Integrating advanced fitting models with experimental catalysis to maximize H2 production in dry reforming using nickel on metalized-silica-alumina catalysts†

IF 5 3区 材料科学 Q2 CHEMISTRY, PHYSICAL Sustainable Energy & Fuels Pub Date : 2024-09-13 DOI:10.1039/D4SE00867G
Ahmed S. Al-Fatesh, Ahmed I. Osman, Ahmed A. Ibrahim, Yousef M. Alanazi, Anis H. Fakeeha, Ahmed E. Abasaeed and Fahad Saleh Almubaddel
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Abstract

This study explores the enhancement of hydrogen production via dry reforming of methane (DRM) using nickel catalysts supported on metalized silica-alumina. By incorporating noble metals (Ir, Pd, Pt, Ru, and Rh), we significantly improve the catalysts' reducibility, basicity, and resistance to coke deposition. Our novel approach integrates a predictive model combining advanced statistical and experimental techniques to optimize catalyst performance. The active site population derived from the reduction of the NiAl2O4 phase is found to be stable and least affected under oxidizing gas stream (CO2) as well as reducible gas stream (H2) during the DRM reaction. The catalyst system is characterized by surface area and porosity, X-ray diffraction, Raman spectroscopy, thermogravimetry analysis, XPS, TEM, and various temperature-programmed reduction/desorption techniques (TPR/CO2-TPD). Notably, the 5Ni/1IrSiAl catalyst shows reduced activity due to low reducibility and basicity, whereas the 5Ni/1RhSiAl catalyst demonstrates superior performance, achieving a hydrogen yield of 62% at 700 °C and 80% at 800 °C after 300 minutes. This enhancement is attributed to the highest edge of reducibility, the maximum concentration of stable active sites “Ni” (derived from NiAl2O4 during the DRM reaction), and the optimum concentration of moderate strength basic sites. Through the application of multiple response surface methodology and central composite design, we developed a predictive model that forecasts the optimal conditions for maximizing hydrogen yield, which was experimentally validated to achieve 95.4% hydrogen yield, closely aligning with the predicted 97.6%. This study not only provides insights into the mechanistic pathways facilitated by these catalysts but also demonstrates the efficacy of computational tools in optimizing catalytic performance for industrial applications.

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将先进的预测模型与实验催化相结合,优化使用金属化硅铝镍(Nickel on Metalized Silica-Alumina Catalysts)催化剂进行干转化过程中的₂氢生产
本研究探讨了使用金属化硅铝上支撑的镍催化剂通过甲烷干重整(DRM)提高制氢能力的问题。通过加入贵金属(Ir、Pd、Pt、Ru、Rh),我们显著提高了催化剂的还原性、碱性和抗焦炭沉积能力。我们的新方法整合了一个预测模型,结合先进的统计和实验技术来优化催化剂性能。在 DRM 反应过程中,通过还原 NiAl₂O₄相得到的活性位点群非常稳定,在氧化性气体流(CO2)和还原性气体流(H2)中受到的影响最小。通过表面积和孔隙率、X 射线衍射、拉曼光谱、热重分析、XPS、TEM 和各种温度编程还原/解吸技术(TPR/CO2-TPD)对催化剂体系进行了表征。值得注意的是,由于还原性和碱性较低,5Ni/1IrSiAl 催化剂的活性有所降低,而 5Ni/1RhSiAl 催化剂则表现出卓越的性能,300 分钟后,700°C 时的氢气产率达到 62%,800°C 时达到 80%。这种性能的提高归功于最高的还原性边缘、最大浓度的稳定活性位点 "Ni"(在 DRM 反应中来自 NiAl2O4)以及最佳浓度的中等强度碱性位点。通过应用多重响应面方法和中心复合设计,我们建立了一个预测模型,该模型预测了氢气产率最大化的最佳条件,经实验验证,氢气产率达到 95.4%,与预测的 97.6% 非常接近。这项研究不仅深入揭示了这些催化剂的机理途径,还证明了计算工具在优化工业应用催化性能方面的功效。
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来源期刊
Sustainable Energy & Fuels
Sustainable Energy & Fuels Energy-Energy Engineering and Power Technology
CiteScore
10.00
自引率
3.60%
发文量
394
期刊介绍: Sustainable Energy & Fuels will publish research that contributes to the development of sustainable energy technologies with a particular emphasis on new and next-generation technologies.
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