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<p>The development of Fischer–Tropsch synthesis (FTS) catalysts with high activity and long-term stability remains a major challenge. In this study, an innovative strategy was proposed to design granular catalysts by promoting industrial alumina granules with Sn and Pt, followed using in-situ growth of a ZIF-67 coating. To assess Fischer–Tropsch performance, three catalyst systems were investigated: <b>(i)</b> ZIF-67(Co)/Al<sub>2</sub>O<sub>3</sub> granular catalyst (Sample 1), <b>(ii)</b> ZIF-67(Co)/Al<sub>2</sub>O<sub>3</sub> powder catalyst (Sample 2), and <b>(iii)</b> conventional Co/Al<sub>2</sub>O<sub>3</sub> granules (Sample 3). The results demonstrated that the in-situ synthesized ZIF-67(Co)/Sn–Pt–Al<sub>2</sub>O<sub>3</sub> granular catalyst exhibited higher CO conversion, enhanced selectivity toward heavy hydrocarbons (C₅⁺) and significantly improved stability during 100&#xa0;h of reaction. To analyze catalytic behavior, the experimental data were fitted using two semi-empirical kinetic models (GPLE1 and GPLE2) and a computational model based on an artificial neural network (ANN) developed in Python. For the ZIF-67/Al<sub>2</sub>O<sub>3</sub> granular systems, the ANN model achieved the highest accuracy with RMSE = 0.1 × 10<sup>−&#xa0;2</sup> and R<sup>2</sup> ≈ 0.95, whereas the predictive accuracy decreased for the promoted catalysts without MOF. These findings indicate that integrating innovative experimental approaches with advanced predictive modeling can provide a powerful strategy for the development of industrial FTS catalysts with high performance and long-term durability.</p> Graphical abstract <p></p>

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Integration of MOF-derived coating and noble metal promotion on granular supports: high-performance ZIF-67(Co)/Sn-Pt-Al2O3 catalysts for Fischer-Tropsch synthesis

  • 期刊论文

  • 发表日期：

    2026年6月24日

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  • Meysam Mirshekari,
  • Halime Kord-Tamandani,
  • Ali Akbar Mirzaei,
  • Ebrahim Mollashahi

摘要

The development of Fischer–Tropsch synthesis (FTS) catalysts with high activity and long-term stability remains a major challenge. In this study, an innovative strategy was proposed to design granular catalysts by promoting industrial alumina granules with Sn and Pt, followed using in-situ growth of a ZIF-67 coating. To assess Fischer–Tropsch performance, three catalyst systems were investigated: (i) ZIF-67(Co)/Al2O3 granular catalyst (Sample 1), (ii) ZIF-67(Co)/Al2O3 powder catalyst (Sample 2), and (iii) conventional Co/Al2O3 granules (Sample 3). The results demonstrated that the in-situ synthesized ZIF-67(Co)/Sn–Pt–Al2O3 granular catalyst exhibited higher CO conversion, enhanced selectivity toward heavy hydrocarbons (C₅⁺) and significantly improved stability during 100 h of reaction. To analyze catalytic behavior, the experimental data were fitted using two semi-empirical kinetic models (GPLE1 and GPLE2) and a computational model based on an artificial neural network (ANN) developed in Python. For the ZIF-67/Al2O3 granular systems, the ANN model achieved the highest accuracy with RMSE = 0.1 × 10− 2 and R2 ≈ 0.95, whereas the predictive accuracy decreased for the promoted catalysts without MOF. These findings indicate that integrating innovative experimental approaches with advanced predictive modeling can provide a powerful strategy for the development of industrial FTS catalysts with high performance and long-term durability.

Graphical abstract