Changes in mineral fraction and pore morphology of coal with acidification treatment: contribution of clay minerals to methane adsorption

Wang, Liang; Li, Ziwei; Li, Jing; Chen, Yinchang; Zhang, Kaizhong; Han, Xiwei; Xu, Guangwei

doi:10.1007/s11356-023-30414-x

Cited by 7 publications

(3 citation statements)

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“…Take the PSD as an example; DFT-CO 2 covers 0.3−1.47 nm, DFT-N 2 spans 0.9−33 nm, and BJH-N 2 analyzes within 2−300 nm. 38 The BJH method is more reliable for analyzing PSDs with a size range of 10−300 nm; however, it underestimates pore sizes of <10 nm by 20− 30%. 38 By taking advantage of the QSDFT method and considering factors such as surface roughness and anisotropy, BJH and DFT theories can be reasonably applied in stages to characterize the mesopore.…”

Section: Results and Analysesmentioning

confidence: 99%

“…38 The BJH method is more reliable for analyzing PSDs with a size range of 10−300 nm; however, it underestimates pore sizes of <10 nm by 20− 30%. 38 By taking advantage of the QSDFT method and considering factors such as surface roughness and anisotropy, BJH and DFT theories can be reasonably applied in stages to characterize the mesopore. Therefore, the full pore size range of PSD consists of 0.35−1.5 nm from DFT−CO 2 , 1.5−10 nm from DFT-N 2 , and 10−300 nm from BJH-N 2 .…”

Section: Results and Analysesmentioning

confidence: 99%

“…Currently, various analytical methods for analyzing low-pressure physical adsorption offer specific testing ranges and applications. Take the PSD as an example; DFT-CO 2 covers 0.3–1.47 nm, DFT-N 2 spans 0.9–33 nm, and BJH-N 2 analyzes within 2–300 nm . The BJH method is more reliable for analyzing PSDs with a size range of 10–300 nm; however, it underestimates pore sizes of <10 nm by 20–30% .…”

Section: Results and Analysesmentioning

confidence: 99%

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Fractal Analysis of Coal Pore Structure Based on Low-Pressure Gas Adsorption and Its Influence on Methane Adsorption Capacity: A Perspective from Micropore Filling Model

Wang,

Wu,

Han

et al. 2024

Energy Fuels

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Understanding pore structure heterogeneity is crucial for gaining insights into the occurrence, transport, and recovery of methane from the coal stratum. The pore structure of coal directly affects the spatial distribution of methane in coal. The influence of the pore structure on methane adsorption has attracted considerable research attention, primarily because of the multiscale characteristics of the pore system and its diverse adsorption behaviors. This study analyzes fractal characteristics to reveal the heterogeneity of the pore structure and pore surface via lowpressure gas adsorption experiments. An adsorption capacity calculation model based on micropore filling is applied and validated by using CH 4 isothermal adsorption experiments. Furthermore, the variation in gas adsorption with fractal dimensions is studied via correlation analysis. Results show that high-rank coal exhibits well-developed micropores with larger micropore fractal dimensions than low-rank coal, and low-rank coal exhibits more meso/macropores and higher meso/macropore fractal dimensions than high-rank coal. The fractal dimensions of meso/macropores and micropores could describe the surface and the volumetric properties of pore structure, respectively. The micropore filling model based on the pore structure can be used to quantitatively calculate the methane adsorption capacity of coal, with errors of −32.6, 2.9, 3.2, and 14.3%. This offers significant advantages over the monolayer adsorption hypothesis in understanding the adsorption behavior of coal. The fractal dimensions of the pore structure are positively correlated with the adsorption capacity in each adsorption form, with correlation coefficients of 0.792 and 0.842 in meso/macropores and 0.821 and 0.743 in micropores, respectively. Because most methane molecules are stored in micropores, the fractal dimensions of micropores play a critical role in governing the methane adsorption capacity of coal. These findings hold substantial implications for understanding the mechanisms that influence methane occurrence in coal under diverse geological conditions, contributing to subsequently assessing the risk of coal and gas outbursts and estimating coalbed methane resources.

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Section: Results and Analysesmentioning

confidence: 99%

Section: Results and Analysesmentioning

confidence: 99%

Section: Results and Analysesmentioning

confidence: 99%

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