2024 : 4 : 14
Mohammad Yaser Masoomi

Mohammad Yaser Masoomi

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0003-1329-5947
Education: PhD.
ScopusId: 36927960900
Faculty: Science
Address: Arak University
Phone:

Research

Title
Magnetic metal-organic frameworks for the extraction of trace amounts of heavy metal ions prior to their determination by ICP-AES
Type
JournalPaper
Keywords
Preconcentration, Magnetic MOF, Tem, PXRD, BRANN modeling, MSPE, Cu(II), Pb(II), Cd(II), Cr(III)
Year
2017
Journal MICROCHIMICA ACTA
DOI
Researchers Meysam Safari ، Yadollah Yamini ، Mohammad Yaser Masoomi ، Ali morsali ، Ahmad many

Abstract

The authors describe the preparation of two kinds of metal-organic frameworks (MOFs), referred to as TMU-8 and TMU-9. The MOFs were applied to the preconcentration of the ions Co(II), Cu(II), Pb(II), Cd(II), Ni(II), Cr(III), and Mn(II) from aqueous solutions. The roles of the azine groups in TMU-8 (in comparison to TMU-9 which does not have an azine group) and the role of void spaces of these MOFs toward the adsorption of metal ions also are evaluated. The studies re vea l tha t TM U-8 h as a be tter ads orp tion c ap abil it y tha n TMU-9. A magnetic TMU-8 was then fabricated by in-situ synthesis of a magnetic core-shell nanocomposite. The mate-rial was chosen as an efficient sorbent for the preconcentration of the above metal ions, followed by their determination by flow injection inductively coupled plasma atomic emission spectrometry. The assay was optimized using a combination of central composite design (CCD) and a Bayesian regularized artificial neural network (BRANN) technique. Under optimal conditions, the preconcentration factors are in the range be-tween 66 and 232, and detection limits are as low as 0.3 to 1 μg ⋅L−1. The relative standard deviations are <6.4% (for n =3;at50 μg ⋅ L−1). Real samples were analyzed, and the results demonstrate that suc h co r e- she l l m ag netic micr o-spheres are promising sorbents for rapid and efficient extrac-tion of heavy metal ions from complex samples.