Unraveling methane adsorption mechanisms in tectonically deformed coal: coupling roles of fissure width, deformation degree, and molecular structure

Tectonically deformed coal (TDC) is widely distributed in major coalbed methane (CBM) producing areas in China, and its fissure-like pore structure is a key factor regulating methane adsorption-desorption behavior. To clarify the coupling mechanism of fissure width, tectonic deformation degree, and methane adsorption, three brittle TDC samples with different deformation intensities (Tunlan: weakly deformed, TL; Malan: moderately deformed, ML; Jining: strongly deformed, JN) from the Xishan Coalfield were selected. Fourier Transform Infrared Spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and ¹³C nuclear magnetic resonance (¹³C-NMR) were used to characterize molecular structures, and molecular dynamics (MD) simulations were performed to investigate methane adsorption in 2 nm, 5 nm, and 10 nm fissure-like pores under 298 K, 328 K, 358 K, and 0–20 MPa. The results show that fissure width and pressure synergistically regulate adsorption energy distribution. Narrow fissures (2 nm) show multi-peak distribution (molecular crowding effect), while wide fissures (10 nm) exhibit single stable peaks; increasing pressure reduces energy dispersion by 44% (5 nm pore, 5→20 MPa) and enhances adsorption stability. Deformation degree controls adsorption capacity via pore structure evolution. ML (moderate deformation) has the highest capacity (multi-scale pore connectivity), TL (weak deformation) shows limited high-pressure growth (isolated large pores), and JN (strong deformation) has the lowest capacity (fragmented narrow fissures and trap adsorption). A unified “multi-scale pore-fracture synergy adsorption mechanism” is proposed, integrating isolated, synergistic, and trap adsorption as context-dependent manifestations. This study provides a theoretical basis for efficient CBM development in TDC reservoirs by revealing the quantitative coupling relationship between structural factors and methane adsorption.

1 Introduction

Tectonically deformed coal (TDC) is formed by fragmentation, crumpling, mylonitization, and other deformation processes of coal bodies under intense tectonic stress. It is widely developed in major coalbed methane (CBM) producing areas in North China and South China, such as the Qinshui Basin in Shanxi Province and the Liupanshui mining area in Guizhou Province. Compared with primary structural coal, the pore structure of TDC shows significant differences (Hao et al., 2022; Jiang et al., 2016). It is characterized by fissure-like pores as the main storage space, with a complex distribution of pore sizes ranging from nanoscale micropores to micrometer-scale fractures. These structural features, including increased specific surface area, enhanced pore connectivity, and surface functional group enrichment, directly lead to strong methane adsorption capacity and low desorption-diffusion efficiency, which is supported by former experimental and simulation studies (Zhang et al., 2022; Wang X. L. et al., 2023). For example, Zhang et al. (2022) confirmed that TDC’s micropore enrichment enhances adsorption potential (Zhang et al., 2022), while Li F. L. et al. (2023) demonstrated that fragmented pore structures (strong deformation) inhibit methane diffusion, reducing desorption efficiency (Li F. L. et al., 2022).

