scholarly journals Arsenic removal by the micellar-enhanced ultrafiltration using response surface methodology

2019 ◽  
Vol 20 (2) ◽  
pp. 574-585 ◽  
Author(s):  
Oznur Begum Gokcek ◽  
Nigmet Uzal
Keyword(s):  
Response Surface Methodology ◽  
Aqueous Solutions ◽  
Response Surface ◽  
Removal Efficiency ◽  
Surfactant Concentration ◽  
Arsenic Removal ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Micellar Enhanced Ultrafiltration ◽  
The Impact

Abstract The present research investigates the removal of arsenic (As) from aqueous solutions using micellar-enhanced ultrafiltration (MEUF) by utilizing two different surfactants: benzethonium chloride and dodecyl pyridinium chloride (BCl and DPCl). The impact of the operating variables and maximum removal efficiency were found under different conditions for BCl and DPCl surfactants. The maximum As rejection efficiency for MEUF with BCl and DPCl surfactants is 92.8% and 84.1%, respectively. In addition to this, a statistics-based experimental design with response surface methodology was used for the purpose of examining the impact of operating conditions, including initial pH, initial As concentration (ppb), and surfactant concentration (BCl, mM) in As-removal from aqueous solutions. In the analysis of the experimental data, a second-order polynomial model that was validated by statistical analysis for the BCl surfactant was used. On the basis of the response model created, the removal of As ions was acquired at optimum operating parameters, including the initial As concentration of 150 ppb, surfactant concentration of 5 mM and pH 10 for the BCl surfactant with 92.8% As-removal efficiency.

scholarly journals Design and Optimization of a Process for Sugarcane Molasses Fermentation bySaccharomyces cerevisiaeUsing Response Surface Methodology

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Nour Sh. El-Gendy ◽  
Hekmat R. Madian ◽  
Salem S. Abu Amr
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Batch Fermentation ◽  
Fermentation Process ◽  
Incubation Temperature ◽  
Operating Conditions ◽  
Quadratic Model ◽  
Optimum Operating ◽  
Sugarcane Molasses ◽  
Bioethanol Production

A statistical model was developed in this study to describe bioethanol production through a batch fermentation process of sugarcane molasses by locally isolatedSaccharomyces cerevisiaeY-39. Response surface methodology RSM based on central composite face centered design CCFD was employed to statistically evaluate and optimize the conditions for maximum bioethanol production and study the significance and interaction of incubation period, initial pH, incubation temperature, and molasses concentration on bioethanol yield. With the use of the developed quadratic model equation, a maximum ethanol production of 255 g/L was obtained in a batch fermentation process at optimum operating conditions of approximately 71 h, pH 5.6, 38°C, molasses concentration 18% wt.%, and 100 rpm.

scholarly journals Fixed bed utilization for the isolation of xylene vapor: Kinetics and optimization using response surface methodology and artificial neural network

2020 ◽  
Vol 26 (2) ◽  
pp. 200105-0
Author(s):  
Kaushal Naresh Gupta ◽  
Rahul Kumar
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Flow Rate ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Operating Parameters ◽  
Bed Height ◽  
Artificial Neural

This paper discusses the isolation of xylene vapor through adsorption using granular activated carbon as an adsorbent. The operating parameters investigated were bed height, inlet xylene concentration and flow rate, their influence on the percentage utilization of the adsorbent bed up to the breakthrough was found out. Mathematical modeling of experimental data was then performed by employing a response surface methodology (RSM) technique to obtain a set of optimum operating conditions to achieve maximum percentage utilization of bed till breakthrough. A fairly high value of R2 (0.993) asserted the proposed polynomial equation’s validity. ANOVA results indicated the model to be highly significant with respect to operating parameters studied. A maximum of 76.1% utilization of adsorbent bed was found out at a bed height of 0.025 m, inlet xylene concentration of 6,200 ppm and a gas flow rate of 25 mL.min-1. Furthermore, the artificial neural network (ANN) was also employed to compute the percentage utilization of the adsorbent bed. A comparison between RSM and ANN divulged the performance of the latter (R2 = 0.99907) to be slightly better. Out of various kinetic models studied, the Yoon-Nelson model established its appropriateness in anticipating the breakthrough curves.

scholarly journals Optimisation of Tray Drier Microalgae Dewatering Techniques Using Response Surface Methodology

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2327 ◽  
Author(s):  
Ruth Anyanwu ◽  
Cristina Rodriguez ◽  
Andy Durrant ◽  
Abdul Olabi
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Air Temperature ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Slight Effect ◽  
Air Velocity ◽  
Independent Variables ◽  
Air Supply ◽  
Central Composite

The feasibility of the application of a tray drier in dewatering microalgae was investigated. Response surface methodology (RSM) based on Central Composite Design (CCD) was used to evaluate and optimise the effect of air temperature and air velocity as independent variables on the dewatering efficiency as a response function. The significance of independent variables and their interactions was tested by means of analysis of variance (ANOVA) with a 95% confidence level. Results indicate that the air supply temperature was the main parameter affecting dewatering efficiency, while air velocity had a slight effect on the process. The optimum operating conditions to achieve maximum dewatering were determined: air velocities and temperatures ranged between 4 to 10 m/s and 40 to 56 °C respectively. An optimised dewatering efficiency of 92.83% was achieved at air an velocity of 4 m/s and air temperature of 48 °C. Energy used per 1 kg of dry algae was 0.34 kWh.

scholarly journals Modeling of nitrate removal from aqueous solution by Fe-doped TiO2 under UV and solar irradiation using response surface methodology

