Evaluation of trichloroethylene degradation by starch supported Fe/Ni nanoparticles via response surface methodology

2015 ◽  
Vol 73 (4) ◽  
pp. 935-946
Author(s):  
Razieh Nikroo ◽  
Iran Alemzadeh ◽  
Manouchehr Vossoughi ◽  
Kamran Haddadian
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Particle Diameter ◽  
Polynomial Equation ◽  
Soluble Starch ◽  
Water Soluble ◽  
Ni Nanoparticles ◽  
Trichloroethylene Degradation ◽  
Initial Ph ◽  
Rsm Model

In this study, degradation of trichloroethylene (TCE), a chlorinated hydrocarbon, using starch supported Fe/Ni nanoparticles was investigated. The scanning electron microscope images showed applying water soluble starch as a stabilizer for the Fe/Ni nanoparticles tended to reduce agglomeration and discrete particle. Also the mean particle diameter reduced from about 70 nm (unsupported Fe/Ni nanoparticle) to about 30 nm. Effects of three key independent operating parameters including initial TCE concentration (10.0–300.0 mg L−1), initial pH (4.00–10.00) and Fe0 dosage (0.10–2.00) g L−1 on TCE dechlorination efficiency in 1 hour were analysed by employing response surface methodology (RSM). Based on a five-level three-factor central composite design, TCE removal efficiency was examined and optimized. The obtained RSM model fitted the experimental data to a second order polynomial equation. The optimum dechlorination conditions at initial TCE concentration 100.0 mgL−1 were initial pH 5.77, Fe0 dosage 1.67 g L−1. At these conditions TCE removal concentration reached 94.87%, which is in close acceptance with predicted value by the RSM model.

Optimization of the Fermentation Conditions for 1-Deoxynojirimycin Production by Streptomyces lawendulae Applying the Response Surface Methodology

2011 ◽  
Vol 7 (3) ◽  
Author(s):  
Zhao-Jun Wei ◽  
Le-Chun Zhou ◽  
Hua Chen ◽  
Gui-Hai Chen
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Starch Content ◽  
Ultra Violet ◽  
Soluble Starch ◽  
High Yield ◽  
Yield Strain ◽  
Fermentation Time ◽  
Ethyl Sulfate ◽  
Initial Ph

Moranoline (1-Deoxynojirimycin, DNJ) is a piperidine alkaloid, and shows high inhibit activities to glucoamylase and ?-glucosidase. One DNJ high-yield strain of Streptomyces lawendulae was obtained after isolated form soil and mutated with the ultra violet (UV) and ethyl sulfate (DES), which named as TB-412, and can produce DNJ with 35.925 mg/L. Response surface methodology (RSM) was applied to optimize the parameters of DNJ yield from S. lawendulae TB-412. The effects of independent variables of fermentation, including time, temperature, initial pH and the soluble starch content were investigated. The statistical analysis showed that the fermentation time, pH and the soluble starch content, and the quadratics of time, temperature, pH and the soluble starch content, as well as the interactions between fermentation time and pH, and time and the soluble starch content, showed significant effects on DNJ yield. The optimal process parameters for DNJ production within the experimental range of the variables researched was at 11d, 27 °C, pH 7.5, and 8% soluble starch content. At this condition, the DNJ yield was predicted to be 42.875 mg/L.

Parametric and energy consumption optimization of Basic Red 2 removal by electrocoagulation/egg shell adsorption coupling using response surface methodology in a batch system

2015 ◽  
Vol 73 (11) ◽  
pp. 2572-2582 ◽  
Author(s):  
Helder Pereira de Carvalho ◽  
Jiguo Huang ◽  
Meixia Zhao ◽  
Gang Liu ◽  
Xinyu Yang ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Energy Consumption ◽  
Reaction Time ◽  
Response Surface ◽  
Removal Efficiency ◽  
Current Density ◽  
Batch System ◽  
Energy Consumption Optimization ◽  
Initial Ph ◽  
Rsm Model

In this study, response surface methodology (RSM) model was applied for optimization of Basic Red 2 (BR2) removal using electrocoagulation/eggshell (ES) coupling process in a batch system. Central composite design was used to evaluate the effects and interactions of process parameters including current density, reaction time, initial pH and ES dosage on the BR2 removal efficiency and energy consumption. The analysis of variance revealed high R2 values (≥85%) indicating that the predictions of RSM models are adequately applicable for both responses. The optimum conditions when the dye removal efficiency of 93.18% and energy consumption of 0.840 kWh/kg were observed were 11.40 mA/cm2 current density, 5 min and 3 s reaction time, 6.5 initial pH and 10.91 g/L ES dosage.

