Combined Characterization of Scanning Electron Microscopy, Pore and Crack Analysis System, and Gas Adsorption on Pore Structure of Coal with Different Volatilization
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摘要: 为了定量表征煤的孔隙结构，研究煤孔隙特征与吸附性能的内在联系，采用低温液氮吸附法（LP-N2GA）、CO2吸附法、扫描电镜（SEM）和孔隙-裂隙分析系统（PCAS）对6种不同变质程度煤样进行孔隙相关分析.煤样孔隙分布相似时，煤样对N2和CO2的吸附能力、孔隙率的近似概率密度和孔隙面积（中孔）与煤的挥发分呈负相关，煤样孔隙的分形维数与煤的挥发分呈正相关.煤样的孔隙分布差异较大时，煤样对N2和CO2的最大吸附容量与孔隙分布有关.建立了煤纳米孔结构的联合表征模式，该表征模式能够更有效地研究和分析煤中的孔隙，包括孔隙数目、孔隙面积、孔隙周长、平均形状因子、孔隙率、分形维数和孔径分布，将SEM-PCAS与气体吸附方法相结合对煤的孔隙结构进行定量联合表征的模式是可行的.Abstract: The coal nanopore structure's common characterization pattern is established by the LP-N2GA method, CO2 adsorption method, SEM-PCAS, and the pore characteristics of six coals with different metamorphic degrees are analyzed. The characterization model enables us to study and analyze the pores in coal more effectively, including pore number, pore area, pore perimeter, average shape factor, porosity, fractal dimension, and pore size distribution. When the pore distribution of coal samples is similar, the adsorption capacity of coal for N2 and CO2, the approximate probability density of porosity and pore area (mesopore) of coal samples are negatively correlated with the volatile matter of coal, and the fractal dimension of the pore of coal samples is positively correlated with the volatile matter of coal. When the pore distribution of coal samples is quite different, the maximum adsorption capacity of N2 and CO2 is related to the pore distribution. The combination of SEM-PCAS and gas adsorption technology facilitates the understanding of the pore characteristics of coal. The research results have specific guiding significance for coal mine gas control.
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图 5 六种煤样CO2和N2的最大吸附量
Fig. 5. Maximum adsorption volumes of CO2 and N2 for six coal samples
图 6 六种煤样的孔径分布(CO2吸附实验)
Fig. 6. Pore size distribution of the samples (CO2 adsorption experiment)
图 7 1号煤样SEM原始图像和PCAS处理后图像
Fig. 7. No.1 coal sample SEM original image and PCAS processed image
图 8 2号煤样SEM原始图像和PCAS处理后图像
Fig. 8. No.2 coal sample SEM original image and PCAS processed image
图 9 3号煤样SEM原始图像和PCAS处理后图像
Fig. 9. No.3 coal sample SEM original image and PCAS processed image
图 10 4号煤样SEM原始图像和PCAS处理后图像
Fig. 10. No.4 coal sample SEM original image and PCAS processed image
图 11 5号煤样SEM原始图像和PCAS处理后图像
Fig. 11. No.5 coal sample SEM original image and PCAS processed image
图 12 6号煤样SEM原始图像和PCAS处理后图像
Fig. 12. No.6 coal sample SEM original image and PCAS processed image
图 14 煤样孔隙面积的近似概率密度函数
Fig. 14. Approximate probability density function of pore area of the coal sample
图 15 孔隙形状因子随孔隙面积的近似函数
Fig. 15. Approximate function of pore form factor with pore area
表 1 测试煤样的基本信息
Table 1. Necessary information on the tested coal samples
样品编号 煤阶 煤样工业分析 Mad (%) Aad (%) Vdaf (%) FCad (%) 1 无烟煤 1.51 28.36 7.70 62.98 2 低挥发性烟煤 1.83 16.61 11.29 70.78 3 低挥发性烟煤 0.66 14.24 11.73 73.54 4 低挥发性烟煤 0.66 8.20 18.57 72.74 5 中挥发性烟煤 0.81 14.9 28.05 56.59 6 高挥发性烟煤 4.77 3.30 32.24 60.81 
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表 2 测试煤样的基本信息
Table 2. Necessary information on test coal samples
样品编号 孔隙数 平均面积/像素 平均周长/像素 平均形状因子 分形维数 孔隙率(%) 1 1 382 109.12 33.73 0.588 1 1.308 9 13.13 2 493 170.81 46.55 0.589 1 1.296 2 7.33 3 1 391 63.71 31.27 0.584 5 1.288 3 7.71 4 1 266 40.74 27.31 0.603 7 1.344 1 4.49 5 343 44.79 33.75 0.577 1 1.407 0 1.34 6 958 51.43 30.93 0.606 8 1.277 4 4.29
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表 3 3、4、5号煤样的实验结果
Table 3. Experimental results of 3, 4 and 5 coal samples
样品编号 N2的最大吸附量（cm3/g, @STP） CO2的最大吸附量（cm3/g, @STP） 孔隙率（%） 分形维数 中孔面积的近似概率密度 
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