pinene (20.89%) and α-cadinol (16.47%). [ABSTRACT FROM AUTHOR]

This paper describes a pre-concentration procedure using magnetic molecularly imprinted polymer (MMIP) nanoparticles for the extraction of copper(II) from aqueous samples prior to its atomic absorption determination. Cu-morin complex was used as template molecule which was chemically bonded to MMIP nanoparticles. MMIP nanoparticles were characterized by scanning electron microscopy as well as Fourier transform infrared spectroscopy. The extraction conditions including pH value, adsorption and desorption time, temperature, amount of ligand and ionic strength of the sample matrix were studied and optimized. The method showed good extraction recoveries (≥96%) with relative standard deviation below 3.4% for real samples. The linear range of calibration curve was between 5-1000 μg/L with a correlation coefficient ( r) of 0.996. The detection limit was 0.5 μg/L. The method was suitable for the determination of trace copper in drinking water samples. [ABSTRACT FROM AUTHOR]

In recent years there has been a rising interest in the application of nanomaterial such as silver nanoparticles (AgNps) in many areas of scientific research. The most active areas of investigation are related to the study and application of optical, biomedical, and newly applied adsorption properties of AgNps. The recent evaluation of adsorptive properties of AgNPs has added new areas to their wide range of applications in analytical separations and pre-concentrating steps. They have also been used for removal of several environmental organic pollutants and uptake of heavy metals. The main objective of this review is to describe the characteristics, mechanisms, and behavior of AgNPs as adsorbent in aquatic systems and sample solutions. [ABSTRACT FROM AUTHOR]

Electromembrane extraction (EME) coupled with high-performance liquid chromatography was developed for determination of organic compounds including citric, tartaric and oxalic acid in biological samples. Organic compounds moved from aqueous samples, through a thin layer of 1-octanol immobilized in the pores of a porous handmade polypropylene tube, and into a basic aqueous acceptor solution present inside the lumen of the tube. This new set-up for EME has a future potential such as simple, cheap and fast sample preparation technique for extraction of organic compounds in various complicated matrices. The pH of acceptor phase, extraction time, voltage, ionic strength, temperature and stirring speed were studied and optimized. Optimum conditions were: the pH of acceptor phase, 7; extraction time, 30 min; voltage, 30 V and stirring speed, 500 rpm. At the optimum conditions, the preconcentration factors of 175–200, the limits of detection of 1.9-3.1 μg L-1 were obtained for the analytes. The developed procedure was then applied to the extraction and determination of organic acid compounds from biological samples. [ABSTRACT FROM AUTHOR]

In this study, dispersive solid phase extraction combined with dispersive liquid-liquid extraction has been developed for the extraction of benzene, toluene, ethylbenzene, and xylenes isomers (BTEX) in soil samples prior to gas chromatography-mass spectrometry. The BTEX were extracted from soil sample into acetonitrile by dispersive solid phase extraction method, and the extract was then used as dispersive solvent in dispersive liquid-liquid extraction procedure. Ant colony optimization-artificial neural network (ACO-ANN) has been employed to develop the model for simulation and optimization of this method. The volume of dispersive solvent, volume of extraction solvent, extraction time, and ultrasonic time were the input variables, while the multiple response function (Rm) of analytes was the output. The optimum operating condition was then determined by ant colony optimization method. At the optimum conditions, the limit of detections of 0.12-0.75 ng g−1 was obtained for the BTEX. The developed procedure was then applied to the extraction and determination of BTEX in the soil samples and one certified soil. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this study, chitosan-zinc oxide nanoparticles were used as an adsorbent matrix for solid-phase extraction and combined with dispersive liquid-liquid microextraction (SPE-DLLME) for determination of benzene, toluene, ethylbenzene, and xylene isomers (BTEX) in water samples. The eluent of SPE was used as the dispersive solvent of the DLLME for further purification and enrichment of the BTEX prior to gas chromatography-flame ionization detector analysis. The effect of variables, including amount of adsorbent, sample and eluent flow rate, type and volume of extraction and dispersive solvent, salt concentration, and extraction time, was investigated and they were optimized. Under the optimum conditions, good linearity for all BTEX with determination coefficients in the range of 0.9993 < r[sup 2] < 0.9997, suitable precision (1.4 % < RSD < 1.9 %; where RSD refers to relative standard deviation), and low detection limits (0.5-1.1 μg L[sup -1] ) were achieved. The current chitosan-zinc oxide nanoparticles SPE-DLLME procedure combines the advantages of SPE and DLLME, and was applied for determination of BTEX in water samples and acceptable recoveries were obtained. [ABSTRACT FROM AUTHOR]

