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Hydrogen generation mechanism of oil-rich coal oxidation in low temperature

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  • Wang, Kai
  • Ding, Jiayou
  • Deng, Jun
  • Zhai, Xiaowei
  • Zhang, Yanni

Abstract

This study aims to elucidate the microscopic mechanism of hydrogen generation from characteristic groups during the low-temperature oxidation of oil-rich coal. FTIR experiments were employed to investigate the changes in characteristic groups with temperature, while quantum chemical simulation was utilized to analyze the reaction characteristics and hydrogen production pathways of hydrogen-rich groups. The results indicate that the characteristic groups associated with H2 production include aromatic hydrocarbon side chains, carboxyl groups, aldehyde groups, and hydroxyl groups. Two hydrogen production reaction processes, propyl side chain and allyl side chain, were delineated, revealing that the reactivity of allyl side chain is greater than that of propyl side chain. The primary mechanism of H2 production involves the initial oxygen attack on the methylene structure of both the propyl and allyl side chains in the coal molecule, generating hydroxyl, carboxyl, and aldehyde groups as intermediate products. Subsequently, the hydrogen radical attracts the hydrogen atom on the oxygen atom, leading to O–H bond cleavage, and the combination of two hydrogen radicals forms H2.

Suggested Citation

  • Wang, Kai & Ding, Jiayou & Deng, Jun & Zhai, Xiaowei & Zhang, Yanni, 2024. "Hydrogen generation mechanism of oil-rich coal oxidation in low temperature," Energy, Elsevier, vol. 293(C).
    • Handle: RePEc:eee:energy:v:293:y:2024:i:c:s0360544224005115
    DOI: 10.1016/j.energy.2024.130739
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    References listed on IDEAS

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    1. Wang, Kai & Hu, Lihong & Deng, Jun & Zhang, Yanni & Zhang, Jiaxin, 2023. "Inhibiting effect and mechanism of polyethylene glycol - Citric acid on coal spontaneous combustion," Energy, Elsevier, vol. 275(C).
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    3. Bai, Zujin & Deng, Jun & Wang, Caiping & Hou, Yanan & Zhang, Yanni & Kang, Furu & Ramakrishna, Seeram, 2023. "Study on the mechanism of lignite oxidation inhibition by antioxidant resveratrol," Energy, Elsevier, vol. 273(C).
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    1. Wang, Kai & Huang, Hao & Deng, Jun & Zhang, Yanni & Wang, Qun, 2024. "A spatio-temporal temperature prediction model for coal spontaneous combustion based on back propagation neural network," Energy, Elsevier, vol. 294(C).

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