Analytical optimization of biodiesel synthesis from seasonal mixed seed oils using Bara Gokhru nano-biocatalyst

Q1 Environmental Science
S. Santhosh Kumar , Ajith J. Kings , L.R. Monisha Miriam , S. Jothibasu
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引用次数: 0

Abstract

Hevea brasiliensis, Madhuca longifolia, Millettia pinnata, Bombax ceiba, and Poinciana regia, ensuring a consistent year-round supply of extraction of oils and are then blended in different ratios and analyzed. A biocatalyst derived from Bara Gokhru undergoes separation, with SiO2 nanoparticles isolated and characterized. Response surface methodology was optimized the process parameters such as 0.35 (v/v) methanol/oil ratio, 7 wt% nano-biocatalyst, 900 rpm speed, and 70 °C heating for 175 min process to achieve 95 % biodiesel. The results were again optimized through following techniques: feed forward back propagation network, cascade-forward back propagation network, Elman back propagation network, and layer recurrent neural network to predict an optimized value. Recoverable methanol and catalyst enhance cost-effectiveness and promotes environmental sustainability, with the catalyst successfully reused five times. The right proportions such as 57.03 % saturated, 28.36 % monounsaturated and 13.49 % polyunsaturated fatty acids were ensured the compatibility of biodiesel which, leads large-scale production with industrial standards.

Abstract Image

Bara Gokhru纳米生物催化剂用于季节性混合种子油合成生物柴油的分析优化
巴西橡胶树,长叶麻,千穗草,棉铃草和王木,确保全年稳定的油提取供应,然后按不同比例混合并分析。从Bara Gokhru中分离出一种生物催化剂,分离出SiO2纳米颗粒并对其进行了表征。响应面法优化了工艺参数:0.35 (v/v)甲醇/油比、7 wt%纳米生物催化剂、900 rpm转速、70℃加热175 min,可获得95%的生物柴油。通过前馈反传播网络、级联前向反传播网络、Elman反传播网络和层递归神经网络对结果再次进行优化,预测出最优值。可回收甲醇和催化剂提高了成本效益,促进了环境的可持续性,催化剂成功重复使用了五次。饱和脂肪酸比例为57.03%,单不饱和脂肪酸比例为28.36%,多不饱和脂肪酸比例为13.49%,保证了生物柴油的相容性,达到了规模化生产和工业标准。
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来源期刊
Bioresource Technology Reports
Bioresource Technology Reports Environmental Science-Environmental Engineering
CiteScore
7.20
自引率
0.00%
发文量
390
审稿时长
28 days
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