In this study, wheat stem was used for electromembrane extraction (EME) for the first time. The EME technique involved the use of a wheat stem whose channel was filled with 3 M HCl, immersed in 10 mL of an aqueous sample solution. Thorium migrated from aqueous samples, through a thin layer of 1-octanol and 5%v/v Di-(2-ethylhexyl) phosphate (DEHP) immobilized in the pores of a porous stem, and into an acceptor phase solution present inside the lumen of the stem. The pH of donor and acceptor phases, extraction time, voltage, and stirring speed were optimized. At the optimum conditions, an enrichment factor of 50 and a limit of detection of 0.29 ng mL −1 was obtained for thorium. The developed procedure was then applied to the extraction and determination of thorium in water samples and in reference material. [ABSTRACT FROM AUTHOR]

There is a great deal of interest in the application of nanomaterials, nanotechnology and nanocrystalline inorganics, such as silver nanoparticles (AgNPs), whose intriguing physical and chemical properties have been topics of many scientific research projects. Notable for their extremely small size, AgNPs have been seen in wide-ranging fields, such as optical probes, optical sensors, and plasmonic and biomedical applications. Since AgNPs show different properties, such as surface-plasmon resonance, large surface area, catalysis, and quantum size effects, they can be used for bioassays based on electrochemistry, silver-enhanced fluorescence, surface-enhanced Raman scattering, colorimetry and chemiluminescence. In this review, we highlight the potential of AgNPs as nanoadsorbents for the analytical processes of extraction, separation and sample pretreatment. [ABSTRACT FROM AUTHOR]

In this study, chitosan-zinc oxide nanoparticles were used as a sorbent of miniaturized matrix solid-phase dispersion combined with flotation-assisted dispersive liquid-liquid microextraction for the simultaneous determination of 13 n-alkanes such as C8H18 and C20H42 in soil samples. The solid samples were directly blended with the chitosan nanoparticles in the solid-phase dispersion method. The eluent of solid-phase dispersion was applied as the dispersive solvent for the following flotation-assisted dispersive liquid-liquid microextraction for further purification and enrichment of the target compounds prior to gas chromatography with flame ionization detection. Under the optimum conditions, good linearity with correlation coefficients in the range 0.9991 < r2 < 0.9995 and low detection limits between 0.08 to 2.5 ng/g were achieved. The presented procedure combined the advantages of chitosan-zinc oxide nanoparticles, solid-phase dispersion and flotation-assisted dispersive liquid-liquid microextraction, and could be applied for the determination of n-alkanes in complicated soil samples with acceptable recoveries. [ABSTRACT FROM AUTHOR]

Highlights: [•] Organic dye in industrial wastewater may result in serious environmental problem. [•] The nanoparticles have large specific area and internal diffusion resistance is absence. [•] The nanoparticles have a higher efficiency for the removing of analyte. [•] The ANN–COA was used to optimize the extraction percent of analyte. [ABSTRACT FROM AUTHOR]

Abstract: In this study, a solid phase extraction using the new sorbent (zinc oxide nanoparticles–chitosan) has been developed for preconcentration and determination of trace amount of uranium from water samples. Hybrid modeling of cuckoo optimization algorithm–artificial neural network (COA–ANN) has been employed to develop the model for simulation and optimization of this method. The 1-(2-pyridylazo)-2-naphthol (PAN) was used as chelating agent. The pH, volume of elution solvent, mass of zinc oxide nanoparticles–chitosan, concentration of PAN, flow rate of sample and elution solvent were the input variables, while recovery of uranium was the output. At the optimum conditions, the limit of detections and enrichment factor were 0.5μgL−1 and 125, respectively for the uranium. The developed procedure was then applied to the extraction and determination of uranium from water samples. [Copyright &y& Elsevier]

