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采用低压 CO₂ 和 N₂ 吸附法测定煤中纳米孔的适用性分析。

Applicability Analysis of Determination Models for Nanopores in Coal Using Low-Pressure CO₂ and N₂ Adsorption Methods.

机构信息

Institute of Resources and Environment, Henan Polytechnic University, Jiaozuo 454000, China.

State Key Laboratory of Coal and CBM Co-Ming, Shanxi Jicheng Anthracite Mining Group Co., LTD., Jicheng 048006, China.

出版信息

J Nanosci Nanotechnol. 2021 Jan 1;21(1):472-483. doi: 10.1166/jnn.2021.18464.

Abstract

The development characteristics of nanopores (with pore sizes <200 nm) in coal are a key factor affecting the accumulation and migration of coalbed methane (CBM). Thus, an appropriate determination method and calculation model are essential for accurate nanopore representation. Based on the experiments of low-pressure CO₂ adsorption (LP-CO₂GA) at 273 K and low-pressure N₂ adsorption (LP-N₂GA) at 77 K on four coals with different ranks, the abilities of different models (e.g., Langmuir, Dubinin-Radushkevich (D-R), Dubinin-Astakhov (D-A), Brunauer-Emmett-Teller (BET) and nonlocal density functional theory (NLDFT)) to accurately predict the pore parameters were analyzed. The results showed that (1) for LP-N₂GA, the Langmuir model is only suitable for gas adsorptions at low relative pressure conditions ( < 0.01), and its error value increased with the relative adsorption pressure. The fitting results of the D-R model showed good agreement with the D-A model under low relative pressure of LP-CO₂GA ( < 0.01), and the D-A model had more accurate fitting results. The BET model is more accurate than the other models (φ = -1.2733%) only in the interval of LP-N₂GA with 0.05 < < 0.35. The data also showed that the NLDFT model can maintain a higher fitting accuracy for LPCO₂/N₂GA processes at relative adsorption pressures from 0.001-0.9996. (2) Using LP-CO₂GA with the Langmuir, D-R, D-A, and NLDFT models, the micropore specific surface area (SSA; 66.9570-248.6736 m²/g) and pore volume (0.0201- 0.0997 cm³/g) were obtained, while the values of meso-/macropore SSA (0.0007-2.3398 m²/g) and pore volume (0.0036-0.04 cm³/g) were calculated by LP-N₂GA with the BET and NLDFT models. The results showed that the fitting accuracy in descending order was the D-R, D-A, Langmuir and NLDFT models. (3) In combination with the applicable model range, LP-CO₂GA with the NLDFT model was recommended for micropore analysis of the coal pore sizes from 0.36-1.1 nm, while LP-N₂GA combined with the NLDFT model was recommended for nanopore analysis of pore sizes from 1.1-200 nm. (4) The characteristics of pore development in the Beiloutian coal were analyzed using LP-CO₂/N₂GA combined with the NLDFT model. It was found that a pore volume and SSA less than 1.0 nm accounted for 88.82% of the total pore volume and 98.05% of the total SSA, indicating that micropores in coal are the main space for CBM storage and are key physical factors for the occurrence and migration of coalbed methane. The conclusions of this article will provide a basis for the accurate calculation of nanopores in coal.

摘要

煤中纳米孔(孔径 <200nm)的发育特征是影响煤层气(CBM)聚集和运移的关键因素。因此,准确表示纳米孔需要选择合适的测定方法和计算模型。本文基于四种不同煤级煤在 273K 下的低温 CO₂吸附(LP-CO₂GA)和 77K 下的低温 N₂吸附(LP-N₂GA)实验,分析了不同模型(如 Langmuir、Dubinin-Radushkevich(D-R)、Dubinin-Astakhov(D-A)、Brunauer-Emmett-Teller(BET)和非局部密度泛函理论(NLDFT))准确预测孔隙参数的能力。结果表明:(1)对于 LP-N₂GA,Langmuir 模型仅适用于相对压力较低(<0.01)的气体吸附,且随着相对吸附压力的增加,其误差值增大。在 LP-CO₂GA 的相对压力较低(<0.01)条件下,D-R 模型的拟合结果与 D-A 模型吻合较好,且 D-A 模型具有更准确的拟合结果。BET 模型在 LP-N₂GA 的 0.05< <0.35 范围内比其他模型(φ=-1.2733%)更准确。此外,数据还表明,NLDFT 模型在相对吸附压力为 0.001-0.9996 时,对 LPCO₂/N₂GA 过程具有较高的拟合精度。(2)利用 LP-CO₂GA 结合 Langmuir、D-R、D-A 和 NLDFT 模型,得到了微孔比表面积(SSA;66.9570-248.6736m²/g)和孔体积(0.0201-0.0997cm³/g),而 BET 和 NLDFT 模型则用于计算中孔/大孔的 SSA(0.0007-2.3398m²/g)和孔体积(0.0036-0.04cm³/g)。结果表明,拟合精度依次为 D-R、D-A、Langmuir 和 NLDFT 模型。(3)结合适用的模型范围,推荐使用 LP-CO₂GA 结合 NLDFT 模型进行煤孔 0.36-1.1nm 范围内的微孔分析,而 LP-N₂GA 结合 NLDFT 模型则推荐用于分析孔径为 1.1-200nm 的纳米孔。(4)利用 LP-CO₂/N₂GA 结合 NLDFT 模型对贝湖煤的孔发育特征进行了分析。结果表明,体积小于 1.0nm 的孔体积和 SSA 占总孔体积的 88.82%,占总 SSA 的 98.05%,表明煤中的微孔是 CBM 储存的主要空间,也是煤层气运移的关键物理因素。本文的结论将为煤中纳米孔的准确计算提供依据。

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