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Mostafa Khajeh,Kamran Dastafkan 한국공업화학회 2014 Journal of Industrial and Engineering Chemistry Vol.20 No.5
In this study, a simple and fast method for preconcentration and determination of trace amount of molybdenum from water samples was developed by silver nanoparticles based solid-phase extraction method and UV–vis spectrophotometry. Hybrid of artificial neural network–particle swarm optimization (ANN–PSO) has been used to develop predictive models for simulation and optimization of solid phase extraction method. Under the optimum conditions, the detection limit and relative standard deviation were 11 mg L-1 and <3.9%, respectively. The pre-concentration factor of this method was 50. The method was applied to preconcentration and determination of molybdenum from water samples.
Mostafa Khajeh,Sheida Hezaryan 한국공업화학회 2013 Journal of Industrial and Engineering Chemistry Vol.19 No.6
In this study, modeling based on ant-colony optimization – artificial neural network have been employed to develop the model for simulation and optimization of nanometer SiO2 for the extraction of manganese and cobalt from water samples. The pH, time, amount of SiO2 nanoparticles and concentration of 1-(2-pyridylazo)-2-naphthol (PAN) were the input variables, while the extraction% of analytes was the output. Under the optimum conditions, the detection limits were 0.52 and 0.7 mg L1,for manganese and cobalt, respectively. The method was applied to the extraction of manganese and cobalt from water samples and one certified reference material.
Mostafa Khajeh,Massoud Kaykhaii,Arezoo Sharafi 한국공업화학회 2013 Journal of Industrial and Engineering Chemistry Vol.19 No.5
In this study, a simple and fast method for preconcentration and determination of trace amount of methylene blue (MB) from water samples was developed by silver nanoparticles based solid-phase extraction method and UV–Vis spectrophotometry. Response surface methodology and hybrid of artificial neural network- particle swarm optimization (ANN-PSO) have been used to develop predictive models for simulation and optimization of solid phase extraction method. Under the optimum conditions, the detection limit and relative standard deviation were 15.0 mg L-1 and <2.7%, respectively. The preconcentration factor was 83. The method was applied to preconcentration and determination of methylene blue from water samples.
Asma Amini,Mostafa Khajeh,Ali Reza Oveisi,Saba Daliran,Mansour Ghaffari-Moghaddam,Hojat Samareh Delarami 한국공업화학회 2021 Journal of Industrial and Engineering Chemistry Vol.93 No.-
A novel adsorbent, GO/Fe3O4/OPO3H2/PCN-222, was successfully synthesized via graphene oxide (GO)modification with magnetic particles, phosphorous-containing groups, and a mesoporous Zr-MOF, PCN-222 (PCN stands for Porous Coordination Network), respectively, to give the nominal composite. The laststep was through a solvent-assisted ligand incorporation technique. Morphological, structural, andphysicochemical properties of the hybrid material was assessed by FT-IR, PXRD, SEM/EDX, BET surfacearea, VSM, TGA/DSC, UV–vis DRS, and ICP-OES analyses. This solid was then used for dispersive solidphase extraction of uranium ions dissolved in water. Several parameters including pH of solution,extraction and desorption times, amount of adsorbent, and type and concentration of elution solventwere investigated and optimized. The maximum adsorption capacity of adsorbent was found to be416.7 mg g 1 (pH, 6.2; amount of adsorbent, 5.0 mg; extraction time, 3.0 min) beyond what wasachievable with the individual components. In addition, various coordination modes between themultifunctional adsorbent and uranyl ions were investigated by DFT calculations in details, revealingsome favorable non-covalent cation–p interaction and strong binding of free-base porphyrin, carboxyland phosphorous-containing groups to the uranium ions. Under optimized conditions, highdetermination coefficient (R2 = 0.9994) was obtained and limit of detection and relative standarddeviation were found 0.9 mg L 1 and 2.7%, respectively
Green synthesis of silver nanoparticles using plant extracts
Mansour Ghaffari-Moghaddam,Robabeh Hadi-Dabanlou,Mostafa Khajeh,Mansoureh Rakhshanipour,Kamyar Shameli 한국화학공학회 2014 Korean Journal of Chemical Engineering Vol.31 No.4
The strategy for design of new nanometals was developed due to their wide applications in many fields. One of the most important nanometals is silver nanoparticles (AgNPs) because of their extensive applications in biotechnologyand biomedical fields. AgNPs were usually synthesized by using chemical and physical methods. In thechemical methods, various toxic chemicals are used, which are harmful to the health of living organisms. Therefore,the AgNPs were synthesized by using biological methods based on green chemistry for reducing the toxic chemicals. There are various resources for green synthesis of AgNPs, such as bacteria, fungi, enzyme and plant extracts. The greensynthesis of AgNPs involves three main steps: the selection of the solvent medium, the selection of environmentallyreducing agents, and the selection of non-toxic substances for the stability of AgNPs. The biosynthesis of AgNPs usingplant extracts is more favorable than other biological methods because of removing the elaborate process of maintainingcell cultures. It can be also suitably scaled up for large scale production of AgNPs. This review focuses on green synthesisof AgNPs using various plant extracts.