Results and Discussion
Catalyst Characterisation The catalysts were characterised by SEM and FTIR to determine the structure and morphology of the catalysts , the presence of their functional groups and the components present in the catalysts , to estimate the quality of the catalysts and to ensure that they were within the acceptable range . The catalysts were prepared by drying and calcinating sea sand at 900 ° C for three hours and then impregnating it with KOH for further testing .
The catalyst ( KOH / calcined sea sand ) was tested using SEM images to observe its surface morphology and texture . The SEM image is shown in Figure 4.1 with a magnification of 500x . The observation showed that the samples were amorphous , with some aggregates ( Muciño et al ., 2014b ). The figure also illustrated that some pores or cavities on the surface of the sand can act as an adsorbent ( Zaker et al ., 2013 ).
Based on Figure 3 , most peaks were observed between 800 to 3350cm -1 wavenumbers for the catalyst ( calcined sea sand + KOH ). A strong absorption peak was found at around 3346cm -1 due to O-H stretching of water molecules present in the interlayer region of montmorillonite . A peak at 2937cm -1 was due to C-H stretching , assigned to calcite . Strong bands at 1636cm -1 and 883cm -1 were assigned to Si-O asymmetric stretching vibrations , suggesting the presence of quartz in the samples ( Sivakumar et al ., 2012 ).
Optimisation of Biodiesel Table 1 shows biodiesel ' s predicted and experimental results using KOH / sea sand . The green catalyst was optimised to determine the optimum yield of biodiesel . Table 1 also indicates the result of 13 experiments done in triplicate using Response Surface Methodology ( RSM ). A model for the experimental design was fitted using Design Expert 6.0.8 ( Stat-Ease Inc ., USA ).
The final equation in terms of ( coded factors ) experimental data is shown in Equation 2 .
Table 2 showed ANOVA for the response surface quadratic model . The model F-value of 244.22 implies that the model is significant . There is only a 0.01 % chance that a " Model F-value " this large could occur due to noise . Values of " Prob > F " less than 0.0500 indicate model terms are significant . In this case , A 2 and B 2 are significant model terms . A value greater than 0.1000 indicates that the model terms are not significant . If there are many significant model terms ( not counting those required to support the hierarchy ), model reduction may improve the model . The " Lack of Fit Value " of 2.03 implies the Lack of Fit is not significant relative to the pure error . There is a 25.17 % chance that a " Lack of Fit " this large could occur due to noise . No significant Lack of Fit is good since the Fit Model is needed .
" The R-squared " value of 0.9943 is in reasonable agreement with " Adj R-Squared " of 0.9902 . " Adeq Precision " measures the signal-tonoise ratio . A ratio greater than 4 is desirable . A ratio of 41.749 indicates an adequate signal . This model can be used to navigate the design space . The model ' s goodness to fit was checked by using the determination coefficient ( R 2 ). In this case , the value of R 2 ( 0.9943 ) is closer to 1 , denoting a better correlation between the observed and predicted responses . The results from the central composite design were fitted to an equation to explain the relationship of the amount of catalysts used on the FAME yield conversion .
Effect of the amount of catalysts on FAME yields conversion Figure 3 represents the interaction effect of calcined sea sand and KOH on biodiesel yield . The composition of the catalyst will enhance biodiesel production by determining the highest FAME yield production . As illustrated in Figure 3 , it showed that 1wt % of KOH and 1wt % of sea sand gave the highest FAME yield conversion of 76.7 %. Transesterifikasi ( 2018 ) studied and concluded that a 7wt % loading amount of catalysts with a 2:1 clamshell to sea sand ratio produced the highest FAME yield of 75.3 % ( Transesterifikasi , 2018 ). Increasing the loading amount from 1 to 5wt % reduced the yield , due to excess alkaline catalyst loading that could result in soap formation and thus decrease biodiesel yield . Therefore , it can be concluded that the optimum amount of catalyst for biodiesel production that gave the higher FAME yield conversion was 1:1 KOH : sea sand ratio , fixing other parameters such as reaction temperature ( 65 º C ), reaction time ( three hours ) and methanol : oil ratio ( 1:15 ) throughout the experiment ( Chouhan & Sarma , 2011 ; Thangaraj et al ., 2019 ).
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