Process Optimization Study of Zn2+ Adsorption on Biochar-Alginate Composite Adsorbent by Response Surface Methodology (RSM)

A novel biochar alginate composite adsorbent was synthesized and applied for removal of Zn2+ ions from aqueous solution. Kinetics, equilibrium and thermodynamic studies showed the suitability of the adsorbent. From a Langmuir isotherm study, the maximum monolayer adsorption capacity of the composite adsorbent was found to be 120 mg/g. To investigate the effect of process variables like initial Zn2+ concentration (25–100 mg/L), adsorbent dose (0.4–8 g/L) and temperature (298–318 K) on Zn2+ adsorption, response surface methodology (RSM) based on a three independent variables central composite design of experiments was employed. A quadratic model equation was developed to predict the relationship between the independent variables and response for maximum Zn2+ removal. The optimization study reveals that the initial Zn2+ concentration and adsorbent dose were the most effective parameters for removal of Zn2+ due to higher magnitude of F-statistic value which effects to a large extent of Zn2+ removal. The optimum physicochemical condition for maximum removal of Zn2+ was determined from the RSM study. The optimum conditions are 43.18 mg/L initial metal ion concentration, 0.062 g adsorbent dose and a system temperature of 313.5 K. At this particular condition, the removal efficiency of Zn2+ was obtained as 85%.

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Optimizing Adsorption of 17α-Ethinylestradiol from Water by Magnetic MXene Using Response Surface Methodology and Adsorption Kinetics, Isotherm, and Thermodynamics Studies

Molecules ◽

10.3390/molecules26113150 ◽

2021 ◽

Vol 26 (11) ◽

pp. 3150

Author(s):

Mengwei Xu ◽

Chao Huang ◽

Jing Lu ◽

Zihan Wu ◽

Xianxin Zhu ◽

...

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Quadratic Model ◽

Adsorption Efficiency ◽

Process Variables ◽

Adsorption Time ◽

Initial Concentration ◽

Independent Variables ◽

The Impact ◽

Adsorbent Dose

Magnetic MXene composite Fe3O4@Ti3C2 was successfully prepared and employed as 17α-ethinylestradiol (EE2) adsorbent from water solution. The response surface methodology was employed to investigate the interactive effects of adsorption parameters (adsorption time, pH of the solution, initial concentration, and the adsorbent dose) and optimize these parameters for obtaining maximum adsorption efficiency of EE2. The significance of independent variables and their interactions were tested by the analysis of variance (ANOVA) and t-test statistics. Optimization of the process variables for maximum adsorption of EE2 by Fe3O4@Ti3C2 was performed using the quadratic model. The model predicted maximum adsorption of 97.08% under the optimum conditions of the independent variables (adsorption time 6.7 h, pH of the solution 6.4, initial EE2 concentration 0.98 mg L−1, and the adsorbent dose 88.9 mg L−1) was very close to the experimental value (95.34%). pH showed the highest level of significance with the percent contribution (63.86%) as compared to other factors. The interactive influences of pH and initial concentration on EE2 adsorption efficiency were significant (p < 0.05). The goodness of fit of the model was checked by the coefficient of determination (R2) between the experimental and predicted values of the response variable. The response surface methodology successfully reflects the impact of various factors and optimized the process variables for EE2 adsorption. The kinetic adsorption data for EE2 fitted well with a pseudo-second-order model, while the equilibrium data followed Langmuir isotherms. Thermodynamic analysis indicated that the adsorption was a spontaneous and endothermic process. Therefore, Fe3O4@Ti3C2 composite present the outstanding capacity to be employed in the remediation of EE2 contaminated wastewaters.

