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Mohammad Reza Hadjmohammadi

Mohammad Reza Hadjmohammadi

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId:
Faculty: Faculty of Chemistry
Address: Babolsar
Phone: 01135302350

Research

Title
SDS-coated amino-functionalized magnetic iron oxide nanoparticles for the efficient removal and recovery of three organophosphorus pesticides from environmental water and fruit juice samples
Type
Presentation
Keywords
SDS-coated amino-functionalized magnetic iron oxide nanoparticles
Year
2017
Researchers Raheleh Hamedi ، Ali Aghaie ، Mohammad Reza Hadjmohammadi

Abstract

The research presented in this paper investigates removal of three organophosphorus pesticides named Chlorpyrifos, Diazinon and Phosalone by ultrasound assisted dispersive magnetic solid phase extraction (UADM-SPE) and their determination using high-performance liquid chromatography. In recent years, magnetic iron oxide nanoparticles (MIONPs) have been appearing as a new type of important functional SPE materials, but they are very sensitive to oxidation and agglomerations; hence, their surface were coated with several organic [1] and inorganic [2] materials; which not only cause to protection of MIONPs, but also provide a component substrate at the surface of MIONPs for adsorption of analytes. SDS-coated amino-functionalized magnetic iron oxide nanoparticles (AMIONPs) were applied as an efficient adsorbent for both removal and preconcentration of these pesticides. The surface modification of synthesized AMIONP was done by self-assembly of SDS as micelle around AMIONPs in acidic medium and these particles act like a magnetic core micelles. This method (UADM-SPE) consists of two main steps: firstly, pesticides are adsorbed through a series of interactions on the surface of SDS-coated AMIONPs (removal step) and in the second step, the recovery of adsorbed analytes will be performed by desorption of them into a suitable solvent (desorption step). At first; a primary screening step was done through half fractional factorial design (26-1) to indicate which variables and their interactions are significant on the removal of pesticides. Then, response surface methodology based on doehlert design, as a multivariate statistic technique, was applied to optimize the level of effective parameters for improving the removal efficiency. Type and volume of desorption solvent were optimized separately. Under the optimum condition (pH=6.1, the ratio of SDS/AMIONPs=3, sample volume=41 ml, extraction time=3 min, and desorbing solvent=250 ml of methanol), extraction recoveries for 0.2 ng