As a key factor controlling gas content and productivity in TDC reservoirs, the correlation between methane adsorption behavior and the size of fissure-like pores (especially pore width) has long been a research hotspot in the field of unconventional natural gas development. On one hand, the width of fissure-like pores affects the adsorption capacity and stability of methane by regulating the superposition effect of van der Waals forces on the wall, the density of adsorption sites, and the molecular diffusion path (Li F. L. et al., 2022; Kang et al., 2023; Li X. S. et al., 2022)^. On the other hand, different types of tectonically deformed coal (such as fragmented coal, granulated coal, and mylonitic coal) exhibit significant differences in the development degree (e.g., density, connectivity) and surface properties (e.g., functional group distribution, roughness) of fissure-like pores due to variations in deformation intensity, which may lead to differences in methane adsorption mechanisms (Nakagawa et al., 2000; Cohaut et al., 2001). For example, mylonitic coal, which forms a large number of nanoscale slit pores due to intense plastic deformation, generally has a significantly higher adsorption capacity than fragmented coal. However, the quantitative laws and microscopic mechanisms behind this difference remain unclear. In the field of research on the pore structure of TDC, extensive research efforts, both domestically and internationally, have contributed to significant progress in this field (Nakagawa et al., 2000; Cohaut et al., 2001; Wang H. et al., 2023; Dong et al., 2023; Du et al., 2024). Foreign research started relatively early. Nakagawa et al. (2000) pioneered the use of small-angle X-ray scattering (SAXS) to quantitatively analyze the fractal dimension of the micropore surface in lignite, laying the foundation for subsequent studies on pore structure. Cohaut et al. (2001) used SAXS to investigate the evolution of porosity in anthracite under different temperatures, revealing the mechanism by which thermal evolution affects the pore structure. Over the past decade, molecular dynamics simulation has become a research hotspot. Wang H. et al. (2023) constructed a coal macromolecular model to simulate changes in pore structure under compressive stress, and found that increasing stress leads to a decrease in pore volume, specific surface area, and connectivity, with the pore size distribution shifting toward smaller pore sizes, thus profoundly explaining the modification process of pore structure by mechanical effects. Dong et al. (2023) used field emission scanning electron microscopy (FESEM) combined with image analysis technology to visually characterize the pore morphology and distribution of tectonically deformed coal with different deformation degrees, and found that as the deformation degree increases, the pore shape becomes more complex and the directional arrangement characteristics become more obvious. Du et al. (2024) took TDC in the Huainan and Huaibei areas as samples, and comprehensively used high-resolution transmission electron microscopy, atomic force microscopy, and nuclear magnetic resonance to systematically analyze the evolutionary characteristics of the nanoscale pore structure of TDC under different deformation mechanisms (brittle and ductile deformation). The study showed that ductile deformed coal is dominated by submicropores (2–5 nm) and ultramicropores (<2 nm), with many open small pores and a large specific surface area of pores; while brittle deformed coal is dominated by micropores (5–10 nm) and transitional pores (10–100 nm), with a relatively high proportion of closed pores. Li et al. (2011) studied the pore characteristics of different types of tectonically deformed coal using SAXS and low-temperature nitrogen adsorption experiments, and pointed out that with the increase of tectonic deformation degree, the proportion of micropores in coal increases, the most probable pore size decreases, and the fractal dimension of the pore surface increases, indicating that deformation promotes the complexity of coal pores at the microscopic level. Zou and Qin (2016) conducted an in-depth analysis of the fractal characteristics of tectonically deformed coal pores through mercury intrusion experiments and fractal theory, and found that the fractal dimension of tectonically deformed coal pores is negatively correlated with permeability, further revealing the influence mechanism of pore structure on fluid transport performance.

In terms of research on methane adsorption characteristics in TDC, scholars have mostly used molecular simulation methods to explore the adsorption mechanism in depth. For example, through grand canonical Monte Carlo simulation, Du et al. (2024) analyzed the influence of factors such as pore size and surface properties on methane adsorption capacity and adsorption heat, and found that the width of slit-like pores has a significant impact on methane adsorption capacity, with a peak adsorption capacity within a specific range of slit width. Moreover, Sakurovs et al. (2012) found that the methane adsorption capacity of TDC is significantly positively correlated with its micropore volume, and the adsorption potential of TDC of different coal ranks differs significantly, with the adsorption potential of low-rank TDC being relatively low and gradually increasing with the increase of coal rank. Zhou et al. (2015) used quantum chemical calculations to study the influence of coal surface functional groups on methane adsorption, and found that oxygen-containing functional groups can enhance the adsorption of methane by coal, providing a new perspective for understanding the adsorption mechanism at the molecular level.

Currently, molecular simulation technology has become an effective means to reveal the mechanism of methane adsorption at the pore scale (Zhang et al., 2023; Han et al., 2021). By constructing accurate coal molecular models and fissure-like pore systems, it can quantitatively analyze the influence of parameters such as fissure width and surface energy on adsorption isotherms, adsorption layer density, and adsorption energy. Qiu et al. (2024) studied the synergistic effect of temperature and pressure on methane adsorption in tectonically deformed coal through molecular simulation, and found that high pressure can offset the reduction of adsorption capacity caused by high temperature to a certain extent, providing a reference for predicting gas content in tectonically deformed coal under different geological conditions. Xie et al. (2023) adopted a combination of molecular dynamics and quantum chemistry to study the inhibition mechanism of moisture on methane adsorption in tectonically deformed coal, revealing the changes in adsorption characteristics under the interaction of multiple factors. However, current research still has limitations. On the one hand, there are few comparative studies on methane adsorption characteristics of fissure-like pores in different types of tectonically deformed coal, and the research on the coupling relationship between fissure width-tectonic type-adsorption capacity needs to be further deepened. Moreover, the fit between the molecular simulation model and the actual tectonically deformed coal needs to be improved to more accurately reflect the complexity and diversity of the pore structure of tectonically deformed coal. It should be emphasized that the simplification of pore structure in molecular simulation is a common challenge in current TDC-related research. The real TDC pore structure is a multi-scale, heterogeneous system integrating micropores, mesopores, macropores, and fractures, with complex features such as tortuosity, roughness, and random connectivity. Moreover, the arbitrary nature of simulated pore structure mainly stems from the difficulty in quantitatively characterizing the three-dimensional spatial distribution of real TDC pores. Although advanced characterization techniques (e.g., μm CT) can provide partial structural information, reconstructing a fully realistic pore model for molecular simulation is still limited by computational power and data integrity.

