Deep eutectic solvent-based ferrofluid for highly efficient preconcentration and determination of metronidazole by vortex-assisted liquid-phase microextraction under experimental design optimization

To determine metronidazole in water samples, we developed an environmentally friendly, efficient, and straightforward ferrofluid-based liquid-liquid microextraction sample pretreatment technique. It is coupled with a high-performance liquid chromatography-ultraviolet analytical technique known for its sensitivity, speed, and precision. The magnetic separation of metronidazole-containing ferrofluid from the matrix was effortlessly achieved through the application of an external magnetic field, eliminating the need for centrifugation. Response surface optimization was employed to systematically determine the key experimental parameters influencing extraction efficiency, including pH, NaCl concentration, ferrofluid volume, and vortex duration. With a low detection limit (0.116 ng mL-1), a broad linear range between 0.5 and 700 ng mL-1 was achieved at optimal conditions. Additionally, acceptable spiking recoveries (94.3-97.3 %) and RSD values (≤3.7 %) for intra- and inter-day precision were attained in water samples. In conclusion, the effectiveness of the vortex and ferrofluid combination, along with the convenience of collection and elimination of the need for centrifugation, bestows a highly valuable technique for determining metronidazole in water samples.

dl-carnitine-based green hydrophobic deep eutectic solvent for the enrichment of bisphenol A in mineral water based on ultrasound-assisted liquid-phase microextraction

A powerful pretreatment technique, ultrasound-assisted dispersive liquid-phase microextraction (USA-DLPME) based on dl-Carnitine-based deep eutectic solvent (DES), has been developed to efficiently enrichment of bisphenol A from mineral water samples. The DES-based USA-DLPME technique demonstrated superior extraction efficiency for bisphenol A compared to established organic solvent-based liquid-liquid extraction techniques. The conditions for the extraction of bisphenol A were predicted using the response surface methodology. The effects of pH (A: 2-10), NaCl concentration (B: 0.2-1.0%w/v), DES volume (C: 30-150 μL), and sonication time (D: 1-5 min) were examined using an experimental design. The extraction recovery of Bisphenol A under optimum conditions was achieved at 99.897% (A = 8, B = 0.4%w/v, C = 120 μL, and D = 5 min). Under these conditions, a wide linear range of 1-600 ng mL-1, an enrichment factor of 81.52, a low detection limit of 0.26 ng mL-1 and a limit of quantification of 0.87 ng mL-1 were obtained. Lastly, the proposed technique was used to accurately and reliably identify bisphenol A in various mineral water samples, yielding relative recoveries in the 92-96% range with RSD≤3%. These findings imply that DESs can be widely and successfully used to extract chemicals from actual materials. DESs are a class of innovative green solvents with the potential to replace organic solvents.

Magnetic nanofluid based on hydrophobic deep eutectic solvent for efficient and rapid enrichment and subsequent determination of cinnamic acid in juice samples: Vortex-assisted liquid-phase microextraction

A quick, environmentally friendly and easy approach for the determination of cinnamic acid in juice samples based on the creation and usage of a novel magnetic nanofluid (mixture of hydrophobic deep eutectic solvent and magnetic nanoparticles) has been reported. Response surface methodology was applied to justify the contribution of the efficient factors including pH, nanofluid volume, ionic strength and vortex time. Cinnamic acid concentrations were monitored and quantified based on their HPLC peak representing linear correlations under the best operational circumstances showing linearity between 3 and 550 ng mL^-1. The LOD, LOQ, and enrichment factor for cinnamic acid were 0.8 ng mL^-1, 2.7 ng mL^-1 and 57.2, respectively. The proposed method was used for enrichment and subsequent determination of cinnamic acid from juice samples which suggests a potential alternative approach for cinnamic acid analysis in complicated food samples.

