Application of response surface methodology for silver nanoparticle stir bar sorptive extraction of heavy metals from drinking water samples: a Box–Behnken design

Hashemi, Sayyed Hossein; Kaykhaii, Massoud; Keikha, Ahmad Jamali; Sajjadi, Zahra; Mirmoghaddam, Majid

doi:10.1039/c9an00165d

Cited by 39 publications

(9 citation statements)

References 46 publications

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“…Each variable ( Table 2) varied over a concentration range expressed in relation to MS medium (1× = MS concentration). After selection of independent variables and their ranges, the experiments were established based on a BBD with six factors at three levels and each independent variable was coded at three levels between +1, 0 and −1 corresponding to the low, mid and high levels (Table 3) [61]. The actual values and observed results for the three levels of the factors studied are presented in S1 and S2 Tables.…”

Section: Box-behnken Design As An Invaluable Tool For Optimization Ofmentioning

confidence: 99%

High throughput mathematical modeling and multi-objective evolutionary algorithms for plant tissue culture media formulation: Case study of pear rootstocks

et al. 2020

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Simplified prediction of the interactions of plant tissue culture media components is of critical importance to efficient development and optimization of new media. We applied two algorithms, gene expression programming (GEP) and M5’ model tree, to predict the effects of media components on in vitro proliferation rate (PR), shoot length (SL), shoot tip necrosis (STN), vitrification (Vitri) and quality index (QI) in pear rootstocks (Pyrodwarf and OHF 69). In order to optimize the selected prediction models, as well as achieving a precise multi-optimization method, multi-objective evolutionary optimization algorithms using genetic algorithm (GA) and particle swarm optimization (PSO) techniques were compared to the mono-objective GA optimization technique. A Gamma test (GT) was used to find the most important determinant input for optimizing each output factor. GEP had a higher prediction accuracy than M5’ model tree. GT results showed that BA (Γ = 4.0178), Mesos (Γ = 0.5482), Mesos (Γ = 184.0100), Micros (Γ = 136.6100) and Mesos (Γ = 1.1146), for PR, SL, STN, Vitri and QI respectively, were the most important factors in culturing OHF 69, while for Pyrodwarf culture, BA (Γ = 10.2920), Micros (Γ = 0.7874), NH4NO3 (Γ = 166.410), KNO3 (Γ = 168.4400), and Mesos (Γ = 1.4860) were the most important influences on PR, SL, STN, Vitri and QI respectively. The PSO optimized GEP models produced the best outputs for both rootstocks.

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Section: Box-behnken Design As An Invaluable Tool For Optimization Ofmentioning

confidence: 99%

High throughput mathematical modeling and multi-objective evolutionary algorithms for plant tissue culture media formulation: Case study of pear rootstocks

et al. 2020

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“…In Eq. 1 , Y is predicted response, β 0 is the constant, X 1 , X 2 , X 3 and X 4 are the coded independent variables, β i is the linear effect, β ii is the quadratic effect, β ij proved the coefficient of the interaction factor, and e is the random error or allows for description or uncertainties between predicated and achieved data [ 31 ]. Equation 2 shows the mathematical relationship of the analytical signal and four indicated variables.…”

Section: Resultsmentioning

confidence: 99%

Chromium-based metal organic framework for pipette tip micro-solid phase extraction: an effective approach for determination of methyl and propyl parabens in wastewater and shampoo samples

et al. 2021

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Background A chromium-based metal organic framework was synthesized and employed as an efficient sorbent for pipette tip micro-solid phase extraction and preconcentration of parabens from wastewater and shampoo samples up to sub-ppb level before their spectrophotometric analysis. Results Factors affecting preconcentration including volume and type of solvent, amount of sorbent, number of extraction, and volume and pH of samples were optimized employing one-variable-at-a-time and response surface methodology. Obtained analytical characteristics of the method proves its usefulness for analysis of real samples. Linear range of the method for parabens was 1.0–200.0 μg/L. Detection limit of the protocol was 0.24 µg/L for propyl paraben and 0.25 µg/L for methyl paraben. Reproducibility of the protocol defined as % RSD was better than 5.78%. Synthesized adsorbent can be re-used for at least 20 extractions. Conclusion The method showed a good detection limit and precision for determination of methyl- and propyl-paraben in wastewater and shampoo samples.

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“…Accordingly, it is a need to develop a novel, effective, fast, inexpensive, and simple sample preparation technique to isolate analyte components of the samples and preconcentrate them to a detectable limit [11]. Several pretreatment techniques including solid phase extraction (SPE) [12], dispersive solid phase extraction (DSPE) [13], solid phase microextraction (SPME) [14], magnetic solid phase extraction (MSPE) [15], liquid-liquid extraction (LLE) [16,17], molecular imprinted polymer (MIP) [18], stir bar sorptive extraction (SBSE) [19], pipette tip microsolid phase extraction [20], molecularly imprinted stir bar sorptive extraction (MIPSB) [21], microwave-assisted extraction (MASE) [22], membrane extraction [23], solid phase extraction (SPE) [24], supercritical fluid extraction (SFE) [25], and silver nanoparticle stir bar sorptive extraction [26] have been used widespread application for preconcentration and isolate trace level compound of complicated matrices. Before talking in detail about these mainly miniaturized techniques, first some details about the classification of extraction methods are explained.…”

Section: Sample Preparation Techniquesmentioning

confidence: 99%

Modern Sample Preparation Techniques: A Brief Introduction

Sargazi¹,

Hashemi²,

Kaykhaii³

2021

Sample Preparation Techniques for Chemical Analysis

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Due to fast growth in microprocessors, analytical instrumentations in spectroscopy, chromatography, microscopy, sensors and microdevices have been subjected to significant developments. Despite these advances, a sample preparation step is indispensable before instrumental analysis. Main reasons are low sensitivity of the instruments, matrix interferences and incompatibility of the sample with the analytical device. Most of the time spent and most of the errors occurring during a chemical analysis is on sample preparation step. As a result, any improvements in this essential process will have a significant effect on shortening the analysis time and its precision and accuracy and lowering the cost. This introductory chapter intends to draw the readers’ attention to the importance of sample preparation, the procedures of sampling and the source of errors that occur in the course of sampling. The chapter then continues with a heading on sample preparation techniques, including exhaustive and non-exhaustive methods of extraction. Microwave, sonication and membrane-based extraction techniques are more emphasized as exhaustive methods and under a new title, miniaturized methods are discussed. Automation, on-line compatibility and simplification is an important aspect of any sample preparation and extraction which is discussed at the end of this chapter.

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Application of response surface methodology for silver nanoparticle stir bar sorptive extraction of heavy metals from drinking water samples: a Box–Behnken design

Abstract: Silver nanoparticles were coated on a glass stir bar and used for the extraction of heavy metals from water samples after their complexation with ligand PAN, followed by their HPLC determination.

Cited by 39 publications

References 46 publications

High throughput mathematical modeling and multi-objective evolutionary algorithms for plant tissue culture media formulation: Case study of pear rootstocks

High throughput mathematical modeling and multi-objective evolutionary algorithms for plant tissue culture media formulation: Case study of pear rootstocks

Chromium-based metal organic framework for pipette tip micro-solid phase extraction: an effective approach for determination of methyl and propyl parabens in wastewater and shampoo samples

Modern Sample Preparation Techniques: A Brief Introduction

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