To understand the occurrence state of methane in graphene pores and compare the effects of different pore sizes, temperatures and pressures on the occurrence state of methane in the pores, pore sizes of 2nm, 5 nm and 10nm, with the simulation pressure range of 0–20 MPa and the simulation temperature of 298K,328K,358K. The simulated fissure-like pores in this study is a necessary trade-off between model operability and mechanism clarity, aiming to eliminate interference from excessive structural complexity and focus on clarifying the core coupling mechanism between single factors (e.g., fissure width) and adsorption behavior.

2 Samples and methods

2.1 Sample preparation

The samples collected in this study are mainly from the Tunlan (TL), Jining (JN), and Malan (ML) Mining Area of the Xishan Coalfield in Taiyuan, among which TL, ML, and JN coals are all brittle deformed coals. To quantitatively characterize the deformation degree of the samples, three key parameters were selected for comprehensive evaluation: fracture density (number of fractures per unit area, ρ), fracture width (average width of fractures, w), and coal block integrity (ratio of intact block volume to total sample volume, I). The quantitative evaluation formula of deformation intensity index (DII) was established as follows: DII = 0.4 × (ρ/ρ₀) + 0.3 × (w/w₀) + 0.3 × (1-I/I₀), where ρ₀ = 5 fractures/cm², w₀ = 0.1 mm, and I₀ = 1.0 are the standard reference values. The test results show that the DII values of TL, ML, and JN samples are 0.32 ± 0.03, 0.67 ± 0.05, and 0.91 ± 0.04, respectively. The deformation degrees of the three coal samples from weak to strong are as follows: Tunlan coal, Malan coal, and Jining coal (Table 1).

Table 1

Table 1. Quantitative evaluation results of macroscopic deformation degree of samples.

Samples were crushed and ground to 200 mesh for proximate and ultimate analyses. 10 g of the ground sample was weighed into a beaker, and an excess mixture of HCl and HF solutions was slowly added. The mixture was stirred with a stirrer for 8 h and pickled repeatedly 3 times to ensure the removal of impurity minerals. The sample was separated by a centrifuge and rinsed with deionized water until no precipitation was detected with AgNO₃ solution. The demineralized sample was filtered with filter paper, then dried in an oven at 60 °C for 8 h, taken out and placed in a dark brown sample bottle for later use.

2.2 Methods

The Fourier Transform Infrared Spectroscopy (FTIR) test was conducted using a Nicolet 6,700 infrared spectrometer manufactured by Thermo Fisher (USA), with a resolution of 4 cm^-1, a cumulative scanning number of 32 times, and a measured spectral range of 400–4,000 cm^-1. X-ray photoelectron spectroscopy (XPS) was performed using a PHI Quantera SXM X-ray photoelectron spectrometer manufactured by ULVAC-PHI, Japan. A hemispherical energy analyzer was used, with an Al target, an X-ray beam spot of 200 μm, a pass energy of 55 eV, a step size of 0.1 eV, an incident angle of 45°, and the vacuum degree of the analysis chamber was better than 1.0 × 10⁻⁷ Torr. A scanning Ar⁺ gun was employed, and the standard sample was thermally oxidized SiO₂/Si. Nuclear magnetic resonance carbon spectroscopy (¹³C-NMR) was conducted using a Bruker AV300 nuclear magnetic resonance spectrometer with a 4 mm probe. The rotation speed was 12 kHz, the nuclear magnetic resonance frequency was 75.47 MHz, the recycle delay was 5 s, and the number of scans ranged from 2000 to 4,000. To obtain an ideal spectrum, cross-polarization (CP), magic angle spinning, and TOSS (total suppression of sidebands) techniques were employed, with a contact time of 3 m and a spectral width of 30,000 Hz. Materials Studio 2023 was selected as the main simulation platform, which integrates grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) modules, enabling efficient construction, calculation and result visualization of pore adsorption systems. Its advantage lies in supporting batch operations of complex molecular models and accurately calculating intermolecular forces and diffusion coefficients through the Forcite module, which has been widely applied in the research on coal-gas interactions (Li X. S. et al., 2022; Yasue et al., 2025). The COMPASS III force field was used to describe intermolecular interactions. This force field has been optimized for non-bonding interactions (van der Waals forces and electrostatic forces) between organic molecules and gas molecules, allowing accurate simulation of the adsorption energy and diffusion behavior of CH₄ molecules in coal pores. The parameter settings referred to the coal molecular simulation research by Zou and Qin (2016). During the simulation, the insertion and deletion of CH₄ under specific temperature and pressure conditions were calculated using the GCMC method. The simulation was carried out for 10⁷ steps with a time step of 1fs.

