“…The presence of 20.2 % calcite magnesium in the raw sample can be traced to the contamination of calcite with magnesium [ 25 , 26 ]. The peaks of the XRD profile of CaO derived from waste chicken eggshell, commercial CaO, and impregnated CaO appeared at the vicinity of 2 value of 35 which confirms the presence of CaO [ 21 , 27 ]. Figure 6 XRD profile of (a) raw, (b) boiled, and (c) calcined chicken eggshells.…”
Section: Resultsmentioning
confidence: 90%
“…The high value of the pore radius suggests that the particle size of the eggshell powder should be further pulverized from the current 75 μm and reduced to nano-size for better catalytic activity. However, commercial CaO impregnated with aqueous potassium iodide solution and calcined was found to have BET surface area of 5.66 m 2 /g [ 27 ] while commercial CaO modified with bromooctane/hexane solution recorded 68.6 m 2 /g [ 22 ]. This was attributed to better surface exfoliation when compared with CaO derived from waste chicken eggshells.…”
Researchers have shown considerable interest in finding a sustainable, low cost, and readily available substitute for the commercial calcium oxide (CaO) catalyst. In this work, raw chicken eggshell was modified by boiling and calcination at 900 C for 3 h. The x-ray diffraction characterization revealed that while the proportion of CaCO 3 in the raw and boiled samples was found to be 79.3 % and 99.2 % respectively, the CaCO 3 had been converted to 63.8 % CaO and CO 2 in the calcined sample. This was due to the thermal decomposition during calcination. The outcome of the infrared spectroscopy showed that the raw and boiled chicken eggshell presented a similar absorption profile with peaks at 1 394 cm À1 , 873 cm À1 , and 712 cm À1 , which were as a result of the presence of asymmetric stretch, out-of-plane bend, and in-plane bend vibration modes. The major peaks presented by the calcined sample at 3642 cm À1 can be attributed to the OAH stretching vibration and bending hydroxyl groups present in Ca(OH) 2 . The Brunauer-Emmett-Teller surface areas for the raw, boiled and calcined chicken eggshell were found to be 2.33 m 2 /g, 3.26 m 2 /g, and 4.6 m 2 /g respectively, indicating increased catalytic activity of the calcined sample. Overall, boiling was found to have a negligible effect on the chicken eggshell, while hightemperature calcination greatly affected the pore size, surface area, composition, and thermal decomposition profile of the chicken eggshell sample.
“…The presence of 20.2 % calcite magnesium in the raw sample can be traced to the contamination of calcite with magnesium [ 25 , 26 ]. The peaks of the XRD profile of CaO derived from waste chicken eggshell, commercial CaO, and impregnated CaO appeared at the vicinity of 2 value of 35 which confirms the presence of CaO [ 21 , 27 ]. Figure 6 XRD profile of (a) raw, (b) boiled, and (c) calcined chicken eggshells.…”
Section: Resultsmentioning
confidence: 90%
“…The high value of the pore radius suggests that the particle size of the eggshell powder should be further pulverized from the current 75 μm and reduced to nano-size for better catalytic activity. However, commercial CaO impregnated with aqueous potassium iodide solution and calcined was found to have BET surface area of 5.66 m 2 /g [ 27 ] while commercial CaO modified with bromooctane/hexane solution recorded 68.6 m 2 /g [ 22 ]. This was attributed to better surface exfoliation when compared with CaO derived from waste chicken eggshells.…”
Researchers have shown considerable interest in finding a sustainable, low cost, and readily available substitute for the commercial calcium oxide (CaO) catalyst. In this work, raw chicken eggshell was modified by boiling and calcination at 900 C for 3 h. The x-ray diffraction characterization revealed that while the proportion of CaCO 3 in the raw and boiled samples was found to be 79.3 % and 99.2 % respectively, the CaCO 3 had been converted to 63.8 % CaO and CO 2 in the calcined sample. This was due to the thermal decomposition during calcination. The outcome of the infrared spectroscopy showed that the raw and boiled chicken eggshell presented a similar absorption profile with peaks at 1 394 cm À1 , 873 cm À1 , and 712 cm À1 , which were as a result of the presence of asymmetric stretch, out-of-plane bend, and in-plane bend vibration modes. The major peaks presented by the calcined sample at 3642 cm À1 can be attributed to the OAH stretching vibration and bending hydroxyl groups present in Ca(OH) 2 . The Brunauer-Emmett-Teller surface areas for the raw, boiled and calcined chicken eggshell were found to be 2.33 m 2 /g, 3.26 m 2 /g, and 4.6 m 2 /g respectively, indicating increased catalytic activity of the calcined sample. Overall, boiling was found to have a negligible effect on the chicken eggshell, while hightemperature calcination greatly affected the pore size, surface area, composition, and thermal decomposition profile of the chicken eggshell sample.