Optimisation of the Oil Extraction from Nigella sativa Seeds Using Response Surface Methodology

2017 ◽  
Vol 68 (2) ◽  
pp. 331-336
Author(s):  
Gabriela Isopencu ◽  
Mirela Marfa ◽  
Iuliana Jipa ◽  
Marta Stroescu ◽  
Anicuta Stoica Guzun ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Nigella Sativa ◽  
Polynomial Equation ◽  
Herbaceous Plant ◽  
Box Behnken Design ◽  
Pareto Analysis ◽  
Black Cumin ◽  
Mediterranean Countries ◽  
Experimental Values

Nigella sativa, also known as black cumin, an annual herbaceous plant growing especially in Mediterranean countries, has recently gained considerable interest not only for its use as spice and condiment but also for its healthy properties of the fixed and essential oil and its potential as a biofuel. Nigella sativa seeds fixed oil, due to its high content in linoleic acid followed by oleic and palmitic acid, could be beneficial to human health. The objective of this study is to determine the optimum conditions for the solvent extraction of Nigella sativa seeds fixed oil using a three-level, three-factor Box-Behnken design (BBD) under response surface methodology (RSM). The obtained experimental data, fitted by a second-order polynomial equation were analysed by Pareto analysis of variance (ANOVA). From a total of 10 coefficients of the statistical model only 5 are important. The obtained experimental values agreed with the predicted ones.

scholarly journals Modeling and Sensitivity Analysis of the Forward Osmosis Process to Predict Membrane Flux Using a Novel Combination of Neural Network and Response Surface Methodology Techniques

Membranes ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 70
Author(s):  
Jasir Jawad ◽  
Alaa H. Hawari ◽  
Syed Javaid Zaidi
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Response Surface ◽  
Forward Osmosis ◽  
Feed Solution ◽  
Operating Conditions ◽  
Ann Model ◽  
Membrane Flux ◽  
Input Variables ◽  
Rsm Model

The forward osmosis (FO) process is an emerging technology that has been considered as an alternative to desalination due to its low energy consumption and less severe reversible fouling. Artificial neural networks (ANNs) and response surface methodology (RSM) have become popular for the modeling and optimization of membrane processes. RSM requires the data on a specific experimental design whereas ANN does not. In this work, a combined ANN-RSM approach is presented to predict and optimize the membrane flux for the FO process. The ANN model, developed based on an experimental study, is used to predict the membrane flux for the experimental design in order to create the RSM model for optimization. A Box–Behnken design (BBD) is used to develop a response surface design where the ANN model evaluates the responses. The input variables were osmotic pressure difference, feed solution (FS) velocity, draw solution (DS) velocity, FS temperature, and DS temperature. The R2 obtained for the developed ANN and RSM model are 0.98036 and 0.9408, respectively. The weights of the ANN model and the response surface plots were used to optimize and study the influence of the operating conditions on the membrane flux.

scholarly journals Efficient Removal of Levofloxacin by Activated Persulfate with Magnetic CuFe2O4/MMT-k10 Nanocomposite: Characterization, Response Surface Methodology, and Degradation Mechanism

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3583
Author(s):  
Junying Yang ◽  
Minye Huang ◽  
Shengsen Wang ◽  
Xiaoyun Mao ◽  
Yueming Hu ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Photoelectron Spectroscopy ◽  
Degradation Mechanism ◽  
Sol Gel ◽  
Combustion Method ◽  
Copper Ferrite ◽  
X Ray ◽  
Rsm Model