3 Results and discussion

3.1 Molecular structure characteristics and model construction

The FTIR spectra of the samples are shown in Figure 1. According to previous research results, the main absorption bands of aromatic structures are 750 cm^-1, 820 cm^-1, 870 cm^-1, and 1,600 cm^-1; the main absorption bands of alkane structures are 1,460 cm^-1, 2,860 cm^-1, and 2,930 cm^-1; the main absorption bands of oxygen-containing groups are 1,000–1,300 cm^-1 and 1700 cm^-1 (Wang et al., 2024; Murata et al., 2000; Hassid et al., 2022). The relative intensities of these groups directly reflect, to a certain extent, the relative abundances of aliphatic carbon structures, aromatic carbon structures, and oxygen-containing groups in the studied sample molecules. From the results of spectral fitting processing for each stage, it can be seen that the aromatic structures in sample TL (Figures 1a–d) are mainly dominated by trisubstituted benzene rings. The aliphatic hydrocarbons contained are mainly asymmetric methylene functional groups. There is an obvious absorption peak between 3,300–3,500 cm^-1, which is attributed to hydroxyl-ether oxygen bonds or self-associated hydroxyl groups, and is of little significance for model construction. Both sample ML (Figures 1e–h) and JN (Figures 1i–l) have a large number of trisubstituted, pent substituted, and disubstituted benzene rings, and the aliphatic hydrocarbons are mainly asymmetric methylene groups.

Figure 1

Figure 1. FTIR spectra of TDC samples. (a–d) TL sample; (e–h) ML sample; (i–l) JN sample.

According to the XPS results, in sample TL (Figures 2a–d), the C element is mainly aromatic structures and their substituted structural carbons; the oxygen element is mainly phenolic hydroxyl and ether oxygen groups; the nitrogen element is dominated by quaternary nitrogen, followed by pyridine-type nitrogen; and the organic sulfur is mainly sulfoxide-type sulfur. In sample ML(Figures 2e–h), it is mainly composed of aromatic structural carbons and phenolic or ether carbons; the oxygen element is mainly carboxyl oxygen; the nitrogen element consists of quaternary nitrogen and pyridine-type nitrogen; and the organic sulfur is mainly sulfoxide-type sulfur. Sample JN (Figures 2i–l), is mainly aromatic structural carbons; the oxygen element mainly includes carbonyl oxygen, phenolic hydroxyl, and ether oxygen groups; the nitrogen element is composed of quaternary nitrogen and pyridine-type nitrogen; the sulfur element is mainly inorganic sulfur, with very little organic sulfur.

Figure 2

Figure 2. XPS spectra of TDC samples. (a–d) TL sample; (e–h) ML sample; (i–l) JN sample.

The chemical shifts in ¹³C-NMR spectrum are divided into three regions: the aliphatic carbon region at δ = 0–90 ppm, the aromatic carbon region at δ = 90–165 ppm, and the carboxyl carbon region at δ = 165–220 ppm (Lv et al., 2024). As can be seen from the results (Figure 3), the aromatic carbon region accounts for the largest area in the ¹³C-NMR spectrum of the samples, while the areas of the aliphatic carbon region and carboxyl carbon region are relatively smaller. It is concluded that the aromatic hydrocarbon structure should account for the largest proportion in the molecular structure, and the remaining aliphatic carbons and carboxyl carbons appear as units connecting the aromatic structures. This conclusion is consistent with that obtained from the FTIR test.

Figure 3

Figure 3. ¹³C-NMR spectra of TDC samples. (a) TL sample; (b) ML sample; (c) JN sample.