“…Recent studies proposed that calcium oxide (CaO) derived from various wastes and the impregnation of CaO with different compounds as one of the best heterogeneous catalysts which can be effectively used for producing biodiesel [23][24][25] from waste frying oil and pongamia oil. Catalyst activity, reusability, loading, low cost are the major advantages of using calcium oxide as the catalyst [16].…”
In the present study, Calcium oxide (CaO) obtained from eggshells has been used as a heterogeneous catalyst for biodiesel production from highly viscous non-edible rubber seed oil (RSO). Characterization of synthesized catalyst was done with the help of scanning electron microscope equipped with Energy dispersive spectrometry (SEM-EDS), X-ray diffraction (XRD) and Fourier transform Infrared spectroscopy (FTIR). Response surface methodology (RSM) with central composite design (CCD) was used to optimize the process parameters and 1H-NMR (Nuclear Magnetic Resonance) spectroscopy analysis was performed to find the conversion of RSO to biodiesel. A conversion of 99.7% of RSO to biodiesel was obtained at 12:1 methanol to oil molar ratio, 4 (wt%) of catalyst, and 3 hour reaction time with a quadratic regression model of R2 of value 0.9566 was obtained. The composition of prepared biodiesel is estimated with the help of Gas Chromatogram-Mass Spectroscopy (GC-MS) analysis. Artificial Neural Network (ANN) with Levenberg-Marquardt algorithm was also trained to predict biodiesel conversion and the value of R2 obtained was 0.9976. It was observed that predicted conversion values from ANN were better when compared to prediction using RSM.
“…Excess methanol present in the FAME is removed by rotary evaporation, and the percentage of final purified product was analyzed using 1 H‐NMR (nuclear magnetic resonance) spectrum (Model: Bruker 500 MHz) using CDCl 3 as solvent. was used for calculating the percentage conversion …”
Biodiesel production by transesterification of rubber seed oil (RSO) using calcium oxide (CaO) derived from calcined limestone as a heterogeneous catalyst is presented in this study. Optimization of process parameters affecting the conversion of RSO to biodiesel is done by design of experiments (DOE) and an effective comparison of two different optimization methods, namely, response surface methodology (RSM) and artificial neural networks (ANN) is presented. A high conversion of 95.2% was obtained at 12:1 methanol: Oil molar ratio, 4 (wt%) catalyst and 5 hr of reaction time. The proposed design model of RSM is found to fit well with the predicted conversion and with molar ratio and reaction time as the significant process parameters affecting the conversion. Best validation performance of 8.8991 occurred at epoch 4 with a mean square error (MSE) of 1.55 in ANN model trained with Levenberg-Marquardt algorithm. By comparing the predicted coefficient of determination, R 2 , values of 0.8452 obtained by using RSM, and 0.9939 obtained by using ANN for biodiesel conversion, it is concluded that ANN model is the best model for predicting the percentage conversion of RSO to biodiesel with minimum error between experimental and predicted values. K E Y W O R D S artificial neural networks, biodiesel, limestone, optimization, response surface methodology, transesterification
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