In this study, a magnetic copper ferrite/montmorillonite-k10 nanocomposite (CuFe2O4/MMT-k10) was successfully fabricated by a simple sol-gel combustion method and was characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), the Brunner–Emmett–Teller (BET) method, vibrating sample magnetometer (VSM), and X-ray photoelectron spectroscopy (XPS). For levofloxacin (LVF) degradation, CuFe2O4/MMT-k10 was utilized to activate persulfate (PS). Due to the relative high adsorption capacity of CuFe2O4/MMT-k10, the adsorption feature was considered an enhancement of LVF degradation. In addition, the response surface methodology (RSM) model was established with the parameters of pH, temperature, PS dosage, and CuFe2O4/MMT-k10 dosage as the independent variables to obtain the optimal response for LVF degradation. In cycle experiments, we identified the good stability and reusability of CuFe2O4/MMT-k10. We proposed a potential mechanism of CuFe2O4/MMT-k10 activating PS through free radical quenching tests and XPS analysis. These results reveal that CuFe2O4/MMT-k10 nanocomposite could activate the persulfate, which is an efficient technique for LVF degradation in water.

Electrocoagulation and nanofiltration integrated process application in purification of bilge water using response surface methodology

2016 ◽  
Vol 74 (3) ◽  
pp. 564-579 ◽  
Author(s):  
Ceyhun Akarsu ◽  
Yasin Ozay ◽  
Nadir Dizge ◽  
H. Elif Gulsen ◽  
Hasan Ates ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Cod Removal ◽  
Positive Sign ◽  
Aluminum Electrode ◽  
Integrated Process ◽  
Bilge Water ◽  
Cod Removal Efficiency ◽  
Initial Ph

Marine pollution has been considered an increasing problem because of the increase in sea transportation day by day. Therefore, a large volume of bilge water which contains petroleum, oil and hydrocarbons in high concentrations is generated from all types of ships. In this study, treatment of bilge water by electrocoagulation/electroflotation and nanofiltration integrated process is investigated as a function of voltage, time, and initial pH with aluminum electrode as both anode and cathode. Moreover, a commercial NF270 flat-sheet membrane was also used for further purification. Box–Behnken design combined with response surface methodology was used to study the response pattern and determine the optimum conditions for maximum chemical oxygen demand (COD) removal and minimum metal ion contents of bilge water. Three independent variables, namely voltage (5–15 V), initial pH (4.5–8.0) and time (30–90 min) were transformed to coded values. The COD removal percent, UV absorbance at 254 nm, pH value (after treatment), and concentration of metal ions (Ti, As, Cu, Cr, Zn, Sr, Mo) were obtained as responses. Analysis of variance results showed that all the models were significant except for Zn (P > 0.05), because the calculated F values for these models were less than the critical F value for the considered probability (P = 0.05). The obtained R2 and Radj2 values signified the correlation between the experimental data and predicted responses: except for the model of Zn concentration after treatment, the high R2 values showed the goodness of fit of the model. While the increase in the applied voltage showed negative effects, the increases in time and pH showed a positive effect on COD removal efficiency; also the most effective linear term was found as time. A positive sign of the interactive coefficients of the voltage–time and pH–time systems indicated synergistic effect on COD removal efficiency, whereas interaction between voltage and pH showed an antagonistic effect.

Optimization of Manufacturing Process of Traditional Algerian Jben Cheese Using Response Surface Methodology (RSM)

2018 ◽  
Vol 8 (1) ◽  
pp. 31-42
Author(s):  
M. Amimour ◽  
T. Idoui ◽  
A. Cheriguene
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Manufacturing Process ◽  
Milk Powder ◽  
Statistical Design ◽  
Polynomial Equation ◽  
Enzymatic Extract ◽  
Traditional Cheese ◽  
Order Polynomial ◽  
Predicted Values

The Aim of this study was to develop an optimized method for manufacturing process of traditional Algerian Jben cheese, using response surface methodology (RSM). In order to develop the objective method of making this traditional cheese, several factors have been studied and a Plackett-Burman statistical design was applied. The effects of the four screened factors (enrichment with milk powder, 10 - 20 g/l; pH of milk, 5.75 - 6.75, enzymatic extract dose, 0.5 - 1.5 ml and coagulation temperature 40 - 60 °C) on the response were investigated, using a Box-Behnken statistical design. Multiple regression analysis was used so that experimental data fits to a second-order polynomial equation. This multiple analysis showed that the model explains about 90.73% of the variation. Based on statistical results, it can be noticed that enrichment with milk powder and pH of milk (Ë‚0.0001***) were highly significant factor influincing cheese yield. The optimal production parame-ters that maximized cheese product (20 g/l enrichment with milk powder, 5.75 pH of milk, 1.29 ml enzymatic extract dose and 60°C coagulation temperature) and the maximal predicted cheese yield (52.68 % ) were found out through response surface methodology. Under these conditions, a verification experiment was carried out and cheese yield was found to be 49.46 %. The overall percentage of agreement for the experimental results (more than 93 % validity) with the predicted values indicates the validation of the statistical model and the success of the optimization process.