A macromolecular model of sample TL (C₁₉₀H₁₆₀O₂₅N₂) was constructed based on the proximate and ultimate analyses, XPS, and ¹³C-NMR, as shown in Figure 4. The cross-linking bonds between aromatic rings in this model are mainly short alkane bonds, and the model contains hydroxyl groups, carboxyl groups, methoxy groups, carbonyl groups, ether groups, and cyclic structures containing O and N elements. Five coal macromolecular models were added to a periodic simulation box, and the system was optimized using annealing molecular dynamics and isothermal-isobaric molecular dynamics simulation methods to construct a porous structure model of sample TL, as shown in Figure 4a. It can be found that in the model, the five coal macromolecules are cross-linked with each other to form a complex porous structure. The optimized model has a size of 26.56 Å × 26.56 Å × 26.56 Å and a density of 1.21 g/cm³. Using the above method, a macromolecular model of sample ML (C₂₂₇H₂₀₁O₂₁NS) was constructed, as shown in Figure 4b. The optimized model has a size of 30.2 Å × 30.2 Å × 30.2 Å and a density of 1.11 g/cm³. Figure 4c shows the macromolecular model of sample JN (C₂₂₆H₂₁₂O₂₀N₂). The optimized model has a size of 29.5 Å × 29.5 Å × 29.5 Å and a density of 1.02 g/cm³.

Figure 4

Figure 4. Macromolecular models of samples. (a) TL sample; (b) ML sample; (c) JN sample.

3.2 CH₄ occurrence in fissure-like organic pores

The adsorption state of CH₄ in fissure-like pores of different sizes was simulated by constructing such pores (Figure 5). It shows the occurrence state of methane in 5 nm pore slits under different pressures. It can be seen that under the different pressure conditions, the distribution of CH₄ in graphene pore slits is mainly very dense near the pore walls and becomes scattered away from the pore walls. In the free space far from the pore walls, the distribution of methane is relatively uniform, and the closer to the pore walls, the denser the distribution. The number of methane molecules both at the graphene pore walls and in the free space increases with the increase of pressure, but the increase rate of methane molecules in the free space is slower than that at the pore walls. At the same time, because methane molecules are continuously undergoing molecular thermal motion in the pores, the state of methane molecules shown in the figure is in dynamic equilibrium, that is, the number of methane molecules at the pore walls is constantly increasing and decreasing, and the two are in a relatively balanced state. Therefore, the distribution state of methane molecules at the pore walls can be observed.

Figure 5

Figure 5. Evolution of CH₄ adsorption site distribution in fissure-like pores in the stacked state at 298K.

3.2.1 Difference of CH₄ adsorption intensity distribution

As can be seen from Figure 6, the adsorption energy distribution curves of methane in different pores/fractures under varying pressures indicate that the distribution characteristics are synergistically regulated by fracture width and pressure: narrower fractures result in wider energy distribution peaks with multi-peak features; for the same fracture width, increasing pressure reduces the dispersion of energy states, and the peak shape shrinks into a narrow single peak. The energy distribution of the 2 nm narrow fracture ranges from −8 to +6 kcal/mol (peak width 14 kcal/mol) with three distinct secondary peaks, indicating multiple adsorption states of methane; the distribution of the 10 nm wide fracture shrinks to −4∼+2 kcal/mol (peak width 6 kcal/mol) with only one main peak (half-peak width 1.8 kcal/mol), showing that the adsorption state tends to be singular and stable. ​For the same fracture width (e.g., 5 nm), when pressure increases from 5 MPa to 20 MPa, the half-peak width of the main peak decreases from 3.2 kcal/mol to 1.8 kcal/mol (a 44% reduction), and the main peak shifts toward lower energy, indicating that high pressure promotes close packing of molecules and enhances adsorption stability.​

Figure 6

Figure 6. Distribution curves of CH₄ adsorption energy under different pressures in (a) 2 nm, (b) 5 nm and (c) 10 nmpore slits.

The curves mostly show double peaks, reflecting the multi-layer adsorption of methane in pores/fractures. With increasing pressure, the main peak height decreases and shifts leftward (energy absolute value increases), indicating that methane transfers from high-energy adsorption sites to low-energy ones (low-pressure adsorption states are less stable). As pore size increases, the main peak shifts rightward and secondary peaks appear to the left of the main peak, suggesting that adsorption site energy rises in larger pores, and smaller pores have stronger adsorption capacity (methane preferentially adsorbs in smaller pores). The multi-peak feature of the 2 nm narrow pore from the “molecular crowding effect”: spatial constraints restrict molecular arrangement, and competition between fracture wall forces and intermolecular repulsion leads to significant differences in adsorption energy (consistent with the nano-pore adsorption state differentiation theory proposed by Simon et al. (Simon et al., 2023). In wide pore, molecular arrangement is close to the bulk phase with uniform forces, thus showing a single peak.

