Application of response surface methodology for optimization of lead biosorption in an aqueous solution by Aspergillus niger

Amini, Malihe; Younesi, Habibollah; Bahramifar, Nader; Zinatizadeh, Ali Akbar; Ghorbani, Farshid; Daneshi, Ali; Sharifzadeh, Mazyar

doi:10.1016/j.jhazmat.2007.10.114

Cited by 390 publications

(164 citation statements)

References 50 publications

(66 reference statements)

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“…An R 2 value of 0.861 rendered this regression model as statistically significant. The value of lack of fit was insignificant (>0.05) thereby confirming the quadratic model appropriate for this study [35].…”

Section: Adsorption Isothermssupporting

confidence: 50%

“…During the batch studies, the experimental factors were optimized for maximum phenol removal using response surface methodology (RSM). RSM is an optimization procedure based on mathematics and statistics and is implemented for estimation of the most advantageous operational parameters as well as the relative significance of each parameter involved in complex interactions with other such parameters [18][19][20][21][22]. In this study, central composite design (CCD) of RSM was utilized in determining the effects of solution pH, adsorbent dosage and time of contact on phenol removal by various soil composites used as a membrane.…”

Section: Introductionmentioning

confidence: 99%

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Phenol Adsorption onto Various Soil Composite Membranes: Insight into Process Kinetics, Modelling and Optimisation Using Response Surface Methodology

Goswami¹

2015

Hydrol Current Res

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Section: Adsorption Isothermssupporting

confidence: 50%

Section: Introductionmentioning

confidence: 99%

Phenol Adsorption onto Various Soil Composite Membranes: Insight into Process Kinetics, Modelling and Optimisation Using Response Surface Methodology

Goswami¹

2015

Hydrol Current Res

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“…The insignificant p-values for lack of fit, at 95% confidence level, also suggest that the fits of the data are appropriate. The fit of these empirical models was also checked by the coefficient of determination (R 2 ), the adj-R 2 , the pred-R 2 , and the coefficient of variation (CV); see Table 4 tions was not explained by the models; R 2 values close to 1 indicate good fits [20]. The pred-R 2 value of MOE was 0.9237, meaning that the full model is estimated to explain about 92.37% of the variability in new data.…”

Section: Statistical Analysis Of the Response Surface Modelmentioning

confidence: 99%

The optimal formulation of recycled polypropylene/rubberwood flour composites from experiments with mixture design

Homkhiew

Ratanawilai

Thongruang

2014

Composites Part B: Engineering

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a b s t r a c tA mixture design was used in experiments, to determine the optimal mixture for composites of rubberwood flour (RWF) and reinforced recycled polypropylene (rPP). The mixed materials were extruded into panels. Effects were determined of the mixture components rPP, RWF, maleic anhydride-grafted polypropylene (MAPP), and ultraviolet (UV) stabilizer, on the mechanical properties. The overall composition significantly affected flexural, compressive, and tensile properties. The fractions of recycled polypropylene and rubberwood flour increased all the mechanical material properties; however, increasing one fraction must be balanced by decreasing the other, and the rubberwood flour fraction had a higher effect size. The fraction of MAPP was best kept in mid-range of the fractions tested, while the UV stabilizer fraction overall degraded the mechanical properties. Our results suggest that the fraction of UV stabilizer should be as small as possible to minimize its negative influences. The models fitted were used for optimization of a desirability score, substituting for the multiple objectives modeled. The optimal formulation found was 50.3 wt% rPP, 44.5 wt% RWF, 3.9 wt% MAPP, 0.2 wt% UV stabilizer, and 1.0 wt% lubricant; the composite made with this formulation had good mechanical properties that closely matched the model predictions.

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“…Larger F-and smaller p-values suggest more significant corresponding variables (Amini et al 2008;Kalavathy et al 2009). The lack of fit measures the failure of the model to represent data in the experimental domain at points that are not included in the regression.…”

Section: Discussionmentioning

confidence: 99%

Effect of Enzymatic Pretreatment on the Preparation and Properties of Soy-Based Adhesive for Plywood

Chen¹,

Zeng²,

Qin³

et al. 2015

BioResources

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Response surface methodology was employed to determine the effects of enzymatic pretreatment temperature, time, and pH on the reducing sugar content and bonding strength of soy-based adhesives (SBAs). Plywood specimens bonded by the SBAs with Pinus massoniana veneer were then produced. A significant positive correlation was observed between reducing sugar content and the bonding strength of SBAs. The effects of pretreatment temperature and time on bonding strength were also significant, but insignificant with respect to reducing sugar content; the effects of enzymatic pretreatment time on response values were the smallest. The optimal enzymatic pretreatment conditions of SBA were a pretreatment temperature of 54 °C, a pretreatment time of 20.0 min, and a pretreatment pH of 5.1. Under these conditions, the reducing sugar content and bonding strength (boiling-water test) of SBAs were 2.93% and 0.62 MPa, which were higher than the control by 113.9% and 30.6%, respectively. X-ray diffraction (XRD) indicated that the ordered degree of soy protein decreased, but the ordered structure had no variation when defatted soy flour was treated by enzymes with combination of acid, salt, and alkali. The SBAs contain more active functional groups and have better water resistance after curing.

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Application of response surface methodology for optimization of lead biosorption in an aqueous solution by Aspergillus niger

Cited by 390 publications

References 50 publications

Phenol Adsorption onto Various Soil Composite Membranes: Insight into Process Kinetics, Modelling and Optimisation Using Response Surface Methodology

Phenol Adsorption onto Various Soil Composite Membranes: Insight into Process Kinetics, Modelling and Optimisation Using Response Surface Methodology

The optimal formulation of recycled polypropylene/rubberwood flour composites from experiments with mixture design

Effect of Enzymatic Pretreatment on the Preparation and Properties of Soy-Based Adhesive for Plywood

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