In this study, zinc oxide nanoparticles-chitosan based on solid phase extraction and high performance liquid chromatography was developed for the separation of organic compounds including citric, tartaric and oxalic acids from biological samples. For simulation and optimization of this method, the hybrids of genetic algorithm with response surface methodology (RSM) and artificial neural network (ANN) have been used. The predictive capability and generalization of both predictive models (RSM and ANN) were compared by unseen data. The results have shown the superiority of ANN compared with RSM. At the optimum conditions, the limits of detections of 2.2-2.9 µg L−1 were obtained for the analytes. The developed procedure was then applied to the extraction and determination of organic acid compounds from biological samples. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Highlights: [•] Zinc was extracted from flour sample using homogenous liquid–liquid microextraction. [•] HLLME is a green extraction technique. [•] This extraction method is simple, efficient and fast. [•] PSO–ANN model was investigated to predict the extraction yield. [•] Determination of the zinc in flour samples was successfully performed. [ABSTRACT FROM AUTHOR]

Highlights: [•] Manganese is essential for humans. [•] Excessive manganese levels are detrimental to the organism. [•] Tea waste extraction method is simple, efficient and fast. [•] Extracting trace amounts of manganese from food samples is essential. [•] The linear regression between the experimental data and network outputs was 0.9755. [ABSTRACT FROM AUTHOR]

The article provides an overview on the classification, preparation and applications of nanoadsorbents, focusing on aqueous media. It discusses the classification of nanomaterials as nanoadsorbets and the importance of nanomaterials in the pre-concentration process. It also tackles the mechanisms and properties of nanomaterials as adsorbents.

In this study, an easy and fast procedure based on solid phase extraction was developed that is intended to pre-concentrate, separate, and determine trace amounts of Fe(III) ions in biological samples using flame atomic absorption spectrometry (FAAS). Silver nanoparticles coated with silica gel were modified by morin and then used as a sorbent. It was synthesized by mixing slurried silica gel with silver nitrate and sodium citrate. The effects of experimental conditions, including pH, sample and eluent flow rates, and the type and least amount of an eluent to the elute iron from the sorbent were studied, and optimum values of these parameters have been found. Under the optimum conditions, the limit of detection of this procedure for Fe(III) was 67 ng/l. The relative standard deviation (RSD%) was 2.5 % (n = 10, C = 0.5 mg/l). The developed procedure was used to determine iron in biological samples. [ABSTRACT FROM AUTHOR]

Abstract: In this study, a three-layer artificial neural network (ANN) model was investigated to predict the extraction yield of essential oils from Diplotaenia cachrydifolia by supercritical fluid extraction. A multilayer feed-forward neural network trained with an error back-propagation algorithm was employed for developing a predictive model. The input parameters chosen of the model are pressure, temperature, extraction time and modifier volume while the extraction yield of essential oils is the output. The Levenberg–Marquardt (LM) algorithm was used to train ANN. The results showed that a network with five hidden neurons was highly accurate in predicting the extraction yield of essential oils of D. cachrydifolia. The mean squared error (MSE) and coefficient of determination (R 2) between the actual and predicted values were determined as 0.0014 and 0.9983 for training, 0.0184 and 0.9542 for validation and 0.0221 and 0.9703 for testing date sets. The main components that were extracted with SFE were dillapiole (30.2%), limonene (13.7%) and α-calacorene (20.1%). [Copyright &y& Elsevier]