3.2.2 Evolution of CH₄ adsorption site distribution

Through the digital image visualization analysis of CH₄ adsorption distribution under constant pressure conditions for different pore sizes (Figure 7). Taking 5 MPa as an example, the CH₄ adsorption distribution shows significant differences with the increase in pore size. In the 2 mm small-sized pore, the CH₄ adsorption area presents a continuous and concentrated high-concentration distribution (with a high proportion of red and orange in the chromatogram). This reflects that small-sized pore, due to their large specific surface area and strong constraints from pore throats, have a more prominent ability to adsorb and capture methane molecules, making it easy for adsorbed methane to form a coherent distribution within the pore. However, when the pore size increases to 5 mm and 10 mm, the high-concentration adsorption areas gradually become discrete and their range narrows (e.g., in 10 mm pore-fractures under 5 MPa, only sporadic adsorption signals exist in the edge areas). That is directly related to the size effect: in small-sized pores, the stress transmission and molecular diffusion paths are shorter, and methane molecules are more directly affected by the adsorption potential of the pore walls, making it easy to form a continuous adsorption phase. In large-sized pores, the internal space is open, molecular diffusion is weakly constrained by the boundaries, and the inhibition of adsorption by inhomogeneities in the pores (such as mineral filling and interference from secondary pores) is enhanced, resulting in a dispersed adsorption distribution.

Figure 7

Figure 7. Comparison of CH₄ adsorption intensity distribution in fissure-like pores under different pressures.

Comparing the adsorption distributions under different pressures for the same pore size (taking 2 mm pore-fractures as an example), the “strengthening effect” of increasing pressure on methane adsorption is clearly distinguishable. Under the low pressure of 5 MPa, the high-concentration adsorption area in 2 mm pores is limited; when the pressure rises to 10 MPa, the adsorption area expands rapidly and connects; when the pressure reaches 20 MPa, the high-concentration adsorption area almost covers the entire pore (with the proportion of dark colors in the chromatogram exceeding 80%) (Javadpour et al., 2007; Jun et al., 2017). This is because pressure acts as the “driving force” for methane molecules (Jun et al., 2017). As the pressure increases, the thermal motion of methane molecules is inhibited, the gas partial pressure in the pores rises, and more methane molecules break through the diffusion resistance to enter the pores and combine with the adsorption sites on the pore wall surfaces (Zimmerman and Bodvarsson, 1996). Extending to 5 mm and 10 mm pores, the strengthening effect of pressure shows gradient differences: the adsorption distribution in 5 mm pores tends to be coherent only after the pressure reaches 15 MPa, while in 10 mm pores, the high-concentration adsorption area expands significantly only when the pressure reaches 20 MPa. This indicates that large-sized pores have a “threshold effect” in their response to pressure-due to the large free space in the pores and the high initial diffusion resistance of CH₄ molecules, a higher pressure is required to break the adsorption-desorption equilibrium and promote the filling of CH₄ molecules in the pores (Xu and Guo, 2014; Bustin and Clarkson, 1998). This pressure-size coupling response is essentially the synergistic effect of pore geometric constraints and CH₄ molecular dynamics: small-sized pores rely on “adsorption potential dominance” and can be driven to adsorb under low pressure; large-sized pores are dominated by “diffusion resistance” and require high pressure to break through the constraints.

3.3 CH₄ adsorption in TDC samples

As Figure 8 shows, the molecular framework of sample TL (weakly deformed sample, DII = 0.32 ± 0.03) mainly maintains its original stretched morphology, forming locally concentrated large pores (bloc-like blue distribution). Although pore connectivity is poor, the molecular framework has high integrity, resulting in a strong adsorption potential field. Moderate deformation (DII = 0.67 ± 0.05) induces cracking, constructing a multi-scale pore network (wide-spread blue areas) in sample ML (moderately deformed sample). It contains micropores and mesopores. Severe deformation causes fragmentation and reconstruction of the molecular framework in sample JN (strongly deformed sample, DII = 0.91 ± 0.04), forming numerous isolated tiny pores (scattered blue distribution). Although there are many pores, they are isolated without connectivity, leading to a weak and uneven adsorption potential field (García-Pérez et al., 2007). Temperature increase generally inhibits adsorption, but deformation coupling shows gradient differences. Sample ML has the weakest temperature impact via “adsorption potential synergy” of multi-scale pores since micropores offset disturbances and mesopores dilute sensitivity (Figure 9b). Sample TL has poor stability due to the single adsorption potential of large pores and simple structure, making desorption easy at elevated temperatures (Figure 9a). Sample JN has weak adsorption potential in isolated pores, so molecules easily escape at high temperatures, amplifying sensitivity (Figure 9c). Moderately deformed sample ML has the highest adsorption capacity due to multi-scale pore synergy, enabling efficient capture across the entire pressure range (Figure 9d). Weakly deformed sample TL relies on large pores; when pressure >6MPa, the growth rate slows down due to saturation of large pores and insufficient new sites. Strongly deformed sample JN has isolated pores that saturate easily; adsorption plateaus at low pressure, with the lowest capacity, as excessive fragmentation disrupts adsorption continuity.

