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Design of Colorimetric Sensor Array for Simultanous Detection of Phosalone and Azinphosmethyl Pesticides Based on Aggregation Silver Nanoparticles (AgNPs)
, M.Sc. Thesis Sharif University of Technology ; Hormozinezhad, Mohammad Reza (Supervisor)
Abstract
Development of simple and rapid approaches for identification of pesticides has been known as a critical demand, due to the broad usage of pesticides and their harmful effects on mammals. Herein, we have introduced a silver nanoparticle (AgNP) based colorimetric sensor array for simultaneous identification of Azinphosmethyl (AM) and Phosalone (PS). In the presence of the target pesticides, unmodified AgNPs at various pHs (4.5, 5.5 and 9.5) showed different aggregation behaviours. As a result of aggregation, the color and UV-Vis spectra of AgNPs changed which led to distinct patterns for AM and PS. The aggregation induced spectral changes of AgNPs were used to identify AM and PS with the help...
Design of a Colorimetric Sensor Array Based on Aggregation of Plasmonic Nanoparticles for Detection and discrimination of Phosalone, Thiometon and Prothioconazole Pesticides
, M.Sc. Thesis Sharif University of Technology ; Hormozi Nezhad, Mohammad Reza (Supervisor) ; Ghasemi, Forough (Co-Supervisor)
Abstract
The use of myriad pesticides in agriculture crops has promoted the demand of developing rapid and sensitive probes for the detection and discrimination of diverse pesticides, which are usually used together. In this work, a colorimetric sensor array has been designed for identification and discrimination of Thiometon (TM) and Phosalone (PS) as organophosphate pesticides and Prothioconazole (PC) as a triazole pesticide. For this purpose, two different plasmonic nanoparticles including unmodified gold nanoparticles (AuNPs) and unmodified silver nanoparticles (AgNPs) were used as sensing elements. The principle of the proposed strategy relied on the aggregation of AuNPs and AgNPs through the...
Simultaneous detection and identification of thiometon, phosalone, and prothioconazole pesticides using a nanoplasmonic sensor array
, Article Food and Chemical Toxicology ; Volume 151 , 2021 ; 02786915 (ISSN) ; Abbasi Moayed, S ; Ghasemi, F ; Mahdavi, V ; Hormozi Nezhad, M. R ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
In this work, a colorimetric sensor array has been designed for the identification and discrimination of thiometon (TM) and phosalone (PS) as organophosphate pesticides and prothioconazole (PC) as a triazole pesticide. For this purpose, two different plasmonic nanoparticles including unmodified gold nanoparticles (AuNPs) and unmodified silver nanoparticles (AgNPs) were used as sensing elements. The principle of the proposed strategy relied on the aggregation AuNPs and AgNPs through the cross-reactive interaction between the target pesticides and plasmonic nanoparticles. Therefore, these aggregation-induced UV–Vis spectra changes were utilized to discriminate the target pesticides with the...
ThThnated Development of a pH assisted AgNP-based colorimetric sensor Array for simultaneous identification of phosalone and azinphosmethyl pesticides
, Article Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy ; Volume 219 , 2019 , Pages 496-503 ; 13861425 (ISSN) ; Abbasi Moayed, S ; Hormozi Nezhad, M. R ; Sharif University of Technology
Elsevier B.V
2019
Abstract
Development of simple and rapid methods for identification of pesticides, due to their broad usage and harmful effects on mammals, has been known as a critical demand. Herein, we have introduced a silver nanoparticle (AgNP)based colorimetric sensor array for simultaneous identification of Azinphosmethyl (AM)and Phosalone (PS)pesticides. In the presence of the target pesticides, unmodified AgNPs at various pHs (4.5, 5.5 and 9.5)showed different aggregation behaviors. As a result of aggregation, the color and UV–Vis spectra of AgNPs changed differentially, leading to distinct response patterns for AM and PS. The aggregation induced spectral changes of AgNPs, were used to identify AM and PS...
A high-throughput approach for the determination of pesticide residues in cucumber samples using solid-phase microextraction on 96-well plate
, Article Analytica Chimica Acta ; Volume 740 , 2012 , Pages 36-42 ; 00032670 (ISSN) ; Es'haghi, A ; Eshaghi, A ; Mesbahi, N ; Sharif University of Technology
Abstract
A high-throughput solid-phase microextraction (SPME) on 96-well plate together with gas chromatography-mass spectrometry (GC-MS) was developed for the determination of some selected pesticides in cucumber samples. Pieces with the length of 1.0cm of silicon tubing were precisely prepared and then coated on the end part of stainless steel wires. The prepared fibers were positioned in a home-made polytetrafluoroethylene (PTFE)-based constructed ninety-six holes block to have the possibility of simultaneous immersion of the SPME fibers into the center of individual wells. Pesticides such as diazinon, penconazol, tebuconazol, bitertanol, malathion, phosalone and chlorpyrifos-methyl were selected...
Preparation and evaluation of various banana-based biochars together with ultra-high performance liquid chromatography-tandem mass spectrometry for determination of diverse pesticides in fruiting vegetables
, Article Food Chemistry ; Volume 360 , 2021 ; 03088146 (ISSN) ; Mahdavi, V ; Roustaei, Z ; Bagheri, H ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
Biomass, originates from plant- or animal-based materials with a huge potential to be reused. Here we report a simple, rapid and inexpensive method for preparation of modified biochars derived from the banana peel followed by their applications in pipette-tip micro solid-phase extraction (PT-µSPE). Due to the contribution of various effective parameters on modification of banana peel biochars (BPBs), Taguchi design was used to optimize activation temperature, activation repetition, treatment material and impregnation ratio. Efficiency of the prepared BPBs were studied by extraction of twelve various pesticides, as model analytes with an extended range of log P values (1.4–5.7), followed by...