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Microwave-accelerated hydrolysis for hydrogen production over a cobalt-loaded multi-walled carbon nanotube-magnetite composite catalyst

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Listed:
  • Luo, Chunlin
  • Liu, Shuai
  • Yang, Gang
  • Jiang, Peng
  • Luo, Xiang
  • Chen, Yipei
  • Xu, Mengxia
  • Lester, Edward
  • Wu, Tao

Abstract

Microwave (MW) irradiation is a promising option for the intensification of chemical reaction processes and has been applied in the promotion of many catalytic reactions. Herein, the (CNTs-Fe3O4)-Co nanocomposites were designed as microwave-responsive catalysts and was fabricated under a controlled manner. The experimental results showed that MW irradiation can lead to the hydrogen generation rate (HGR) of the (CNTs-Fe3O4)(1:4)-Co (10 wt%) catalyst being boosted from 75.0 to 95.4% as compared with conventional heating under the temperature range of 40 to 60℃. Moreover, the evaluation of the catalytic performance of the (CNTs-Fe3O4)(1:4) composite with different Co loadings and DFT calculations were carried out to verify the synergistic effect of cobalt and Fe3O4 sites of the (CNTs-Fe3O4)(1:4)-Co (10 wt%) catalyst. Furthermore, the pre-exponential factor (A) of NaBH4 hydrolysis under MW heating was found to be approximately 15 times higher than that of conventional heating, implying that MW irradiation significantly improved the effective collision frequency of the atoms at the reaction interface of the catalyst, resulting in a higher number of active sites on the surface of the (CNTs-Fe3O4)(1:4)-Co (10 wt%) catalyst. Additionally, the existence of the non-thermal effect of MW irradiation was studied by using a specially designed experimental set-up. The results showed that MW thermal and non-thermal effects contributed to the enhancement of HGR.

Suggested Citation

  • Luo, Chunlin & Liu, Shuai & Yang, Gang & Jiang, Peng & Luo, Xiang & Chen, Yipei & Xu, Mengxia & Lester, Edward & Wu, Tao, 2023. "Microwave-accelerated hydrolysis for hydrogen production over a cobalt-loaded multi-walled carbon nanotube-magnetite composite catalyst," Applied Energy, Elsevier, vol. 333(C).
    • Handle: RePEc:eee:appene:v:333:y:2023:i:c:s0306261922017950
    DOI: 10.1016/j.apenergy.2022.120538
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    References listed on IDEAS

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    1. Teimouri, Zahra & Abatzoglou, Nicolas & Dalai, Ajay K., 2024. "A novel machine learning framework for designing high-performance catalysts for production of clean liquid fuels through Fischer-Tropsch synthesis," Energy, Elsevier, vol. 289(C).

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