Figure 8

Figure 8. Distribution characteristics of CH₄ adsorption sites in molecular models of (a) TL, (b) ML, and (c) JN samples (Note: The ball-and-stick structures in the figure represent the molecular skeletons of the samples, and the blue regions illustrate the spatial distribution of methane adsorption sites).

Figure 9

Figure 9. Methane adsorption isotherms of (a) TL, (b) ML, and (c) JN samples under different temperature conditions. (d) Comparison of adsorption capacities among three different samples.

3.4 Multi-scale analysis of the coupling mechanism between fissure width, deformation and adsorption

The three typical adsorption behaviors (isolated adsorption, synergistic adsorption, trap adsorption) observed in TDC samples with different deformation degrees are essentially the macroscopic manifestations of a unified “multi-scale pore-fracture synergy adsorption mechanism” under varying pore structure connectivity and spatial distribution patterns. The core logic of this unified mechanism is: Tectonic deformation degree regulates the multi-scale pore-fracture connectivity (micropores-mesopores-macropores-fractures) and spatial distribution characteristics of TDC, thereby controlling methane adsorption behavior through the synergistic effect between adsorption potential (dominated by micropores) and diffusion capacity (dominated by mesopores/macropores and fractures). The specific manifestations under different deformation degrees are as follows.

3.4.1 Isolated adsorption in large pores and wide fissures

Under weak deformation conditions, the molecular framework of coal (e.g., TL sample) mainly undergoes local rupture, forming wide fissures and large pores but failing to establish effective connectivity between them. This leads to the failure of synergy between adsorption potential (provided by large pores) and diffusion capacity (provided by wide fissures). From the perspective of molecular skeletons, the molecular framework of TL is mainly characterized by original local rupture. Although such local rupture generates wide fissures, it fails to effectively reconstruct the overall connectivity of the skeleton. The formation of wide fissures is more like a passive response of the molecular skeleton to weak external forces rather than an active synergy, resulting in physical blocking in the connection area between wide fissures and large pores. Through microscopic structural analysis of the fissure-pore junction, it is found that over 60% of the junction areas contain incompletely broken molecular segments (Jia et al., 2023). These segments, like gates, significantly restrict the free diffusion of methane molecules between fissures and pores, creating substantial diffusion resistance. In the adsorption kinetics process, large pores, relying on their large specific surface area and relatively concentrated adsorption sites, exhibit strong adsorption potential (local red dense areas, Figure 7). They can quickly capture methane molecules under low-pressure conditions, showing a fast adsorption rate. However, as pressure increases, the adsorption sites inside large pores gradually become saturated. Meanwhile, wide fissures cannot timely supplement methane molecules to large pores due to diffusion resistance, leading to a “local saturation bottleneck” in the adsorption process (Wang M. C. et al., 2023). This bottleneck effect causes the adsorption capacity growth rate of the TL sample to stagnate significantly in the high-pressure segment, and the adsorption isotherm shows an obvious “platforming” feature (Figure 9). This observation is consistent with the findings of Wang et al. (2023), who reported that isolated large pores in weakly deformed coal lead to limited high-pressure adsorption growth due to diffusion barriers (Wang H. et al., 2023). From an energy perspective, the adsorption of methane molecules in large pores is mainly dominated by van der Waals forces and pore wall surface energy, while in wide fissures, they also need to overcome the “blocking energy barrier” of molecular segments. This further exacerbates the discontinuity of the adsorption process under high pressure, profoundly reflecting the synergistic failure of the wide fissures large pore “isolated adsorption” mode at multiple scales.

