Simulated study on CH4 adsorption by Shanxi gas-fat coal at different moisture contents

Context To investigate the impact of moisture on gas adsorption in gas-fat coal, Shanxi gas-fat coal was chosen as the research subject. The Adsorption module within molecular simulation software was utilized to construct gas-fat coal models with moisture contents of 0%, 1.14%, 2.26%, and 3.72%. The...

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Published inJournal of molecular modeling Vol. 29; no. 11; p. 334
Main Authors Wang, Lin, Chen, Xiangjun, Wang, Dezhang, Wang, Xiaodan
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2023
Springer Nature B.V
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Summary:Context To investigate the impact of moisture on gas adsorption in gas-fat coal, Shanxi gas-fat coal was chosen as the research subject. The Adsorption module within molecular simulation software was utilized to construct gas-fat coal models with moisture contents of 0%, 1.14%, 2.26%, and 3.72%. The results revealed that the isothermal adsorption curves of gas-fat coal under different moisture contents all followed the Langmuir adsorption curve (Type Ι), wherein the Langmuir volume of gas-fat coal was most sensitive to changes in moisture content within the range of 0 to 1.14%. A linear equation was found to better characterize the influence of moisture on gas content in Shanxi gas-fat coal, represented by the formula η  = 1/(1 + 1.98078 w ), where, η represents the moisture impact coefficient; w is the moisture content; 1.98078 is the coefficient of moisture influence of Shanxi gasifier coal. Coupled with changes in the surface free energy of gas-fat coal, the pressure exerted a positive effect on the adsorption of gas on the coal surface, enhancing the adsorption space of methane within gas-fat coal. Methods Using Materials Studio software, the adsorption capacity and adsorption heat of methane were computed at various temperatures (323 K, 333 K, 343 K) and pressures (0.5–8 MPa). Furthermore, a comparative analysis was conducted to assess the applicability of classical linear equations, linear equations, power function equations, and exponential function equations in quantitatively characterizing the influence of moisture.
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ISSN:1610-2940
0948-5023
0948-5023
DOI:10.1007/s00894-023-05733-y