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<p>The Gas-phase products generated by aliphatic hydrocarbon functional groups during the spontaneous combustion of coal represent a significant source of environmental pollution. A primary focus of contemporary research is the investigation of their microscopic reaction pathways and the dynamics of free radical transformations. This study examines the combustion and pyrolysis reaction mechanisms of three distinct aliphatic hydrocarbon functional groups utilising the Machine Learning Potential Molecular Dynamics (ML potential MD) method, with validation conducted through thermogravimetric-Fourier transform infrared spectroscopy (TG-FTIR) and in-situ FTIR experiments. The findings suggest that the reactivity of the ‒CH group is the highest, followed by ‒CH<sub>2</sub>, while ‒CH<sub>3</sub> exhibits the greatest stability. The ‒CH functional group exhibits the highest tendency for CH<sub>4</sub> produced, the ‒CH<sub>2</sub> group displays the highest tendency for CO<sub>2</sub> produced, and the ‒CH<sub>3</sub> group demonstrates the highest tendency for H<sub>2</sub>O and CO produced. The ·O radical plays a pivotal role in promoting combustion in the oxidative combustion of functional groups, while both the ·HO radical and the ·H radical act as key initiators in this process. These findings offer theoretical insights into mitigating carbon emissions from the perspective of functional groups and free radicals.</p>

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Study on combustion reaction products and free radicals of aliphatic hydrocarbon functional groups in coal based on ML potential MD

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月24日

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  • Jinzhang Jia,
  • Yumo Wu,
  • Dan Zhao,
  • Fengxiao Wang,
  • Dongming Wang,
  • Qiang Yang,
  • Yinghuan Xing

摘要

The Gas-phase products generated by aliphatic hydrocarbon functional groups during the spontaneous combustion of coal represent a significant source of environmental pollution. A primary focus of contemporary research is the investigation of their microscopic reaction pathways and the dynamics of free radical transformations. This study examines the combustion and pyrolysis reaction mechanisms of three distinct aliphatic hydrocarbon functional groups utilising the Machine Learning Potential Molecular Dynamics (ML potential MD) method, with validation conducted through thermogravimetric-Fourier transform infrared spectroscopy (TG-FTIR) and in-situ FTIR experiments. The findings suggest that the reactivity of the ‒CH group is the highest, followed by ‒CH2, while ‒CH3 exhibits the greatest stability. The ‒CH functional group exhibits the highest tendency for CH4 produced, the ‒CH2 group displays the highest tendency for CO2 produced, and the ‒CH3 group demonstrates the highest tendency for H2O and CO produced. The ·O radical plays a pivotal role in promoting combustion in the oxidative combustion of functional groups, while both the ·HO radical and the ·H radical act as key initiators in this process. These findings offer theoretical insights into mitigating carbon emissions from the perspective of functional groups and free radicals.