A simple procedure based on magnetic nanoparticles has been developed for analytical purposes. In this method, 1-(2-pyridylazo)-2-naphthol (PAN)-modified magnetic nanoparticles (MNPs) were used for separation and pre-concentration of manganese(II) ions from aqueous samples. This method combines the use of a solution solvent with separation of magnetic nanoparticles from sample solution using a magnet. The influence of different parameters, such as amount of extractant (PAN) loaded on the nanoparticles, pH of solution, adsorption time, amount of modified nanoparticle, type and amount of eluents for desorption of manganese from magnetic nanoparticles were evaluated. The effect of various cationic and anionic interferences on the percentage recovery of manganese was also studied. Manganese ions were adsorped from a solution at pH 9.5 and desorbed from nanoparticles with 10 mL of DMSO : HNO3 (1 : 1, v/v). The detection limit of the proposed method was found to be 0.11 µg L−1. The method was employed to recover and determine the level of manganese in different water samples. [ABSTRACT FROM AUTHOR]

Abstract: In this study, a new method called miniaturised homogenous liquid–liquid extraction, followed by graphite furnace atomic absorption spectrometry, was developed for the extraction and determination of lead from food samples. The procedure was based on the fast extraction of lead from an acetic acid sample solution into 0.5mL chloroform, as an extraction solvent. After adding water into the mixture, the extracting solvent phase immediately formed a distinct water-immiscible phase below the vial, which could easily be separated, evaporated and re-dissolved in 1.0mL nitric acid 0.1molL−1 for further analysis. The effects of various experimental parameters in extraction step were studied using two optimisation methods, one variable at a time and Box–Behnken design. The results showed that the amount of salt and extraction time did not have effect on the extraction efficiency. Therefore, a three-level Box–Behnken experimental design with three factors, which combined the response surface modelling, was used to optimise lead extraction. Three independent variables, including pH of solution (ranging from 6.5 to 10.5), concentration of dithizone as chelating agent (ranging from 0.05 to 0.5μgL−1) and extracting solvent volume (ranging from 300 to 900μL) were respectively coded as pH, D and V at three different levels (−1, 0 and 1). In this study, the optimum condition was determined at pH 8.4, a volume of chloroform at 0.45mL, and concentration of dithizone at 0.5μgL−1. Under the optimum condition, the limit of detection (LOD) was 0.05μgL−1. Furthermore, the relative standard deviation of the ten replicate was <5.0%. The developed procedure was applied to the extraction and determination of lead in the food samples. [Copyright &y& Elsevier]

This work describes the development by response surface methodology (RSM) of a procedure for copper determination by inductively coupled plasma optical emission spectrometry (ICP OES) in water samples after extraction by copper imprinted polymer. Results of the two-level full factorial design (24) based on an analysis of variance demonstrated that only the solution pH; amount of polymer and adsorption time were statistically significant. Optimal conditions for the extraction of copper samples were obtained by using Box-Behnken design. Solution pH; amount of polymer and adsorption time were regarded as factors in the optimisation study. The working conditions were 4.6, 0.03 g and 3.5 h, for solution pH, amount of polymer; and adsorption time, respectively. Under the optimised experimental conditions, the detection limit of the proposed method followed by ICP OES was found to be 0.8 µg L−1. The relative standard deviation (RSD) was found to less than 0.81%. The pre-concentration factor was 22.5. The accuracy of the optimised procedure was evaluated by analysis of certified reference material. The method was applied to the determination of copper in water samples. [ABSTRACT FROM PUBLISHER]

In this study, ion-imprinted polymer was prepared for manganese(II) by formation of binary (1-(2-pyridylazo)-2-naphthol) complex in methanol (porogen) following copolymerization with 4-vinylpyridine (VP), ethyleneglycoldimethacrylate (EDMA), and 2,2′-azobisisobutyronitrile (AIBN) as a functional monomer, cross-linking agent, and initiator, respectively. The standardized effects of the independent variables and their interactions were also investigated using Pareto chart. Results of the two-level fractional factorial design (2) based on an analysis of variance demonstrated that only pH of solution, amount of polymer, and adsorption time were seen to be statistically significant. For optimization of manganese removal from aqueous solution by manganese-imprinted polymer (Mn-IP) a three-factor, three level Box-Behnken design techniques combining with response surface methodology (RSM) was used on 15 different experimental data obtained in a batch study. The significance of independent variables and their interactions were tested by the analysis of variance (ANOVA) with 95% confidence limits. The optimal conditions were 9.7, 44.4 mg, and 19.1 min for pH of solution, amount of polymer, and adsorption time, respectively. Under the optimized experimental conditions, the detection limit of the proposed procedure followed by ICP-OES was found to be 0.6 μg L. Furthermore, the distribution ratio and selectivity coefficients of manganese and other selected ions were investigated. The method was applied to the determination of manganese in water samples. [ABSTRACT FROM AUTHOR]