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Optimisation and Modelling of Pb (II) and Cu (II) Biosorption onto Red Algae (Gracilaria changii) by Using Response Surface Methodology

Water ◽

10.3390/w11112325 ◽

2019 ◽

Vol 11 (11) ◽

pp. 2325 ◽

Cited By ~ 3

Author(s):

Mubeen Isam ◽

Lavania Baloo ◽

Shamsul Rahman Mohamed Kutty ◽

Saba Yavari

Keyword(s):

Response Surface Methodology ◽

Metal Ions ◽

Response Surface ◽

Metal Ion ◽

Ion Concentration ◽

Solution Ph ◽

Gracilaria Changii ◽

Red Macroalgae ◽

Removal Of Metal ◽

Removal Of Metal Ions

The removal of Pb (II) and Cu (II) ions by using marine red macroalgae (Gracilaria changii) as a biosorbent material was evaluated through the batch equilibrium technique. The effect of solution pH on the removal of metal ions was investigated within the range of 2–7. The response surface methodology (RSM) technique involving central composite design (CCD) was utilised to optimise the three main sorption parameters, namely initial metal ion concentration, contact time, and biosorbent dosage, to achieve maximum ion removal. The models’ adequacy of response was verified by ANOVA. The optimum conditions for removal of Pb (II) and Cu (II) were as follows: pH values of 4.5 and 5, initial concentrations of 40 mg/L, contact times of 115 and 45 min, and biosorbent dosage of 1 g/L, at which the maximum removal percentages were 96.3% and 44.77%, respectively. The results of the adsorption isotherm study showed that the data fitted well with the Langmuir’s model for Pb (II) and Cu (II). The results of the adsorption kinetic study showed that the data fitted well with the pseudo-second order model for Pb (II) and Cu (II). In conclusion, red alga biomass exhibits great potential as an efficient low-cost sorbent for removal of metal ions.

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Batch versus column modes for the adsorption of radioactive metal onto rice husk waste: conditions optimization through response surface methodology

Water Science & Technology ◽

10.2166/wst.2017.220 ◽

2017 ◽

Vol 76 (5) ◽

pp. 1035-1043 ◽

Cited By ~ 20

Author(s):

Abida Kausar ◽

Haq Nawaz Bhatti ◽

Munawar Iqbal ◽

Aisha Ashraf

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Rice Husk ◽

Flow Rate ◽

Ion Concentration ◽

Quadratic Model ◽

Batch Adsorption ◽

Batch Mode ◽

Bed Height ◽

Column Adsorption

Batch and column adsorption modes were compared for the adsorption of U(VI) ions using rice husk waste biomass (RHWB). Response surface methodology was employed for the optimization of process variables, i.e., (pH (A), adsorbent dose (B), initial ion concentration (C)) in batch mode. The B, C and C2 affected the U(VI) adsorption significantly in batch mode. The developed quadratic model was found to be validated on the basis of regression coefficient as well as analysis of variance. The predicted and actual values were found to be correlated well, with negligible residual value, and B, C and C2 were significant terms. The column study was performed considering bed height, flow rate and initial metal ion concentration, and adsorption efficiency was evaluated through breakthrough curves and bed depth service time and Thomas models. Adsorption was found to be dependent on bed height and initial U(VI) ion concentration, and flow rate decreased the adsorption capacity. Thomas models fitted well to the U(VI) adsorption onto RHWB. Results revealed that RHWB has potential to remove U(VI) ions and batch adsorption was found to be efficient versus column mode.

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Optimized characterization of response surface methodology on lubricant with titanium oxide nanoparticles

Industrial Lubrication and Tribology ◽

10.1108/ilt-09-2016-0214 ◽

2017 ◽

Vol 69 (3) ◽

pp. 387-392 ◽

Cited By ~ 4

Author(s):

Nor Syahirah Mohamad ◽

Salmiah Kasolang

Keyword(s):

