Using RSM to optimize crystallite size of rice husk derived graphene prepared by microwave process
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Abstract
In this research work, the optimization of the microwave process is done for the preparation of graphene from rice husk using RSM (Response Surface Methodology) as the graphene has exceptional qualities and is highly used in many industrial applications. The experiments are designed by using Box-Behnken Design (BBD) approach. The characterization of prepared graphene is done by Field Emission Scanning Electron Microscopy (FESEM), UV–Visible spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), X-ray powder diffraction (XRD), etc. The best root to find good quality graphene is the objective of this research. Weight of Ferrocene (gm), rice husk powder (gm), and Furnace Temperature (°C) is selected as input variables within the range of 20-60 gm, 40-80 gm, and 600-800 °C, respectively. The satisfactory correlation between experimental and predictable data is described by a higher value R2 (0.9979). The obtained optimized minimum crystallite size of graphene is 32.72 nm. The optimized parametric conditions to minimize the crystalline size are at a Weight of ferrocene 57.86 gm, Rice husk powder 79.15 gm, and Furnace temperature of 792.58 °C. The characterization, prediction, and process optimization are made. The validated model confirms that the model can prepare graphene particles from paddy product rice husk. The prediction and optimization of the process parameters are made to synthesize graphene from rice husk. RSM is used as a statistical technique to obtain a quadratic model for the response. As graphene's properties mainly depend upon the size of the particle. So, the prediction of the crystalline size is made by this RSM technique.
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