A new microfluidic-chip device followed by sensitive image analysis of smart phone for simultaneous determination of dyes with different acidic-basic properties

In this study, a new microfluidic-chip coupled with micro solid phase extraction (μ-SPE) and a RGB detection system was designed. The method was used for extraction and simultaneous determination of trace amounts of dyes with different acidic-basic properties. Erythrosine (Ery) and Crystal Violet (CV) were selected as acidic and basic model analytes, respectively. The first step of this method is based on the on-chip electromembrane extraction (CEME) of analytes from aqueous solution. The utilized microfluidic system is a single compartment that composed of three polymethyl metacrylate plates (with sandwiched structures) patterned with palm shaped helix channels. The device consisted one pair of platinum electrodes that were embedded in the acceptor phase channels in each side. The middle part was cut and used as the path of the sample. The extracted analytes by CEME were passed through the micro-packed column containing strong cation and anion exchanger sorbents respectively. Two adsorbents were separated by a polypropylene frit and sealed on each side by two polypropylene frites. Following dye adsorption on the sorbents, the colors that emerged were promptly evaluated using RGB colorimetry on a smartphone. Central composite design was used to analyze and optimize the effective parameters on extraction efficiency. The relative standard deviations (RSDs%) based on five replicate measurements were less than 7.8% for RGB and 8.6% for the spectrophotometry technique under ideal conditions. Image analysis using a smartphone yielded LOD values of 15.0 and 10.5 μg L^-1 for Ery and CV, respectively. The CEME- μ-SPE -RGB approach produced findings that were equivalent to those obtained by spectrophotometry. Finally, the approach was used to accurately determine Ery and CV in water samples, yielding good relative recoveries (recovery ≥94.0).

Highly selective magnetic dual template molecularly imprinted polymer for simultaneous enrichment of sulfadiazine and sulfathiazole from milk samples based on syringe-to-syringe magnetic solid-phase microextraction

Antibiotics, such as sulfadiazine and sulfathiazole, are widely used in veterinary applications which can result in remains in edible animal products. Therefore, there is an immense need for a reliable, selective, sensitive, and simple analytical technique for monitoring the concentration of sulfadiazine (SDZ) and sulfathiazole (STZ) in edible animal products. In this regard, we developed a magnetic dual template molecularly imprinted polymer (MMIP) to determine the SDZ and STZ in milk samples. For the sensitive and selective extraction and determination of target analytes, MMIPs have been combined with the syringe-to-syringe magnetic solid-phase microextraction (SS-MSPME) method. In addition, we used central composite design (CCD) for the extraction of SDZ and STZ. With optimum conditions, an efficient, rapid, and convenient technique for the preconcentration and determination of SDZ and STZ in milk samples by SS-MSPME coupling with HPLC-UV was developed. Using our combined approach, the limits of detection are 0.9 and 1.3 ng mL^-1 for SDZ and STZ, respectively, along with good linearity and determination coefficients higher than 0.98. Our method demonstrates a practical approach for the deduction of antibiotics in milk samples with high recoveries and selectivity.

A new approach for microextraction of trace albendazole sulfoxide drug from the samples of human plasma and urine, and water by the molecularly imprinted polymer nanoparticles combined with HPLC

In this research study, a method of dispersive-micro-solid phase extraction (D-µ-SPE) combined with molecularly imprinted polymer nanoparticles (MIP-NPs) with HPLC-UV was developed for the fast and selective detection of the trace amount of albendazole sulfoxide (ABZSO) in the biological samples. To investigate the effective factors on ABZSO microextraction by the method, central composite design (CCD) was utilized, and the optimum conditions for ABZSO microextraction were sample pH of 8.0, MIP-mass of 15 mg, sonication time of 12 min, and eluent (methanol) volume of 0.25 mL. Under the obtained optimal extraction conditions, the value for the limit of detection (LOD) and limit of quantification (LOQ) was respectively showed to be 0.074 and 0.246 ng mL^-1. In addition, the calculated peak areas exhibited a linear relationship with the ABZSO concentration ranging from 0.4 to 4200 ng mL^-1. The analyses of the samples including human plasma and urine, and water were successfully performed by the usage of the D-µ-SPE method, which was a simple and sensitive technique and a suitable alternative for the analysis of ABZSO. In the analysis of ABZSO in various samples, the recoveries at various levels of ABZSO concentrations (50, 300, and 500 ng mL^-1) were in the range of 95.7-103.0 %, and the relative standard deviations (RSDs; n = 3) varied from 2.2 to 4.4%.