2015 ◽  
Vol 17 (2) ◽  
pp. 379-388 ◽  
Keyword(s):  
Aqueous Solution ◽  
Response Surface Methodology ◽  
Solar Radiation ◽  
Response Surface ◽  
Removal Efficiency ◽  
Nitrate Removal ◽  
Operating Conditions ◽  
Solar Irradiation ◽  
Design Matrix ◽  
Statistical Tool

<div> <p>Nitrate is a common groundwater pollutant all over the world. In some regions of Iran, its levels are high enough to cause serious problems to human health and the environment<span dir="RTL">.</span> The objectives of this work were to evaluate the efficiency of Fe-doped TiO<sub>2</sub> nanoparticles at removing nitrate from aqueous solutions under UV and solar radiation and to model nitrate removal using response surface methodology techniques. In this study, a response surface methodology based on the Box&ndash;Behnken design matrix was used to describe the process of nitrate removal from an aqueous solution with four independent parameters, namely Fe-doped TiO<sub>2</sub> (dose 1-2 g l<sup>-1</sup>), nitrate concentration (25-100 mg l<sup>-1</sup>), contact time (10-120 min), and pH (4-9). The results indicated that the removal efficiency of nitrate in the presence of ultraviolet and solar radiation was 56.5 % and 21.8%, respectively. The removal efficiency of nitrate increased with time and initial concentration of nitrate. Analysis of variance (ANOVA) indicated that the proposed model was essentially in accordance with the experimental results with the correlation coefficient R<sup>2 </sup>= 0.9237 and Adj-R<sup>2</sup> = 0.8347. Response surface methodology (RSM) proved to be a powerful statistical tool for investigating the operating conditions for nitrate removal under UV irradiation.</p> </div> <p>&nbsp;</p>

scholarly journals Response surface methodology, modeling to improve mercury removal from aqueous solutions using L-Cysteine functionalized Multi-walled Carbon Nanotubes

2019 ◽  
Vol 21 (1) ◽  
pp. 64-69
Keyword(s):  
Carbon Nanotubes ◽  
Response Surface Methodology ◽  
Aqueous Solutions ◽  
Response Surface ◽  
Removal Efficiency ◽  
Mercury Concentration ◽  
Contact Time ◽  
Mercury Removal ◽  
Multi Walled Carbon Nanotubes ◽  
Walled Carbon Nanotubes

<p>The aim of this study was to evaluate the mercury removal from aqueous solutions by using L-Cysteine functionalized Multi-walled Carbon Nanotubes. The effect of pH, adsorbent dose, contact time and mercury concentration in removal efficiency was evaluated. Multi -walled carbon nanotubes were functionalized with L-cysteine. The Response Surface Methodology (RSM) was used to find the optimum process parameters. The results showed that an increase in contact time, pH and adsorbent dosage resulted in an increase of the adsorption rate. However, removal efficiency decreases by increasing mercury concentration. The highest and lowest removal efficiencies of mercury were 89% and 17%, respectively. The maximum adsorption rate was occurring at 120 min. It is concluded that L-Cysteine functionalized multi-walled carbon nanotubes is an effective adsorbent for removal from aqueous solutions.</p>

scholarly journals Enzyme-Assisted Mechanical Peeling of Cassava Tubers

Catalysts ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 66
Author(s):  
Ziba Barati ◽  
Sajid Latif ◽  
Sebastian Romuli ◽  
Joachim Müller
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Surface Area ◽  
Incubation Time ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Optimum Conditions ◽  
Peeling Process ◽  
Pre Treatment

In this study, the effect of enzymatic pre-treatment and the size of cassava tubers on mechanical peeling was examined. Cassava tubers were sorted based on their mass as small, medium and large. Viscozyme® L and an abrasive cassava peeling machine was used for the enzymatic pre-treatment and the mechanical peeling, respectively. Response surface methodology (RSM) was used to investigate the effect of the enzyme dose (0.5–1.9 mL g−1), incubation time (1.5–6 h), peeling time (1.5–4.5 min) and size of the tubers (small, medium and large) on the peeling process. Peeled surface area (PSA) and peel loss (PL) were measured as main responses in RSM. Results showed that the PSA and PL were significantly (p < 0.05) influenced by the enzyme dose, incubation time and peeling time. The size of tubers only had a significant impact on the PSA. The optimum operating conditions for different sizes of tubers were found and validated. Under optimum conditions, the PSA of the large tubers (89.52%) was significantly higher than the PSA of the medium and small tubers (p < 0.05). Application of enzymatic pre-treatment can improve the mechanical peeling process especially for larger cassava tubers.

scholarly journals Application of Response Surface Methodology for Optimization of Permeabilization Process of Baker’s Yeast

2014 ◽  
Vol 16 (2) ◽  
pp. 31-35 ◽  
Author(s):  
Ilona Trawczyńska ◽  
Marek Wójcik
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Catalase Activity ◽  
Isopropyl Alcohol ◽  
Treatment Time ◽  
Baker’S Yeast ◽  
Operating Conditions ◽  
Yeast Cells ◽  
Optimum Operating ◽  
Baker's Yeast

Abstract Permeabilization was used for the purpose of transforming the cells of microorganisms into biocatalysts with an enhanced enzyme activity. Baker’s yeast cells were permeabilized with various organic solvents. A high degree of catalase activity was observed upon permeabilization with acetone, chloroform, isopropyl alcohol and ethyl acetate. Response surface methodology was used to model the effect of concentration of isopropyl alcohol, temperature and treatment time on the permeabilization of baker’s yeast cells to maximize the decomposition of H2O2. The optimum operating conditions for permeabilization were observed at 53.7% concentration of isopropyl alcohol, treatment time of 40 min and temperature of 15.6oC. A maximum value of catalase activity was found to be 6.188 U/g wet wt. and was ca. 60 times higher than the catalytic activity of yeast not treated by the permeabilization process.

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