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基于超声萃取的煤自燃关键基团测定及风险预测

Determination of Key Groups of Coal Spontaneous Combustion and Risk Prediction Based on Ultrasonic Extraction.

作者信息

Lu Guoju, Zhao Guofei, Yu Liya, Zhang Meihong, Wang Xiaoli

机构信息

Department of Safety Engineering, Shanxi Institute of Energy, Jinzhong 030600, China.

出版信息

ACS Omega. 2024 Dec 18;9(52):51525-51535. doi: 10.1021/acsomega.4c09010. eCollection 2024 Dec 31.

Abstract

In order to accurately investigate the key microstructures in the spontaneous combustion exothermic process of coal, an ultrasonic extraction method was employed to extract the coal, and the complex microscopic groups within it were stripped and studied. On this basis, Fourier transform infrared spectroscopy and differential scanning calorimetry were employed to assess the content of microscopic groups and the exothermic characteristics of the raw and extracted coal samples. The findings indicated that toluene and methanol demonstrated a notable capacity for extracting aromatic and aliphatic hydrocarbon compounds from coal, whereas -methyl pyrrolidone (NMP) and ethylenediamine (EDA) exhibited a pronounced effect on oxygen-containing functional groups and hydroxyl groups. The heat flow curves and spontaneous combustion risk indices of the extracted coal samples were reduced to varying degrees, and the coal-oxygen reaction was suppressed. The order of the coal samples' spontaneous combustion risk indices was E-EDA, E-NMP, E-methanol, and E-toluene, with the latter having the lowest value. The effects of -OH-a and oxygen-containing functional groups on the spontaneous combustion exotherm of the coal samples were greater. The Pearson correlation coefficient method was employed to identify the key groups with the highest correlation with the risk indices of coal. These were found to be -CH- and -OH-a, respectively. A multivariate linear regression model for predicting the spontaneous combustion risk of coal was subsequently established. The results demonstrated that -CH- had a more significant effect on the spontaneous combustion risk index than that of -OH-a.

摘要

为了准确探究煤自燃放热过程中的关键微观结构,采用超声萃取法对煤进行萃取,剥离并研究其中的复杂微观基团。在此基础上,利用傅里叶变换红外光谱和差示扫描量热法评估原煤和萃取后煤样的微观基团含量及放热特性。结果表明,甲苯和甲醇对从煤中萃取出芳香烃和脂肪烃化合物具有显著能力,而N-甲基吡咯烷酮(NMP)和乙二胺(EDA)对含氧官能团和羟基有明显作用。萃取后煤样的热流曲线和自燃风险指数均有不同程度降低,煤氧反应受到抑制。煤样自燃风险指数顺序为E-EDA、E-NMP、E-甲醇、E-甲苯,后者数值最低。-OH-a和含氧官能团对煤样自燃放热的影响更大。采用皮尔逊相关系数法确定与煤风险指数相关性最高的关键基团,分别为-CH-和-OH-a。随后建立了预测煤自燃风险的多元线性回归模型。结果表明,-CH-对自燃风险指数的影响比-OH-a更显著。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/02ee/11696386/4131780490ff/ao4c09010_0001.jpg

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