Biocompatible chitosan-zinc oxide nanocomposite based dispersive micro-solid phase extraction coupled with HPLC-UV for the determination of rosmarinic acid in the extracts of medical plants and water sample

In the present research, a procedure was described for the recovery of rosmarinic acid (RA) from medical extract samples using chitosan‑zinc oxide nanoparticles as a biocompatible nanocomposite (CS-ZnO-NC). The dispersive micro-solid phase extraction (D-μ-SPE) of RA from the medical extract samples was investigated by using the prepared biocompatible composite as a solid phase. The HPLC-UV method was used for measuring the extracted RA. The important variables (pH, biocompatible composite mass, contact time, and volume of eluent) associated with the extraction process were analyzed by the application of central composite design (CCD). The achieved optimum values for the mentioned variables were 7.0, 10 mg, 4 min, and 180 μL, respectively. The extraction recovery (99.68%) obtained from the predicted model was in agreement with the experimental data (98.22 ± 1.33%). In addition, under the obtained optimum conditions and over the concentration in the range of 2-3500 ng mL-1, a linear calibration curve was obtained with R2 > 0.993. The limit of detection (LOD) and quantification (LOQ) values were computed, and the obtained ranges were respectively from 0.060 to 0.089 ng mL-1 and 0.201 to 0.297 ng mL-1. In addition, the enrichment factors were obtained in the range of 93.7-110.5 with preconcentration factor of 83.3. Therefore, the D-μ-SPE-HPLC-UV method could be used for analyzing RA in the samples of the extracts obtained from the medical plants and water with the recovery values of the analyte in the range of 96.6%-105.4% and the precision with relative standard deviation <5.7%.

Magnetic dual-template molecularly imprinted polymer based on syringe-to-syringe magnetic solid-phase microextraction for selective enrichment of p-Coumaric acid and ferulic acid from pomegranate, grape, and orange samples

Magnetic dual-template molecularly imprinted polymer (Fe3O4@SiO2-MDMIP) was prepared to enrich and determine both p-Coumaric acid (p-CA) and ferulic acid (FA) based on syringe-to-syringe magnetic solid-phase microextraction (SS-MSPME). The obtained MDMIP was characterized and recognized, and then its adsorbing performance was studied. Based on the results, the Fe3O4@SiO2-MDMIP indicated selective recognition towards p-CA and FA with large adsorption capacity. The optimization of MDMIP-SS-MSPME conditions (pH, Fe3O4@SiO2-MDMIP mass, NaCl concentration, number of cycle, and elution volume) were conducted using the central composite design (CCD). Under the optimum conditions, an effectual and a convenient method was established to determine p-CA and FA in pomegranate, grapes, and orange samples based on SS-MSPME coupling with high-performance liquid chromatography-ultraviolet (HPLC-UV). Our developed method showed the limit of detection (LOD) of 0.08 ng mL-1 for p-CA and 0.07 ng mL-1 for FA. The method also indicated good linearity with R2 > 0.99 and good recoveries of 85.12-94.96% with RSDs ≤ 5.58% spiked at three various concentration levels in pomegranate, grapes, and orange samples.

Synthesis and application of Ce-doped TiO2 nanoparticles loaded on activated carbon for ultrasound-assisted adsorption of Basic Red 46 dye

Ce was doped on TiO₂ nanoparticles (NPs), and this association was loaded on activated carbon (Ce-TiO₂-NPs-AC). The characterization was completed by FE-SEM, TEM, and XRD, and finally these NPs were used for the ultrasonic-assisted adsorption of Basic Red 46 (BR 46) from aqueous solution. An experimental model suggested by the central composite design (CCD)-as a branch of response surface methodology (RSM)-provides insight into the influence of variables, such as BR 46 concentration, pH, adsorbent mass, and sonication time, on BR 46 removal. Experimental results revealed that setting conditions at 25 mg L^-1 of BR 46, pH 5.0, 0.02 g of Ce-TiO₂-NPs-AC and 4 min sonication resulted in a high coefficient of determination (R² > 0.99) and low probability values. The difference in the values is likely due to the accumulation of more than 99% of BR 46, while equilibrium data described by Langmuir isotherm model with a high adsorption capacity of 58.61 mg g^-1 and adsorption process were successfully correlated with pseudo-second-order kinetics model.