Response Surface Methodology ◽

Mathematical Models ◽

Response Surface ◽

Quadratic Model ◽

Coefficient Of Determination ◽

Contour Plot ◽

Content Type ◽

Independent Variables ◽

Non Linear System

Purpose An optimized model is often deployed to reduce trial and error in experimental approach and obtain the multi-variant correlation. In this study, response surface methodology (RSM), namely, Box–Behnken design (BBD) approach, has been used to optimize the characterization of lubricant with additives. BBD is based on multivariate analysis whereby the effects of different parameters are considered simultaneously. It is a non-linear system which is more representative of the actual phenomenon. This study aims to investigate the effect of three independent variables, namely, speed, load and concentration of TiO2, on the coefficient of friction (CoF). Design/methodology/approach RSM was applied to get the multiplicity of the self-determining input variables and construct mathematical models. Mathematical models were established to predict the CoF and to conduct a statistical analysis of the independent variables’ interactions on response surface using Minitab 16.0 statistical software. Three parameters were regulated: speed (X1), load (X2) and concentration of TiO2 (X3). The output measured was the CoF. Findings The result obtained from BBD has shown that the most influential parameter was speed, followed by concentration of TiO2 nanoparticles and then normal load. Analysis of variance indicated that the proposed experiment from the quadratic model has successfully interpreted the experimental data with a coefficient of determination R2 = 0.9931. From the contour plot of BBD, the optimization zone for interacting variables has been obtained. The zone indicates two regions of lower friction values (<0.04): concentration between 0.5 to 1.0 Wt.% for a speed range of 1,000 to 2,000 rpm, and load between 17 to 20 kg for a speed in the range of 1,200 to 1,900 rpm. The optimized condition shows that the minimum value of CoF (0.0191) is at speed of 1,782 rpm, load of 20 kg and TiO2 concentration of 1.0 Wt.%. Originality/value In general, it has been shown that RSM is an effective and powerful tool in experimental optimization of multi-variants.

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Process Optimization at an Industrial Scale in the adsorptive removal of Cd2+ ions using Dolochar via Response Surface Methodology

10.21203/rs.3.rs-811892/v1 ◽

2021 ◽

Author(s):

Utkarsh Upadhyay ◽

Sarthak Gupta ◽

Ankita Agarwal ◽

Inkollu Sreed ◽

Kayamkulathethu Latitha Anitha

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Flow Rate ◽

Metal Ion ◽

Large Scale ◽

Scale Up ◽

Ion Concentration ◽

Ion Adsorption ◽

Cadmium Ion ◽

Bed Height

Abstract Over the years, researchers have continuously searched for ways to achieve adsorption of heavy metal ions from the industrial effluents at lowest possible cost, which has resulted into the development of innumerous special type of low cost adsorbents, called biosorbents. While potential of many biosorbents have been explored in laboratory setup, very few studies have tried to scale up the biosorption process and predict the performance of these biosorbents in a large scale industrial setup. In this work, performance of laboratory synthesized dolochar has been investigated for adsorption of Cd2+ ions in a large scale process with the application of Aspen Adsorption. Moreover, the optimum values of the operating parameters (namely, flow rate, bed height and inlet metal ion concentration) that would result into maximum amount of cadmium ion adsorption (high exhaustion capacity) in minimum time (less exhaustion time) for a fixed mass of dolochar (1200 kg) have been calculated via the application of Response Surface Methodology. It was found out that, at optimum values of bed height (3.48 m), flow rate (76.31 m3/day) and inlet concentration (10 ppm), the optimized value of exhaustion capacity and exhaustion time for cadmium ion adsorption in dolochar packed bed is equal to 1.85 mg/g and 11.39 hours, respectively. The validity of these simulation experiments can be proven by the fact that the obtained exhaustion capacity of dolochar packed beds always remained in close proximity of the experimentally obtained value of adsorption capacity of the dolochar in batch process mode (equal to 2.1 mg/g).

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Use of agro-waste (Musa paradisiaca peels) as a sustainable biosorbent for toxic metal ions removal from contaminated water

10.31221/osf.io/yrpvn ◽

2019 ◽

Author(s):

Chem Int

Keyword(s):

