article · Arabian Journal of Chemistry
Manganese dioxide nanoparticles have been produced using an extract from Vernonia amygdalina leaves, which provided the phytochemicals required for reducing, capping, and stabilising the material. A four-factor statistical model evaluated how leaf extract ratio, potassium permanganate concentration, pH, and reaction time affected nanoparticle formation across twenty-five experimental runs. Statistical analysis confirmed a close alignment between the predicted values and experimental results. The ideal synthesis conditions were established as a 43.72 percent extract ratio, 1.81 millimolar precursor concentration, a pH of 6.02, and a reaction time of roughly 103 minutes. Under these parameters, the synthesized nanoparticles demonstrated an average crystallite size between 20 and 22 nanometres. Additional physical and chemical testing verified the optical properties, surface topography, thermal characteristics, surface roughness, and porosity distributions of the resulting nanomaterial.
Using plant extracts instead of harsh chemicals provides a cleaner, biological route for nanomaterial manufacturing. Pinpointing the precise chemical and physical parameters required for biosynthesis allows researchers to maximise yields, control particle size, and ensure reliable batch-to-batch consistency without relying on hazardous synthetic reagents.
The abstract does not indicate an application pathway or specific commercial use for the produced nanoparticles.
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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.
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DOI: 10.1016/j.arabjc.2020.06.006
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