Dispersive micro-solid phase extraction based on Fe3O4@SiO2@Ti-MOF as a magnetic nanocomposite sorbent for the trace analysis of caffeic acid in the medical extracts of plants and water samples prior to HPLC-UV analysis

In this work, Fe₃O₄@SiO₂@Ti-MOF-NCs, as an efficient sorbent, have been synthesized in a laboratory and utilized for extracting CA in the medical extracts of plants and water samples before their analysis by HPLC.

Magnetic dispersive micro-solid phase extraction with the CuO/ZnO@Fe3O4-CNTs nanocomposite sorbent for the rapid pre-concentration of chlorogenic acid in the medical extract of plants, food, and water samples

CuO/ZnO@Fe₃O₄-CNTs-NC was synthesized and used as a sorbent in a MDMSPE method for the determination of chlorogenic acid in the medical extract of plants, food, and water samples.

Ultrasound wave assisted adsorption of congo red using gold-magnetic nanocomposite loaded on activated carbon: Optimization of process parameters

In this study, gold-magnetic nanocomposite in the presence of ultrasound wave assisted was synthesized and loaded on activated carbon (Au-Fe₃O₄-NCs-AC) by simple, fast and low-cost process. This novel material was applied for ultrasound assisted adsorption of congo red (CR) as model of toxic and even carcinogenic substance from aqueous solution. The detail of morphology and identity of Au-Fe₃O₄-AC was characterized by SEM and TEM techniques and correlation among response to variables such as pH (2-10), adsorbent mass (0.005-0.025 g), initial CR concentration (10-30 mg L^-1) and ultrasound time (2-6 min) was investigated by response surface methodology (RSM) under central composite design (CCD). Analysis of variance (ANOVA) exhibit a high R² value of 0.999 and confirm suitability of constructed second-order regression model for excellent evaluation and prediction of the experimental data. The interaction and main factor and optimum conditions of the under study process were determined from response surface plots based on desirability function. The maximum CR adsorption were achieved at pH of 4, 15 mg L^-1 of CR, 0.017 g of Au-Fe₃O₄-AC and 5 min sonication which owing to 99.49% removal efficiency is highly recommended for future CR removal from different matrixes. Adsorption kinetic follow second-order rate expression in combination to inter particle diffusion and equilibrium adsorption data best represented by the Langmuir isotherm with maximum mono-layer adsorption capacity of 43.88 mg g^-1.

Optimization of process parameters for determination of trace Hazardous dyes from industrial wastewaters based on nanostructures materials under ultrasound energy

In this study, ultrasound-assisted dispersive solid phase micro-extraction based on nanosorbent namely silver-zinc oxide nanoparticles loaded on activated carbon (Ag-ZnO-NP-AC) combined with derivative spectrophotometry method for the simultaneous pre-concentration and determination of Methyl Green (MG) and Rose Bengal (RB) dyes in water and industrial wastewater. Characterized sorbent by field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDX), particle-size distribution (PSD), Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD) and Transmission electron microscopy (TEM) analysis with superior adsorption capacity was applied in ultrasound assisted dispersive-solid-phase micro-extraction (UA-DSPME) methodology. pH, sorbent mass, ultrasonication time, and eluent volume influence and contribution on response correspond to simultaneous pre-concentration and determination of MG and RB were optimized by response surface methodology (RSM) and results were compared with the experimental values. Under the optimal conditions (UA-DSPME), the enrichment factors (EFs) were 93.89 and 97.33 for the MG and RB dyes, respectively. The limits of detection were 2.14 and 2.73ngmL^-1 and the limit of quantification were 7.15 and 9.09ngmL^-1 for MG and RB, respectively. The analytes can be determined over 10-2000ngmL^-1 with recoveries between 90.8% to 97.7% and RSDs less than 3.6%. The developed method due to simplicity and rapidity is able successful for repeatable and accurate monitoring of under study analytes from complicated matrices.

