Biodiesel production from acidic palm oil through transesterification catalyzed by Zn-doped BaTiO3 perovskite catalysts: Optimized by GA-BP

In this work, a series of Zn-doped BaTiO 3 catalysts were synthesized by the sol-gel method and applied to catalyze the transesterification of acidic palm oil with methanol for the biodiesel production. The maximum biodiesel yield was obtained for BaTiO 3 possessing a Zn stoichiometric coefficient of 0.15 and activated at 900 °C, designated as BTZO-0.15-900. The physicochemical properties of the catalysts were revealed by various characterization methods, including XRD, SEM-EDS, TEM, XPS, FTIR, BET, CO 2 -TPD, NH 3 -TPD and ICP-MS. The characterization results indicated that BTZO-0.15-900 was a mesoporous bifunctional catalyst, whose abundant oxygen vacancies significantly enhance its catalytic activity for the transesterification reaction. Subsequently, the Genetic Algorithm-Backpropagation (GA-BP) neural network was employed to optimize the BTZO-0.15-900 catalyzed transesterification parameters, where the maximum biodiesel yield of 97.6% was achieved under the optimal conditions of reaction temperature of 160.6 °C, catalyst amount of 5.8 wt%, methanol to oil molar ratio of 11.4:1 at a fixed reaction duration of 2 h. Moreover, the catalyst also exhibited excellent acid resistance and reusability. Specifically, it achieved a biodiesel yield of 80.6% from a high-acid-value feedstock (15.90 mg KOH/g), and maintained a high yield of 81.4% after the fifth reuse cycle. The quality of the produced biodiesel complied with EN 14214 and ASTM D6751 specifications, thereby affirming its commercial viability. • Zn-doped BaTiO 3 bifunctional catalysts were synthesized by sol-gel method. • BTZO-0.15-900 shows oxygen vacancies and mesoporous structure. • GA-BP neural network was applied to optimize transesterification parameters. • Maximum biodiesel yield of 97.6 % was obtained. • The catalyst exhibits the good acid resistance capability and stability.