Optimization of aqueous extraction of orevactaene and flavanoid pigments produced by Epicoccum nigrum

2019 ◽  
Vol 48 (4) ◽  
pp. 301-308 ◽  
Author(s):  
Sawinder Kaur ◽  
Paramjit S. Panesar ◽  
Sushma Gurumayum ◽  
Prasad Rasane ◽  
Vikas Kumar
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Maximum Yield ◽  
Polynomial Equation ◽  
Extraction Process ◽  
Aqueous Extraction ◽  
Extraction Temperature ◽  
Content Type ◽  
Epicoccum Nigrum ◽  
Broken Rice

Purpose The extraction of bioactive compounds such as pigments from natural sources, using different solvents, is a vital downstream process. The present study aims to investigate the effect of different variables, namely, extraction temperature, mass of fermented rice and time on the extraction process of orevactaene and flavanoid pigment from Epicoccum nigrum fermented broken rice. Design/methodology/approach Central composite rotatable design under response surface methodology was used for deducing optimized conditions. The pigments were extracted under conditions of extraction temperature (40-70°C), mass of fermented rice (0.5-1.5 g) and time (30-90 min), using water as the extraction media. The experimental data obtained were studied by analysis of variance. Data were fitted to a second-order polynomial equation using multiple regression analysis. Findings The optimum conditions generated by the software for aqueous extraction process, i.e. extraction temperature of 55.7°C, 0.79 g of fermented matter and extraction time of 56.6 min, resulted in a pigment yield of 52.7AU/g orevactaene and 77.2 AU/g flavanoid. Research limitations/implications The developed polynomial empirical model for the optimal recovery of the orevactaene and flavanoid pigments could be used for further studies in prediction of yield under specified variable conditions. Practical implications The response surface methodology helped in optimizng the conditions for the eco-friendly low-cost aqueous extarction process for orevactaene and flavanoid pigments, produced by Epicoccum nigrum during solid state fermentation of broken rice. This optimization can provide the basis for scaling up for industrial extraction process. Originality/value This paper focuses on optimizing the extraction conditions to get the maximum yield of orevactaene and flavanoid pigments, using water as the extracting media. No literature is available on the optimization of the extraction process of Epicoccum nigrum pigments, to the best of the authors’ knowledge.

Optimization of photocatalytic degradation of real textile dye house wastewater by response surface methodology

2016 ◽  
Vol 74 (9) ◽  
pp. 1999-2009 ◽  
Author(s):  
Sayed Mohammad Bagher Hosseini ◽  
Narges Fallah ◽  
Sayed Javid Royaee
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Flow Rate ◽  
Advanced Oxidation Process ◽  
Influential Factor ◽  
P Value ◽  
Textile Dye ◽  
Optimum Conditions ◽  
Effective Parameters ◽  
Initial Ph

This study evaluates the advanced oxidation process for decolorization of real textile dyeing wastewater containing azo and disperse dye by TiO2 and UV radiation. Among effective parameters on the photocatalytic process, effects of three operational parameters (TiO2 concentration, initial pH and aeration flow rate) were examined with response surface methodology. The F-value (136.75) and p-value <0.0001 imply that the model is significant. The ‘Pred R-Squared’ of 0.95 is in reasonable agreement with the ‘Adj R-Squared’ of 0.98, which confirms the adaptability of this model. From the quadratic models developed for degradation and subsequent analysis of variance (ANOVA) test using Design Expert software, the concentration of catalyst was found to be the most influential factor, while all the other factors were also significant. To achieve maximum dye removal, optimum conditions were found at TiO2 concentration of 3 g L−1, initial pH of 7 and aeration flow rate of 1.50 L min−1. Under the conditions stated, the percentages of dye and chemical oxygen demand removal were 98.50% and 91.50%, respectively. Furthermore, the mineralization test showed that total organic compounds removal was 91.50% during optimum conditions.

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