Comparison between dispersive solid-phase and dispersive liquid-liquid microextraction combined with spectrophotometric determination of malachite green in water samples based on ultrasound-assisted and preconcentration under multi-variable experimental design optimization

The ultrasound-assisted dispersive solid-phase microextraction (USA-DSPME) and the ultrasound-assisted dispersive liquid-liquid microextraction (USA-DLLME) developed for as an ultra preconcentration and/or technique for the determination of malachite green (MG) in water samples. Central composite design based on analysis of variance and desirability function guide finding best operational conditions and represent dependency of response to variables viz. volume of extraction, eluent and disperser solvent, pH, adsorbent mass and ultrasonication time has significant influence on methods efficiency. Optimum conditions was set for USA-DSPME as: 1mg CNTs/Zn:ZnO@Ni₂P-NCs; 4min sonication time and 130μL eluent at pH 6.0. Meanwhile optimum point for USA-DLLME conditions were fixed at pH 6.0; 4min sonication time and 130, 650μL and 10mL of extraction solvent (CHCl₃), disperser solvent (ethanol) and sample volume, respectively. Under the above specified best operational conditions, the enrichment factors for the USA-DSPME and USA-DLLME were 88.89 and 147.30, respectively. The methods has linear response in the range of 20.0 to 4000.0ngmL^-1 with the correlation coefficients (r) between 0.9980 to 0.9995, while its reasonable detection limits viz. 1.386 to 2.348ngmL^-1 and good relative standard deviations varied from 1.1% to 2.8% (n=10) candidate this method for successful monitoring of analyte from various media. The relative recoveries of the MG dye from water samples at spiking level of 500ngmL^-1 were in the range between 94.50% and 98.86%. The proposed methods has been successfully applied to the analysis of the MG dye in water samples, and a satisfactory result was obtained.

Ultrasound assisted extraction of Maxilon Red GRL dye from water samples using cobalt ferrite nanoparticles loaded on activated carbon as sorbent: Optimization and modeling

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 (CoFe₂O₄-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 174μL 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.

Investigate the ultrasound energy assisted adsorption mechanism of nickel(II) ions onto modified magnetic cobalt ferrite nanoparticles: Multivariate optimization

In present study, magnetic cobalt ferrite nanoparticles modified with (E)-N-(2-nitrobenzylidene)-2-(2-(2-nitrophenyl)imidazolidine-1-yl) ethaneamine (CoFe₂O₄-NPs-NBNPIEA) was synthesized and applied as novel adsorbent for ultrasound energy assisted adsorption of nickel(II) ions (Ni²⁺) from aqueous solution. The prepared adsorbent characterized by Fourier transforms infrared spectroscopy (FT-IR), transmission electron microscope (TEM), vibrating sample magnetometer (VSM) and X-ray diffraction (XRD). The dependency of adsorption percentage to variables such as pH, initial Ni²⁺ ions concentration, adsorbent mass and ultrasound time were studied with response surface methodology (RSM) by considering the desirable functions. The quadratic model between the dependent and independent variables was built. The proposed method showed good agreement between the experimental data and predictive value, and it has been successfully employed to adsorption of Ni²⁺ ions from aqueous solution. Subsequently, the experimental equilibrium data at different concentration of Ni²⁺ ions and 10mg amount of adsorbent mass was fitted to conventional isotherm models like Langmuir, Freundlich, Tempkin, Dubinin-Radushkevich and it was revealed that the Langmuir is best model for explanation of behavior of experimental data. In addition, conventional kinetic models such as pseudo-first and second-order, Elovich and intraparticle diffusion were applied and it was seen that pseudo-second-order equation is suitable to fit the experimental data.

