PMID- 27544797 OWN - NLM STAT- PubMed-not-MEDLINE DCOM- 20180307 LR - 20180307 IS - 1873-2828 (Electronic) IS - 1350-4177 (Linking) VI - 38 DP - 2017 Sep TI - Ultrasound assisted extraction of Maxilon Red GRL dye from water samples using cobalt ferrite nanoparticles loaded on activated carbon as sorbent: Optimization and modeling. PG - 672-680 LID - S1350-4177(16)30282-6 [pii] LID - 10.1016/j.ultsonch.2016.08.012 [doi] AB - In this research, a selective, simple and rapid ultrasound assisted dispersive solid-phase micro-microextraction (UA-DSPME) was developed using cobalt ferrite nanoparticles loaded on activated carbon (CoFe(2)O(4)-NPs-AC) as an efficient sorbent for the preconcentration and determination of Maxilon Red GRL (MR-GRL) dye. The properties of sorbent are characterized by X-ray diffraction (XRD), Transmission Electron Microscopy (TEM), Vibrating sample magnetometers (VSM), Fourier transform infrared spectroscopy (FTIR), Particle size distribution (PSD) and Scanning Electron Microscope (SEM) techniques. The factors affecting on the determination of MR-GRL dye were investigated and optimized by central composite design (CCD) and artificial neural networks based on genetic algorithm (ANN-GA). CCD and ANN-GA were used for optimization. Using ANN-GA, optimum conditions were set at 6.70, 1.2mg, 5.5min and 174muL for pH, sorbent amount, sonication time and volume of eluent, respectively. Under the optimized conditions obtained from ANN-GA, the method exhibited a linear dynamic range of 30-3000ngmL(-1) with a detection limit of 5.70ngmL(-1). The preconcentration factor and enrichment factor were 57.47 and 93.54, respectively with relative standard deviations (RSDs) less than 4.0% (N=6). The interference effect of some ions and dyes was also investigated and the results show a good selectivity for this method. Finally, the method was successfully applied to the preconcentration and determination of Maxilon Red GRL in water and wastewater samples. CI - Copyright (c) 2016 Elsevier B.V. All rights reserved. FAU - Mehrabi, Fatemeh AU - Mehrabi F AD - Chemistry Department, Gachsaran Branch, Islamic Azad University, Gachsaran 75818-63876, Iran. FAU - Vafaei, Azam AU - Vafaei A AD - Chemistry Department, Gachsaran Branch, Islamic Azad University, Gachsaran 75818-63876, Iran. Electronic address: a.vafaei11@yahoo.com. FAU - Ghaedi, Mehrorang AU - Ghaedi M AD - Chemistry Department, Yasouj University, Yasouj 75914-35, Iran. Electronic address: m_ghaedi@mail.yu.ac.ir. FAU - Ghaedi, Abdol Mohammad AU - Ghaedi AM AD - Chemistry Department, Gachsaran Branch, Islamic Azad University, Gachsaran 75818-63876, Iran. FAU - Alipanahpour Dil, Ebrahim AU - Alipanahpour Dil E AD - Chemistry Department, Yasouj University, Yasouj 75914-35, Iran. FAU - Asfaram, Arash AU - Asfaram A AD - Chemistry Department, Yasouj University, Yasouj 75914-35, Iran. LA - eng PT - Journal Article DEP - 20160810 PL - Netherlands TA - Ultrason Sonochem JT - Ultrasonics sonochemistry JID - 9433356 OTO - NOTNLM OT - Artificial neural network-genetic algorithm OT - Central composite design OT - CoFe(2)O(4)-NPs-AC OT - Determination OT - Maxilon Red GRL OT - Ultrasound assisted EDAT- 2016/08/22 06:00 MHDA- 2016/08/22 06:01 CRDT- 2016/08/22 06:00 PHST- 2016/04/13 00:00 [received] PHST- 2016/08/09 00:00 [revised] PHST- 2016/08/10 00:00 [accepted] PHST- 2016/08/22 06:00 [pubmed] PHST- 2016/08/22 06:01 [medline] PHST- 2016/08/22 06:00 [entrez] AID - S1350-4177(16)30282-6 [pii] AID - 10.1016/j.ultsonch.2016.08.012 [doi] PST - ppublish SO - Ultrason Sonochem. 2017 Sep;38:672-680. doi: 10.1016/j.ultsonch.2016.08.012. Epub 2016 Aug 10.