期刊
SUSTAINABILITY
卷 10, 期 3, 页码 -出版社
MDPI
DOI: 10.3390/su10030707
关键词
artificial neural network; biodiesel; heterogeneous catalyst; modeling; optimization; transesterification
资金
- Cape Peninsula University of Technology (CPUT)
The present work was aimed at assessing the possible use of ripe plantain fruit peel as a green-base catalyst in synthesizing Azadirachta indica oil methyl esters (AIOME). The free fatty acid content of the oil (5.81 wt %) was initially reduced to 0.90 wt % using methanol: oil at 2.19 v/v, Fe-2(SO4)(3) at 6 wt %, time of 15 min and temperature of 65 degrees C. The pretreated oil was converted to AIOME in a transesterification process with calcined ripe plantain peel ash (CRPPA) at 700 degrees C as catalyst. The process was modeled by artificial neural network and optimized using genetic algorithm. The effectiveness of the developed CRPPA is ascribable to its high K content and microstructural transformation. The reliability of the model obtained was confirmed with a high coefficient of determination (R-2) of 0.996 and a low mean relative percentage deviation (MRPD) of 8.10%. The best operating variables combination for the process was methanol: oil of 0.73 v/v, CRPPA of 0.65 wt % and time of 57 min while the temperature was kept constant at 65 degrees C with a corresponding AIOME yield of 99.2 wt %. The results of this work demonstrated the potentials of ripe plantain peels and neem oil as cheap feedstocks for biodiesel production.
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