Imprinted polymer particles have been developed as a novel adsorbent for the adsorption of copper from aqueous solution. This method has received much attention in various fields because of their high selectivity for template molecules. In this work, separation of copper from water and biological samples by batch solid phase extraction based on molecular imprinting technique is presented. Copper-imprinted polymer was prepared by free radical solution polymerization in a glass tube containing CuSO, morin, 4-vinylpyridine as a functional monomer, ethyleneglycoldimethacrylate as a cross-linking monomer, 2,2′- azobisisobutyronitrile as an initiator. The polymer block obtained was ground and sieved, and the Cu-morin complex was removed from polymer particles. The synthesized polymer particles both prior to and after leaching have been characterized by IR and X-ray diffraction studies. The effect of different parameters, such as pH, adsorption and desorption time, type and least amount of the eluent for elution of the complex from polymer were evaluated. The limit of detection of the proposed method was 0.12 μg L. The method was applied to the recovery and determination of copper in water and biological real samples. [ABSTRACT FROM AUTHOR]

Abstract: In this work, several lead-ion imprinted polymers (Pb(II)-IIP) for pre-concentration and determination of lead by graphite furnace atomic absorption spectrometry were synthesized based on the batch solid phase extraction. For this purpose, copolymerization of Pb(II)–morin complex was performed using 4-vinylpyridine (VP), ethyleneglycoldimethacrylate (EDMA) and 2,2′-azobisisobutyronitrile (AIBN) as functional monomer, cross-linking agent and initiator, respectively. The polymer particles were characterized by FT-IR and X-ray diffraction (XRD). The optimization process was carried out using a two-level fractional factorial design and the Box–Behnken matrix. Four variables including pH, shaking time, mass of polymer and morin were selected as the factors affecting the optimization process. The obtained results using the two-level fractional factorial design indicated that pH, mass of polymer and morin were statistically significant. Using the Box–Behnken design, the optimal conditions for the extraction of lead were 6.1, 29.2mg and 2.7mg, for pH, mass of polymer and morin, respectively. Under the optimized conditions, the detection limit of the proposed method was found to be 92ngL−1, while the relative standard deviation for 10 replicates was 4%. [Copyright &y& Elsevier]

Abstract: The oil and extracts of Satureja hortensis cultivated in Iran were extracted using supercritical carbon dioxide and hydrodistillation method. The oil and extracts were analyzed by GC-FID and GC/MS. The compounds were identified according to their retention indices and mass spectra (EI, 70eV). The effects of various parameters such as pressure, temperature, percent of modifier (methanol) and extraction time, were investigated by a fractional factorial design (24-1) to determine the significant parameters and their interactions. The results showed that the pressure, temperature and percent of modifier are significant (p <0.05), but the extraction time was found to be insignificant. The response surface methodology (RSM), based on Box-Behnken design was employed to obtain the optimum conditions of the significant parameters (pressure, temperature and percent of modifier). The optimal conditions could be obtained at a pressure of 35.0MPa, temperature of 72.6°C, and 8.6% (v/v) for methanol. The main extracted components using SFE were γ-Terpinene (35.5%), Thymol (18.2%) and Carvacrol (29.7%). [Copyright &y& Elsevier]

