Gachsaran Azad University

Do Gonbadān, Iran

Gachsaran Azad University

Do Gonbadān, Iran
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Ghaedi M.,Yasouj University | Montazerozohori M.,Yasouj University | Biyareh M.N.,Yasouj University | Mortazavi K.,Gachsaran Azad University | And 2 more authors.
International Journal of Environmental Analytical Chemistry | Year: 2013

Multiwalled carbon nanotubes chemically functionalized with 2-((3-silylpropylimino) methyl) phenol (SPIMP-MWCNT) and successfully applied for the solid phase extraction (SPE) of some metal ions in food samples. The influences of the analytical parameters including pH, amounts of solid phase, eluent conditions (type, volume and concentrations), sample volume and interference of some metal ions on the recoveries of ions Cu2+, Pb2+, Fe2+, Ni2+ and Zn2+ ion were investigated. The metal ions retained on SPIMP-MWCNT was eluted using 6 mL of 4 mol L-1 HNO3 solution and their content was determined by flame atomic absorption spectrometry (FAAS) with recoveries more than 95% and relative standard deviations (n = 5) between 2.4-3.4% for both reproducibility and repeatability. The detection limit of this metal ions was between 1.0-2.6 ng mL-1 (3Sb, n = 10) and their preconcentration factor was 100, while their loading capacity was above 32.9 mg g-1 of SPIMP-MWCNT. The proposed method was successfully applied for the preconcentration and determination of analytes in different samples. © 2013 Copyright Taylor and Francis Group, LLC.

Ghaedi M.,Yasouj University | Niknam K.,Persian Gulf University | Niknam E.,Gachsaran Azad University | Mortazavi K.,Gachsaran Azad University | And 2 more authors.
Journal of the Chinese Chemical Society | Year: 2010

Amethod for the simultaneous preconcentration of Cu2+, Zn 2+ and Fe3+ ions, in some food samples has been reported. The method is based on the adsorption of 3-(1-(1-H-indol-3-yl)-3-phenylallyl)- 1H-indole (IPAI) loaded on Duolite XAD 761. The metal ions adsorbed on the modified solid phase resin are eluted using 6 mLof 4 mol L-1 nitric acid. The influences of the analytical parameters including pH and amount of ligand and solid phase and type and amount of surfactant and sample volume on the metal ions recoveries were investigated. The effects of matrix ions on the retentions of the analytes were also examined. The recoveries of analytes were generally higher than 95% with a RSD lower than 5%. The method has been successfully applied for these metals content evaluation in some real samples.

Ahmadi F.,Gachsaran Azad University | Niknam K.,Persian Gulf University | Niknam E.,Gachsaran Azad University | Delavari S.,Gachsaran Azad University | Khanmohammadi A.,Gachsaran Azad University
E-Journal of Chemistry | Year: 2011

Bis((1H-benzo[d]imidazol-2yl)methyl)sulfane (BHIS) was used as a complexing agent in cloud point extraction for the first time and applied for selective pre-concentration of trace amounts of silver. The method is based on the extraction of silver at pH 8.0 by using non-ionic surfactant T-X114 and bis((1H-benzo[d]imidazol-2yl)methyl)sulfane as a chelating agent. The adopted concentrations for BHIS, Triton X-114 and HNO3, bath temperature, centrifuge rate and time were optimized. Detection limits (3SDb/m) of 1.7 along with enrichment factor of 39 for silver ion was achieved. The high efficiency of cloud point extraction to carry out the determination of analytes in complex matrices was demonstrated. The proposed method was successfully applied to the ultra-trace determination of silver in real samples.

Hosseini S.J.,Gachsaran Azad University | Kokhdan S.N.,Gachsaran Azad University | Ghaedi A.M.,Gachsaran Azad University | Moosavian S.S.,Gachsaran Azad University
Fresenius Environmental Bulletin | Year: 2011

Commercially powdered activated carbon and multiwalled carbon nanotubes were used for the removal of methyl orange (MO) from aqueous solutions. The effects of solution pH, initial dye concentration, temperature and sorption time on MO removal were studied. The equilibrium sorption isotherms have been analyzed by Langmuir, Freundlich, Dubinin and Radushkevich (D-R), and HarkinsJura (H-J) models, and Langmuir isotherms had the highest correlation coefficients. The apparent thermodynamic parameters were calculated, and the obtained values support the conclusion that MO molecules sorb by an entropydriven, endothermic process. The kinetic of the sorption was analyzed using pseudo-first order, pseudo-second order, Elovich and intraparticle diffusion kinetic models. The data showed that the second-order equation was the more appropriate one, although intraparticle diffusion is the ratelimiting factor. © by psp.

Alizadeh M.,Gachsaran Azad University | Chamsaz M.,Ferdowsi University of Mashhad | Asadpour S.,Ferdowsi University of Mashhad
Asian Journal of Chemistry | Year: 2011

A quantitative structure-retention relationship (QSRR) study, has been carried out on 50 diverse phenols in gas chromatography (GC) in a dual-capillary column system made of DB-5 (SE-54 bonded phase) and DB-17 (OV-17 bonded phase) fused-silica capillary columns by using molecular structural descriptors. Modeling of retention times of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR), partial least squares (PLS) regression and artificial neural networks (ANN). Stepwise SPSS was used for the selection of the variables (descriptors) that resulted in the best-fitted models. For prediction retention times of compounds in DB-5 and DB-17 columns, three and four descriptors, respectively were used to develop a quantitative relationship between the retention times and structural properties. Appropriate models with low standard errors and high correlation coefficients were obtained. After variables selection, compounds randomly were divided into two training and test sets and MLR and PLS methods (with leave-oneout cross validation) and ANN used for building of the best models. The predictive quality of the QSRR models were tested for an external prediction set of 10 compounds randomly chosen from 50 compounds. The squared regression coefficients of prediction for the MLR, PLS and ANN models for DB-5 column were 0.9645, 0.9606 and 0.9808, respectively and also for DB-17 column were 0.9757, 0.9757 and 0.9875, respectively. Result obtained showed that non-linear model can simulate the relationship between structural descriptors and the retention times of the molecules in data sets accurately.

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