Multi-responses optimization of simultaneous biosorption of cationic dyes by live yeast Yarrowia lipolytica 70562 from binary solution: Application of first order derivative spectrophotometry

Present study is based on application of live yeast Yarrowia lipolytica 70562 as new biosorbent was investigated for the simultaneous biosorption of Crystal Violet (CV) and Brilliant Green (BG) from wastewater. The effect of operating parameters such as initial dye concentrations (6-14mgL^-1), solution pH (4.0-8.0) and contact time (4-20h) was investigated by response surface methodology (RSM) for modeling and optimization of biosorption process and accordingly the best operational conditions was set as: initial CV and BG concentration of 8.0, and 10mgL^-1, pH of 7.0 and contact time of 16h. Above specified conditions lead to achievement of maximum biosorption of 98.823% and 99.927% for CV and BG dyes, respectively. The experimental equilibrium data well explained according to Langmuir isotherm model with maximum biosorption capacity of 65.359 and 56.497mgg^-1 for BG and CV, respectively. The second order and intraparticle diffusion models as cooperative mechanism has high efficiency and performance for interpretation of real data.

Application of modificated magnetic nanomaterial for optimization of ultrasound-enhanced removal of Pb2+ ions from aqueous solution under experimental design: Investigation of kinetic and isotherm

Magnetic γ-Fe₂O₃ nanoparticles modificated by bis(5-bromosalicylidene)-1,3-propandiamine (M-γ-Fe₂O₃-NPs-BBSPN) and characterized by field emission scanning electron microscopy (FE-SEM), Fourier transforms infrared spectroscopy (FT-IR) and X-ray diffraction (XRD). This modified compound as novel adsorbent was applied for the ultrasound-assisted removal of Pb²⁺ ion in combination with flame atomic absorption spectroscopy (FAAS). The influences of the effective parameters including initial Pb²⁺ ion concentration, pH, adsorbent mass and ultrasound time were optimized by central composite design (CCD). Maximum removal percentage of Pb²⁺ ion which obtained at 25mgL^-1 of Pb²⁺, 25mg of adsorbent and 4min mixing with sonication at pH 6.0. The precision of the equation obtained by CCD was confirmed by the analysis of variance and calculation of correlation coefficient relating the predicted and the experimental values of removal percentage of Pb²⁺ ion. The kinetic and isotherm of ultrasound-assisted removal of Pb²⁺ ion was well described by second-order kinetic and Langmuir isotherm model with maximum adsorption capacity of 163.57mgg^-1.

The performance of nanorods material as adsorbent for removal of azo dyes and heavy metal ions: Application of ultrasound wave, optimization and modeling

The present research is focused on the synthesis and characterization of zinc (II) oxide nanorods loaded on activated carbon (ZnO-NRs-AC) to prepare an outstanding adsorbent for the simultaneous adsorption of heavy metals and dyes as hazardous pollutant using ultrasound energy. The adsorbent was identified by Scanning Electron Microscope (SEM), Transmission Electron Microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD) analysis. The individual effects and possible interactions between the most effective variables including initial metal ions (Cd²⁺ and Co²⁺) and azo dyes (methylene blue (MB) and crystal violet (CV)) concentration, adsorbent dosage and ultrasonic time on the responses were investigated by response surface methodology (RSM) and optimum conditions was fixed at Cd²⁺, Co²⁺, MB and CV concentrations were 25, 24, 18 and 14mgL^-1, respectively, 0.025g of ZnO-NRs-AC and 5.1min sonication to achieve maximum removal percentage (>97.0%) for targets compounds. The artificial neural network (ANN) model was applied for prediction of data with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) in the hidden layer with 14 neurons. The minimum mean squared error (MSE) of 0.9646, 0.0402 and 0.0753 with high determination coefficient (R²) of 0.9996, 0.9991 and 0.9999 for train, test and validation, respectively, were able to predict and model the adsorption process. The results of examination of the time on experimental adsorption data and their subsequent fitting reveal applicability of pseudo-second-order and intraparticle diffusion model. The experimental equilibrium data was analyzed by Langmuir, Freundlich, Temkin and D-R isotherm models and explored that the data well presented by Langmuir model with maximum adsorption capacity of 97.1, 92.6, 83.9 and 81.6mgg^-1 for Cd⁺², Co⁺² ions, MB and CV dyes, respectively.

