Abstract
This study presents a sustainable approach for mitigating greenhouse gas emissions by converting methane (CH4) and carbon dioxide (CO2) into syngas using nickel-based catalysts supported on hexagonal boron nitride (hBN), synthesized through chemical vapor deposition (CVD). Characterization of the 4 wt% Ni/hBN catalyst, conducted using high-resolution techniques such as X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM), revealed quasi-spherical nickel particles with an average diameter of 37 nm and a calculated dispersion of 10.5%. At 700°C, this catalyst achieved conversions of 78% for CH4 and 80% for CO2, outperforming the 12 wt% Ni/γ-Al2O3 (FCR-4) catalyst by about 20%. It also displayed excellent coke resistance, with a carbon deposition rate of 2.5 mg C/(g_cat h), half that of FCR-4, and a noteworthy 30% reduction in activation energy, from 21.4 to 15.0 kJ/mol. The hydrogen yield reached 74%, a 37% increase over FCR-4, with an H2/CO ratio of 0.96, indicating its suitability for Fischer–Tropsch processes. Furthermore, a Fe-Ni/hBN catalyst was developed through selective deposition of 1% Fe onto the Ni/hBN support by establishing a temperature window of 140–200°C, determined by gas chromatography (GC) and confirmed by high-resolution transmission electron microscopy (HRTEM). This catalyst variant demonstrated minimal coke formation at 600°C, achieving CH4 and CO2 conversions of 44% and 49%, respectively, comparable to FCR-4, while maintaining superior stability against alternative catalysts. Overall, the low acidity and high thermal stability of hBN, along with CVD control over particle size and dispersion, highlight its potential for efficient dry reforming of methane (DRM) under optimized conditions.
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Garmejani, B. M., Mehravar, S., & Fatemi, S. (2026). CVD-Engineered Ni and FeNi Catalysts on Hexagonal Boron Nitride for Efficient CO2-Methane Co-Conversion to Syngas: High-Performance Alternatives to Traditional Alumina-Supported Catalysts. International Journal of Energy Research, 2026(1). https://doi.org/10.1155/er/5520777
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