Heavy Metal ◽

Metal Ions ◽

Contact Time ◽

Metal Ion ◽

Equilibrium Concentration ◽

Ion Concentration ◽

Contaminated Water ◽

Musa Paradisiaca ◽

Percentage Removal ◽

Adsorbent Dose

A study of removal of heavy metal ions from heavy metal contaminated water using agro-waste was carried out with Musa paradisiaca peels as test adsorbent. The study was carried by adding known quantities of lead (II) ions and cadmium (II) ions each and respectively into specific volume of water and adding specific dose of the test adsorbent into the heavy metal ion solution, and the mixture was agitated for a specific period of time and then the concentration of the metal ion remaining in the solution was determined with Perkin Elmer Atomic absorption spectrophotometer model 2380. The effect of contact time, initial adsorbate concentration, adsorbent dose, pH and temperature were considered. From the effect of contact time results equilibrium concentration was established at 60minutes. The percentage removal of these metal ions studied, were all above 90%. Adsorption and percentage removal of Pb2+ and Cd2+ from their aqueous solutions were affected by change in initial metal ion concentration, adsorbent dose pH and temperature. Adsorption isotherm studies confirmed the adsorption of the metal ions on the test adsorbent with good mathematical fits into Langmuir and Freundlich adsorption isotherms. Regression correlation (R2) values of the isotherm plots are all positive (>0.9), which suggests too, that the adsorption fitted into the isotherms considered.

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EXTRACTION OPTIMIZATION AND ANTIOXIDANT ACTIVITY OF PHENOLIC COMPOUNDS FROM AVOCADO PEEL

Journal of Medicine and Pharmacy ◽

10.34071/mp.2019.3.7 ◽

2019 ◽

pp. 49-59

Author(s):

Nu Linh Giang Ton ◽

Thi Hoai Nguyen ◽

Quoc Hung Vo

Keyword(s):

Antioxidant Activity ◽

Response Surface Methodology ◽

Antioxidant Capacity ◽

Response Surface ◽

Total Antioxidant Capacity ◽

Total Phenolic Content ◽

Phenolic Content ◽

Quadratic Model ◽

Total Phenolic ◽

Total Antioxidant

Avocado peel has been considered as a potential source of natural antioxidants in which phenolics are among the most important compounds. Therefore, this study aims to optimize the extraction process of phenolics using response surface methodology and evaluate the corresponding antioxidant activity. From the quadratic model, the optimal condition was determined including the ethanol concentration 54.55% (v/v), the solvent/solute ratio 71.82/1 (mL/g), temperature 53.03 oC and extraction time 99.09 min. The total phenolic content and the total antioxidant capacity at this condition with minor modifications were 26,74 ± 0,04 (mg GAE/g DW) and 188.06 ± 1.41 (mg AAE/g DW), respectively. The significant correlation between total phenolic content and total antioxidant capacity was also confirmed. Key words: response surface methodology, central composite rotatable design, total phenolic content, total antioxidant capacity, avocado peel

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Optimization of Lignin Extraction Variables by Response Surface Methodology from Pine Saw Dust, and Quantification of Major Structural Units in Isolated Lignin Fraction

Applied Sciences ◽

10.3390/app11041739 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1739

Author(s):

Muhammad Ajaz Ahmed ◽

Jae Hoon Lee ◽

Joon Weon Choi

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Quantum Coherence ◽

Resonance Spectrum ◽

Quadratic Model ◽

Molecular Weights ◽

Solids Loading ◽

A Value ◽

Lignin Extraction ◽

Lignin Fraction

A synergistic combination of dioxane, acetic acid, and HCl was investigated for lignin extraction from pine wood biomass. After initial screening of reagent combination, response surface methodology (RSM) was used to optimize the lignin yield with respect to the variables of time 24–72 h, solids loading 5–15%, and catalyst dose 5–15 mL. A quadratic model predicted 8.33% of the lignin yield, and it was further confirmed experimentally and through the analysis of variance (ANOVA). Lignin at optimum combination exhibited features in terms of derivatization followed by reductive cleavage (DFRC) with a value of (305 µmol/gm), average molecular weights of 4358 and polydispersity of 1.65, and 2D heteronuclear single quantum coherence nuclear magnetic resonance spectrum (2D-HSQC NMR) analysis showing relative β-O-4 linkages (37.80%). From here it can be suggested that this fractionation can be one option for high quality lignin extraction from lignocellulosic biomass.

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