Screening and optimization of highly effective ultrasound-assisted simultaneous adsorption of cationic dyes onto Mn-doped Fe3O4-nanoparticle-loaded activated carbon

The ultrasound-assisted simultaneous adsorption of brilliant green (BG) and malachite green (MG) onto Mn-doped Fe₃O₄ nanoparticle-loaded activated carbon (Mn-Fe₃O₄-NP-AC) as a novel adsorbent was investigated and analyzed using first derivative spectrophotometry. The adsorbent was characterized using FT-IR, FE-SEM, EDX and XRD. Plackett-Burman design was applied to reduce the total number of experiments and to optimize the ultrasound-assisted simultaneous adsorption procedure, where pH, adsorbent mass and sonication time (among six tested variables) were identified as the most significant factors. The effects of significant variables were further evaluated by a central composite design under response surface methodology. The significance of independent variables and their interactions was investigated by means of the analysis of variance (ANOVA) within 95% confidence level together with Pareto chart. Using this statistical tool, the optimized ultrasound-assisted simultaneous removal of basic dyes was obtained at 7.0, 0.02g, 3min for pH, adsorbent mass, and ultrasonication time, respectively. The maximum values of BG and MG uptake under these experimental conditions were found to be 99.50 and 99.00%, respectively. The adsorption process was found to be followed by the Langmuir isotherm and pseudo-second order model using equilibrium and kinetic studies, respectively. According to Langmuir isotherm model, the maximum adsorption capacities of the adsorbent were obtained to be 101.215 and 87.566mgg^-1 for MG and BG, respectively. The value of apparent energy of adsorption obtained from non-linear Dubinin-Radushkevich model (4.348 and 4.337kJmol^-1 for MG and BG, respectively) suggested the physical adsorption of the dyes. The studies on the well regenerability of the adsorbent in addition to its high adsorption capacity make it promising for such adsorption applications.

Optimization and modeling of preconcentration and determination of dyes based on ultrasound assisted-dispersive liquid-liquid microextraction coupled with derivative spectrophotometry

Present study is based on describing an ultrasound-assisted dispersive liquid-liquid microextraction coupled with derivative spectrophotometry (UAS-DLLME-UV-vis) as useful technique for selective determination of crystal violet (CV) and azure b (Az-B). The significant factors like pH, extractor volume, disperser value and extraction time contribution and their numerical coefficient in quadratic model were calculated according to central composite design (CCD). According to desirability function (DF) as good criterion the best experimental conditions was adjusted and selected at pH of 7.0, 170μL of chloroform, 800μL of ethanol that strongly mixed with the aqueous phase via 4min sonication. Additionally, under study system was modeled by trained artificial neural networks (ANNs) as fitness function with acceptable error of MSE 2.97×10^-06 and 1.15×10^-05 with R²: 0.9999 and 0.9997 for CV and Az-B, respectively. The optimum conditions by using genetic algorithm (GA) method was pH of 6.3, 160μL of chloroform, 740μL of ethanol and 4.5min sonication. Under above specified and optimize conditions, the predicted extraction percentage were 99.80 and 102.20% for CV and Az-B, respectively. The present UAS-DLLME-UV-vis procedure has minimum interference from other substances assign to the matrix, which candidate this method as good alternative to quantify under study dyes content with recoveries in the range of 86-100% for dyes. The detection limits were 2.043ngmL^-1 and 1.72ngmL^-1, and limits of quantitation were 6.81ngmL^-1 and 5.727ngmL^-1 for CV and Az-B, respectively. The proposed methodology was successfully applied for quantification of under study analytes at different media.

