Physicochemical parameter influences and their optimization on the biosynthesis of MnO2 nanoparticles using Vernonia amygdalina leaf extract

The manganese dioxide nanoparticles (MnO2 NPs) were synthesized using Vernonia amygdalina leaf extract which was used as a reducing, capping, and stabilizing agents due to the presence of bioactive phytochemical compounds. Twenty five runs were designed to investigate the effect of V. amygdalina lea...

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Main Authors: Yilkal Dessie, Sisay Tadesse, Rajalakshmanan Eswaramoorthy
Format: Article
Language:English
Published: Elsevier 2020-08-01
Series:Arabian Journal of Chemistry
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1878535220302033
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spelling doaj-1dcaa03d3a1e45738a4db8eba6ba54072020-11-25T03:19:55ZengElsevierArabian Journal of Chemistry1878-53522020-08-0113864726492Physicochemical parameter influences and their optimization on the biosynthesis of MnO2 nanoparticles using Vernonia amygdalina leaf extractYilkal Dessie0Sisay Tadesse1Rajalakshmanan Eswaramoorthy2Adama Science and Technology University, Department of Applied Chemistry, Adama, Ethiopia; Corresponding author.Hawassa University, Department of Chemistry, Hawassa, EthiopiaAdama Science and Technology University, Department of Applied Chemistry, Adama, EthiopiaThe manganese dioxide nanoparticles (MnO2 NPs) were synthesized using Vernonia amygdalina leaf extract which was used as a reducing, capping, and stabilizing agents due to the presence of bioactive phytochemical compounds. Twenty five runs were designed to investigate the effect of V. amygdalina leaf extract ratio (A), initial potassium permanganate (KMnO4) concentration (B), pH (C), and reaction time (D) on the biosynthesized MnO2 NPs using 4-factor, 4-level D-Optimal Response Surface Quadratic Design Model approach. The relationship between physicochemical variables and absorption responses were established using transform second degree polynomial quadratic model. The effects of each absorption responses were analyzed by ANOVA principle using quadratic equations. A very low p-values (<0.0001), non-significant Lack of Fit F-values, and reasonable regression coefficient values (coefficient R2 = 0.9790, adjusted R2 = 0.9496, and predicted R2 = 0.8452) suggested that there is an effective correlation between experimental results and predicted values. Numerical and graphical optimized results demonstrated that the optimized conditions for the predicted absorbance at 320 nm (1.095) were suggested at 43.72%, 1.81 mM, 6.02, and 103.42 min for V. amygdalina leaf extract ratio, initial KMnO4 concentration, pH, and reaction time, respectively. Under these optimal conditions, the average absorbance from four experimental run was recorded to be 0.9678. This result was very closest to the predicted values. The average size elucidated by X-ray diffraction (XRD) analysis was found in the range between 20 nm and 22 nm. The stretching/or and vibrational, surface topography, thermal, and surface roughness as well as its porosity distributions were investigated by UV–Vis spectroscopy, Fourier transforms infrared (FTIR), scanning electron microscopy (SEM), differential scanning calorimeter (DSC), and Gwyddion software analysis.http://www.sciencedirect.com/science/article/pii/S1878535220302033Manganese dioxide nanoparticlesVernonia amygdalinaOptimization processD-optimal designPhysicochemical parametersSurface roughness
collection DOAJ
language English
format Article
sources DOAJ
author Yilkal Dessie
Sisay Tadesse
Rajalakshmanan Eswaramoorthy
spellingShingle Yilkal Dessie
Sisay Tadesse
Rajalakshmanan Eswaramoorthy
Physicochemical parameter influences and their optimization on the biosynthesis of MnO2 nanoparticles using Vernonia amygdalina leaf extract
Arabian Journal of Chemistry
Manganese dioxide nanoparticles
Vernonia amygdalina
Optimization process
D-optimal design
Physicochemical parameters
Surface roughness
author_facet Yilkal Dessie
Sisay Tadesse
Rajalakshmanan Eswaramoorthy
author_sort Yilkal Dessie
title Physicochemical parameter influences and their optimization on the biosynthesis of MnO2 nanoparticles using Vernonia amygdalina leaf extract
title_short Physicochemical parameter influences and their optimization on the biosynthesis of MnO2 nanoparticles using Vernonia amygdalina leaf extract
title_full Physicochemical parameter influences and their optimization on the biosynthesis of MnO2 nanoparticles using Vernonia amygdalina leaf extract
title_fullStr Physicochemical parameter influences and their optimization on the biosynthesis of MnO2 nanoparticles using Vernonia amygdalina leaf extract
title_full_unstemmed Physicochemical parameter influences and their optimization on the biosynthesis of MnO2 nanoparticles using Vernonia amygdalina leaf extract
title_sort physicochemical parameter influences and their optimization on the biosynthesis of mno2 nanoparticles using vernonia amygdalina leaf extract
publisher Elsevier
series Arabian Journal of Chemistry
issn 1878-5352
publishDate 2020-08-01
description The manganese dioxide nanoparticles (MnO2 NPs) were synthesized using Vernonia amygdalina leaf extract which was used as a reducing, capping, and stabilizing agents due to the presence of bioactive phytochemical compounds. Twenty five runs were designed to investigate the effect of V. amygdalina leaf extract ratio (A), initial potassium permanganate (KMnO4) concentration (B), pH (C), and reaction time (D) on the biosynthesized MnO2 NPs using 4-factor, 4-level D-Optimal Response Surface Quadratic Design Model approach. The relationship between physicochemical variables and absorption responses were established using transform second degree polynomial quadratic model. The effects of each absorption responses were analyzed by ANOVA principle using quadratic equations. A very low p-values (<0.0001), non-significant Lack of Fit F-values, and reasonable regression coefficient values (coefficient R2 = 0.9790, adjusted R2 = 0.9496, and predicted R2 = 0.8452) suggested that there is an effective correlation between experimental results and predicted values. Numerical and graphical optimized results demonstrated that the optimized conditions for the predicted absorbance at 320 nm (1.095) were suggested at 43.72%, 1.81 mM, 6.02, and 103.42 min for V. amygdalina leaf extract ratio, initial KMnO4 concentration, pH, and reaction time, respectively. Under these optimal conditions, the average absorbance from four experimental run was recorded to be 0.9678. This result was very closest to the predicted values. The average size elucidated by X-ray diffraction (XRD) analysis was found in the range between 20 nm and 22 nm. The stretching/or and vibrational, surface topography, thermal, and surface roughness as well as its porosity distributions were investigated by UV–Vis spectroscopy, Fourier transforms infrared (FTIR), scanning electron microscopy (SEM), differential scanning calorimeter (DSC), and Gwyddion software analysis.
topic Manganese dioxide nanoparticles
Vernonia amygdalina
Optimization process
D-optimal design
Physicochemical parameters
Surface roughness
url http://www.sciencedirect.com/science/article/pii/S1878535220302033
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