Abstract: In the present study, we developed a magnetic nanoparticle adsorbent that uses iron oxide nanoparticles as the core and 1-(2-pyridylazo)-2-naphthol (PAN) as manganese ion exchange groups in cereal samples. This adsorbent was shown to be quick and efficient for the adsorption of manganese due to higher specific surface area, lower mass removal resistance and the absence of internal diffusion resistance. This method is simple and rapid for the preconcentration and determination of manganese in food samples by inductively coupled plasma optical emission spectrometry (ICP OES). The technical feasibility of magnetic nanoparticles for the removal of manganese was investigated under batch studies. It was based on (PAN)-modified magnetic nanoparticles. Four variables (pH of solution, amount of extractant (E), amount of nanoparticles (N) and time) were regarded as factors in the optimization. Results of the two-level fractional factorial design (24−1) based on an analysis of variance demonstrated that only the pH, amount of extractant (E) and amount of nanoparticles (N) were statistically significant. Optimal conditions for the extraction of manganese were obtained using Box–Behnken design. For optimum recovery of manganese, the variables pH of solution, amount of nanoparticles and amount of extractant values were 9.44, 3.46mg and 3.91mg, respectively. In the optimum experimental conditions, the limit of detection and enrichment factor of the proposed method were 0.1μgL−1 and 28, respectively. The precision as RSD was 3.6% for concentration of 50μgL−1. The accuracy of the proposed procedure was evaluated by analysis of certified reference material. The method was applied to the determination of manganese in barley, wheat and rice flour samples. The manganese content in the samples analyzed varied from 7.8 to 19.9μgg−1. [ABSTRACT FROM AUTHOR]

Essential oil of Nepeta persica cultivated in Iran was obtained by steam distillation and supercritical (carbon dioxide) extraction methods. The oils were analysed by capillary gas chromatography using flame ionization and mass spectrometric detections. The compounds were identified according to their retention indices and mass spectra (EI, 70 eV). The effects of different parameters such as pressure, temperature, modifier volume and extraction times (dynamic and static) on the supercritical fluid extraction (SFE) of N. persica oil were investigated. The results showed that under the pressure of 20.3 MPa, temperature of 45 °C, methanol of 1.5% v/v), dynamic extraction time of 50 min and static extraction time of 25 min extraction was more selective for the 4αβ,7α,7aα-nepetalactone. Twelve compounds were identified in the steam-distilled oil. The major components of N. persica were 4αβ,7α,7aα-nepetalactone (26.5%), cis-α-farnesene (4.4%) and 3,4α-dihydro-4aα,7α,7aα-nepetalactone (3.5%). However, by using supercritical carbon dioxide under optimum conditions, only two components have more than 90.0% of the oil. The extraction yield based on steam distillation was 0.08% (v/w). On the other hand, using SFE extraction yield in the range of 0.22-8.90% (w/w) were obtained at different conditions. The results show that, in Iranian N. persica oil, 4αβ,7α,7aα-nepetalactone is a major component. [ABSTRACT FROM AUTHOR]

Abstract: This article describes the development of a procedure for zinc determination in water and biological samples after extraction by magnetic nanoparticles by inductively coupled plasma optical emission spectrometry (ICP-OES). The optimization strategy was carried out by using two level full factorial designs. Results of the two level full factorial design (24) based on an analysis of variance demonstrated that only the pH, amount of extractant and amount of nanoparticles were statistically significant. Optimal conditions for three variables: pH of solution, amount of extractant (E), and amount of nanoparticles (N) for the extraction of zinc samples were obtained by using Box–Behnken design. These values were 3.8, 3.1 and 3.3mg, for pH of solution, amount of nanoparticles and amount of extractant, respectively. Under the optimized experimental conditions, the detection limit of the proposed method followed by ICP-OES was found to be 0.8μgL−1. The method was applied to the determination of zinc in water and biological samples. [Copyright &y& Elsevier]