Preparation of nanomaterials for the ultrasound-enhanced removal of Pb2+ ions and malachite green dye: Chemometric optimization and modeling

Copper oxide nanoparticle-loaded activated carbon (CuO-NP-AC) was synthesized and characterized using different techniques such as FE-SEM, XRD and FT-IR. It was successfully applied for the ultrasound-assisted simultaneous removal of Pb²⁺ ions and malachite green (MG) dye in binary system from aqueous solution. The effect of important parameters was modeled and optimized by artificial neural network (ANN) and response surface methodology (RSM). Maximum simultaneous removal percentages (>99.0%) were found at 25mgL^-1, 20mgL^-1, 0.02g, 5min and 6.0 corresponding to initial Pb²⁺ concentration, initial MG concentration, CuO-NP-AC amount, ultrasonication time and pH, respectively. The precision of the equation obtained by RSM was confirmed by the analysis of variance and calculation of correlation coefficient relating the predicted and the experimental values of ultrasound-assisted simultaneous removal of the analytes. A good agreement between experimental and predicted values was observed. A feed-forward neural network with a topology optimized by response surface methodology was successfully applied for the prediction of ultrasound-assisted simultaneous removal of Pb²⁺ ions and MG dye in binary system by CuO-NPs-AC. The number of hidden neurons, MSE, R², number of epochs and error histogram were chosen for ANN modeling. Then, Langmuir, Freundlich, Temkin and D-R isothermal models were applied for fitting the experimental data. It was found that the Langmuir model well describes the isotherm data with a maximum adsorption capacity of 98.328 and 87.719mgg^-1 for Pb²⁺ and MG, respectively. Kinetic studies at optimum condition showed that maximum Pb²⁺ and MG adsorption is achieved within 5min of the start of most experiments. The combination of pseudo-second-order rate equation and intraparticle diffusion model was applicable to explain the experimental data of ultrasound-assisted simultaneous removal of Pb²⁺ and MG at optimum condition obtained from RSM.

Trace determination of safranin O dye using ultrasound assisted dispersive solid-phase micro extraction: Artificial neural network-genetic algorithm and response surface methodology

In this study, ultrasound assisted dispersive solid-phase micro extraction combined with spectrophotometry (USA-DSPME-UV) method based on activated carbon modified with Fe2O3 nanoparticles (Fe2O3-NPs-AC) was developed for pre-concentration and determination of safranin O (SO). It is known that the efficiency of USA-DSPME-UV method may be affected by pH, amount of adsorbent, ultrasound time and eluent volume and the extent and magnitude of their contribution on response (in term of main and interaction part) was studied by using central composite design (CCD) and artificial neural network-genetic algorithms (ANN-GA). Accordingly by adjustment of experimental conditions suggested by ANN-GA at pH 6.5, 1.1mg of adsorbent, 10min ultrasound and 150μL of eluent volume led to achievement of best operation performance like low LOD (6.3ngmL(-1)) and LOQ (17.5ngmL(-1)) in the range of 25-3500ngmL(-1). In following stage, the SO content in real water and wastewater samples with recoveries between 93.27-99.41% with RSD lower than 3% was successfully determined.

Modeling and optimization of Hg2+ ion biosorption by live yeast Yarrowia lipolytica 70562 from aqueous solutions under artificial neural network-genetic algorithm and response surface methodology: kinetic and equilibrium study

This study was devoted to the investigation of Hg²⁺ ion biosorption by a live yeast organism, namely, Yarrowia lipolytica 70562 (supplied commercially), which was sufficiently identified and studied by SEM-EDS and FT-IR methods.

Synthesis and characterization of ZnO-nanorods loaded onto activated carbon and its application for efficient solid phase extraction and determination of BG from water samples by micro-volume spectrophotometry

The applicability of ZnO-nanorods loaded onto activated carbon (ZnO-NRs-AC) for the dispersive solid phase microextraction (DSPME) of brilliant green (BG) from water samples has been described.