journal article·2026-06

Dual strategy of structural modulation and Al-doping for high-performance Fe/Al2O3 catalyst in methane decomposition

Lu Liu, Shenyong Ren, Chengshu Yao, Fubin Peng, Min Gu, Baojian Shen, Chunming Xu

Carbon· Volume 256
Publisher page

Abstract

Catalytic methane decomposition (CMD) is a versatile technique to produce green hydrogen and valuable nano-carbon materials. However, highly efficient catalysts still remain to be developed due to coking and metal sintering, which hinder the practical application of this technology. In this work, a dual strategy combining catalyst structural construction and active sites precise regulation was successfully developed to fabricate porous Al-doped Fe/Al2O3 catalysts with superior catalytic performance. By introducing cetyltrimethylammonium bromide (CTAB) during hydrothermal synthesis to regulate Al3+ doping within the α-Fe2O3 lattice, a porous structure and oxygen vacancies were induced in the catalyst. A synergistic mechanism was revealed through comprehensive characterization (BET, XRD, H2-TPR, XPS, and CH4-TPSR), showing that the CTAB-derived porous structure enhances mass transfer as the tailored reduction enables the coexistence of metallic Fe0 with residual Al-doped Fe3O4. The Al doping enhanced the interaction between Fe and Al2O3, suppressing excessive pre-reduction and yielding highly dispersed and firmly anchored Fe0 nanoparticles. During CMD reactions at 750°C, methane conversion of Al-doped Fe/Al2O3 catalyst reached 89%, with a deactivation factor of only 5% and a carbon yield of 595 wt.% over 3 hours. The anchored Fe0 facilitate the base-growth of carbon nanotubes (CNTs), whereas Fe3C promoted the tip-growth of bamboo-like CNTs, providing an effective route for simultaneous high-purity hydrogen production and controlled CNT synthesis.
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Research context

OpenAlex topics: Catalytic Processes in Materials Science · Catalysts for Methane Reforming · Catalysis and Oxidation Reactions

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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