In this article, the separation of zinc from aqueous samples by solid-phase extraction based on a molecular imprinting technique is described. Zn-imprinted polymer was prepared by free radical solution polymerisation in a glass tube containing ZnSO4, morin, 4-vinylpyridine as a functional monomer, ethyleneglycoldimethacrylate as a cross-linking monomer, and 2,2'-azobisisobutyronitrile as an initiator. The obtained polymer block was ground and sieved (55-75 µm) and the Zn-morin complex was separated from polymer particles by leaching with 2M HCl. The synthesised polymer particles have been characterised by IR and differential scanning calorimetric studies either before or after leaching. The effects of different parameters, such as pH, adsorption and desorption time, type and minimum amount of the eluent for elution of the complex from polymer were evaluated. Extraction efficiency more than 99% was obtained by elution of the polymers with 10 mL of CH2Cl2-dimethyl sulfoxide (1 : 1, v/v). The detection limit of the proposed method was 2.9 µg L-1. A dynamic linear range in the range of 25-200 µg L-1 was obtained. The relative standard deviation was found to be below 9.2%. In addition, the influence of various cationic and anionic interferences on the complex recovery was studied. The method was applied to the recovery and determination of Zn in a few different real samples. [ABSTRACT FROM AUTHOR]

A simple method based on magnetically assisted chemical separation has been developed for analytical purposes. In this method, morin-modified magnetic nanoparticles were used for the selective extraction and preconcentration of copper ions from aqueous solutions. The influence of different parameters, such as the presence of the morin extractant, the amount of morin extractant loaded on the nanoparticles, the pH, adsorption time and the type and minimum amount of eluent required for elution of the copper from the magnetic nanoparticles, were evaluated. The detection limit of the proposed method followed by ICP-OES was found to be 1.3 µg L-1 and a dynamic linear range of 10-200 µg L-1 was obtained. The relative standard deviation was less than 5%. The method was applied to the recovery and determination of copper in real samples. [ABSTRACT FROM AUTHOR]

Abstract: This article describes the application of response surface methodology (RSM) to the development of a procedure for zinc and copper determination by flame atomic absorption spectrometry (FAAS) in food samples after extraction by a microwave system. A Box-Behnken matrix was used to find optimal conditions for the procedure through a response surface study. Three variables “irradiation power; time; and temperature” were regarded as factors in the optimization study. The working conditions were established as a compromise between optimum values found for each analyte taking into consideration the robustness of the procedure. These values were 97°C, 90W and 9.0min, for temperature, irradiation power and time, respectively. The accuracy of the optimized procedure was evaluated by the analysis of certified reference materials. The method was applied to the determination of copper and zinc in wheat flour and corn flour samples. [Copyright &y& Elsevier]

This work reports the preparation of molecularly imprinted polymer (MIP) particles for selective extraction and determination of aluminum ion from aqueous media. Polymerization was achieved in a glass tube containing AlCl3, morin, 4-vinylpyridine, ethyleneglycoldimethacrylate, 2,2' - azobisisobutyronitrile. The polymer block obtained was ground and sieved (55-75 μ m) and the Al (III)-morin complex was removed from polymer particles by leaching with 2 M of HCl, which leaves a cavity in the polymer particles. The polymer particles, both prior to and after leaching, have been characterized by IR and differential scanning calorimetry (DSC) studies. The effect of different parameters, such as pH, adsorption and desorption time, type and least amount of eluent for elution of complex from polymer were evaluated. Extraction efficiencies more than 99% were obtained by elution of the polymers with 15 mL of methanol-acetonitrile mixture (1:2) followed by ICP-OES. The limit of detection of the proposed method was 3.5 μ g L-1. A dynamic linear range (DLR) in the range of 20 to 200 μ g L-1 was obtained. The relative standard deviation (RSD) was less than 6.5%. The influence of various cationic and anionic interferences on percent recovery of complex was studied. The method was applied to the recovery and determination of aluminum in different real samples. [ABSTRACT FROM AUTHOR]

