One-step conversion of acidified oil to biodiesel by novel bifunctional SrZr1-xFexO3 catalyst

Yujiao Zhang, Shengli Niu, Sunwen Xia, Sitong Liu and Jisen Liu

Renewable Energy, 2023, vol. 217, issue C

Abstract: The novel heterogeneous catalysts of SrZr1-xFexO3 (x = 0, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30 or 0.40) with acid-base bifunctional property are prepared through the sol-gel method and applied in catalyzing transesterification and esterification from acidified oil to produce biodiesel. The substitution of Zr by Fe in the SrZrO3 perovskite results in the lattice distortion to generate abundant surface oxygen vacancies. Also, the enhancement of electron density on active sites improves the acidity and basicity of catalyst to construct the acid-base pair sites for high efficiency of biodiesel production. The SrZr0.75Fe0.25O3 catalyst shows the strongest catalytic activity and the maximum FAME yield of 99.5% is achieved at the reaction temperature of 178 °C, catalyst amount of 4.5 wt%, methanol to oil molar ratio of 19:1 and reaction duration of 3.4 h through optimizing reaction parameters by convolutional neural network. The catalyst exhibits strong acid resistance and the FAME yield of 93.9% is achieved with 30 wt% oleic acid addition, where methanol is readily adsorbed to Sr site for transesterification and free fatty acids are readily adsorbed to Fe site for esterification. In addition, the SrZr0.75Fe0.25O3 catalyst shows satisfactory reusability and the FAME yield of 96.2% is maintained for the fifth reused cycle.

Keywords: Biodiesel; Transesterification; Free fatty acids; Convolutional neural network; Density functional theory (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:217:y:2023:i:c:s0960148123010534

DOI: 10.1016/j.renene.2023.119139

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