Abstract: Essential oil of Salvia mirzayanii cultivated in Iran was obtained by hydrodistillation and supercritical (carbon dioxide) extraction methods. The oil was analysed by capillary gas chromatography using flame ionization and mass spectrometric detections. The compounds were identified according to their retention indices and mass spectra (EI, 70eV). The effects of different parameters such as pressure, temperature, modifier volume and extraction times (dynamic and static) on the supercritical fluid extraction (SFE) of S. mirzayanii oil were investigated. The results showed that, under a pressure of 35.5MPa, temperature of 35°C, 6% methanol, dynamic extraction time of 50min and static extraction time of 30min, extraction was more selective for the linalyl acetate. Thirty four compounds were identified in the hydrodistilled oil. The major components of S. mirzayanii were linalyl acetate (7.6%), 1,8-cineole (8.0%), linalool (9.0%) and 8-acetoxy linalool (11.0%). However, by using supercritical carbon dioxide in optimum conditions, only three components contain more than 63% of the oil. The yield of the obtained oil based on hydrodistillation was 2.20% (v/w). Extraction yield based on the SFE varied in the range of 1.50–9.67% (w/w) under different conditions. The results revealed that, in Iranian S. mirzayanii oil, linalyl acetate is a major component. [Copyright &y& Elsevier]

Abstract: This work reports the preparation of molecularly imprinted polymer (MIP) particles for selective extraction and determination of selenium ions from aqueous media. Polymerization was achieved in a glass tube containing SeO2, o-phenylenediamine, 2-vinylpyridine (VP), ethyleneglycoldimethacrylate (EDMA), 2,2′-azobisisobutyronitrile (AIBN). The polymer block obtained was ground and sieved (55–75μm) and the Se-o-phenylenediamine complex was removed from polymer particles by leaching with 2M of HCl, which leaves a cavity in the polymer particles. The polymer particles both prior to and after leaching have been characterized by IR and thermogravimetric (TG) studies. The effect of different parameters, such as pH, extraction time, type and least amount of eluent for elution of complex from polymer were evaluated. Extraction efficiencies >99% were obtained by elution of the polymers with 15mL of methanol–acetonitrile mixture (1:2, v/v). The limit of detection of the proposed method followed by hydride generation atomic absorption spectroscopy (HG-AAS) was found to be 3.3μgL−1 and a dynamic linear range (DLR) of 10–200μgL−1 was obtained. The relative standard deviations (R.S.D.s) at 30.0μgL−1 of Se were below than 8.1%. The influence of various cationic interferences on percent recovery of complex was studied. The method was applied to the recovery and determination of selenium in different real samples. [Copyright &y& Elsevier]

Abstract: In the present work, a rapid method for the extraction and determination of chlorobenzenes (CBs) such as monochlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-dichlorobenzene, 1,2,3-trichlorobenzene and 1,2,4-trichlorobenzene in water samples using the headspace solvent microextraction (HSME) and gas chromatography/electron capture detector (ECD) has been described. A microdrop of the dodecane containing monobromobenzene (internal standard) was used as extracting solvent in this investigation. The analytes were extracted by suspending a 2.5μl extraction drop directly from the tip of a microsyringe fixed above an extraction vial with a septum in a way that the needle passed through the septum and the needle tip appeared above the surface of the solution. After the extraction was finished, the drop was retracted back into the needle and injected directly into a GC column. Optimization of experimental conditions such as nature of the extracting solvent, microdrop and sample temperatures, stirring rate, microdrop and sample volumes, the ionic strength and extraction time were investigated. The optimized conditions were as follows: dodecane as the extracting solvent, the extraction temperature, 45°C; the sodium chloride concentration, 2M; the extraction time, 5.0min; the stirring rate, 500rpm; the drop volume, 2.5μl; the sample volume, 7ml; the microsyringe needle temperature, 0.0°C. The limit of detection (LOD) ranged from 0.1μg/l (for 1,3-dichlorobenzene) to 3.0μg/l (for 1,4-dichlorobenzene) and linear range of 0.5–3.0μg/l for 1,2-dichlorobenzene, 1,3-dichlorobenzene and from 5.0 to 20.0μg/l for monochlorobenzene and from 5.0 to 30μg/l for 1,4-dichlorobenzene. The relative standard deviations (R.S.D.) for most of CBs at the 5μg/l level were below 10%. The optimized procedure was successfully applied to the extraction and determination of CBs in different water samples. [Copyright &y& Elsevier]