3.4.2 Synergistic adsorption in multi-scale fissures and pores

Moderate deformation induces ordered cleavage and reconstruction of the coal molecular framework (e.g., ML sample), constructing a well-connected multi-scale pore-fracture network (micropores-narrow fissures-mesopores-mesofissures). This network realizes the optimal synergy between adsorption potential and diffusion capacity. The moderately deformed sample ML endows it with unique multi-scale fissure-pore synergistic advantages, which extend from the microscopic pore structure to macroscopic adsorption performance. At the microstructural level, the multi-stage cleavage process induced by moderate deformation precisely regulates the development of multi-scale fracture widths and pores. The formation of narrow fissures is highly synchronized with the development of micropores. In the crack tip region of narrow fissures, due to the deep cleavage of the molecular skeleton, a large number of functional groups with strong adsorption activity (such as unsaturated carbon bonds and hydroxyl groups) are exposed (Morgan and Mercedes, 2020). These functional groups form synergistic adsorption units with the adsorption sites on the micropore surface, significantly enhancing the adsorption potential under low-pressure conditions and enabling rapid and stable capture of methane molecules (dense red sites, Figure 7). Mesofissures (5–10 nm), as the macroscopic extension of mesopores (2–5 nm), achieve their connectivity through the ordered reconstruction of the molecular skeleton under moderate deformation (Pan et al., 2015). Characterization of the pore structure in the mesofissure and mesopore connection region reveals a connectivity rate exceeding 90% (Wang et al., 2021). This high connectivity accelerates the diffusion of methane molecules under high-pressure conditions. The presence of mesofissures effectively alleviates the adsorption saturation pressure of mesopores under high pressure, allowing mesopores to continuously receive methane molecules transported from mesofissures and achieving a dynamic balance between adsorption and diffusion. Similar results were reported by Li et al. (2022), who confirmed that multi-scale pore connectivity in moderately deformed coal maximizes adsorption-diffusion synergy, leading to the highest adsorption capacity (Li F. L. et al., 2022). From the perspective of multi-scale energy transfer, there exists an energy coupling effect between the micropore-narrow fracture adsorption system and the mesopore-mesofracture diffusion system in sample ML. The energy released by micropore adsorption can partially drive the diffusion of methane molecules in mesofractures and mesopores; conversely, the diffusion in mesofractures and mesopores can supplement methane molecules for micropore adsorption. This synergistic transfer of energy and substances ensures that sample ML maintains a high growth rate of adsorption capacity across the entire pressure range (0–10 MPa), and the adsorption isotherm shows an ideal continuous rising characteristic (Figure 9), perfectly demonstrating the efficiency and stability of the multi-scale fissure-pore synergistic adsorption mode.

3.4.3 Trap adsorption in fragmented narrow fissures and isolated pores

Strong deformation causes severe fragmentation and disordered accumulation of the coal molecular framework (e.g., JN sample), forming fragmented narrow fissures and isolated tiny pores. This completely destroys the synergy between adsorption potential and diffusion capacity, resulting in ineffective adsorption. The fragmented narrow fissures and isolated pores formed in the strongly deformed sample JN constitute a distinctive trap adsorption mode, whose essence lies in the complete loss of synergy caused by excessive fragmentation of the microstructure. The process of fragmentation-reconstruction and disordered accumulation of the molecular skeleton induced by strong deformation makes the formation of narrow fissures completely deviate from the ordered pore development law, resulting in narrow fractures with fragmented and non-directional distribution characteristics (Zhang et al., 2020). In the connection regions between these fragmented narrow fissures and isolated pores, a large number of dead spaces (such as closed microcavities and gaps between broken molecular segments) are formed due to the disordered accumulation of the molecular skeleton (Wang et al., 2020). These dead spaces greatly restrict the effective diffusion paths of methane molecules, leading to over 80% of the fracture-pore connection regions losing their adsorption and diffusion functions (fissure-pore blocking rate >80%) (Li et al., 2019). This is consistent with the research of Jia et al. (2023), who found that excessive deformation-induced pore fragmentation creates diffusion barriers and trap adsorption in TDC (Jia et al., 2023). During the adsorption process, the adsorption behaviors of fragmented narrow fissures and isolated pores exhibit significant asynchrony” and “inefficiency. Although isolated pores have certain adsorption sites, methane molecules can hardly enter the interior of the pores due to the blocking of fragmented narrow fractures, and only form scattered adsorption on the pore surfaces (scattered red sites, Figure 7), resulting in extremely low adsorption capacity under low-pressure conditions. As the pressure increases, the adsorption sites inside the isolated pores are rapidly saturated, while fragmented narrow fissures cannot provide effective supplementation of methane molecules to the pores, causing the entire adsorption system to fall into a dilemma of early saturation and difficult improvement. The adsorption isotherm shows an obvious platforming feature even in the low-pressure segment (Figure 9). From the perspective of molecular dynamics, the movement of methane molecules in fragmented narrow fissures and isolated pores requires frequent traversal of an energy barrier maze composed of disordered molecular segments. This not only increases the energy consumption of molecular movement but also causes a large number of methane molecules to be trapped in dead spaces due to their inability to overcome the energy barriers, forming trap molecules that cannot actually participate in effective adsorption. This profoundly reveals the nature of synergistic failure in the trap adsorption mode of fragmented narrow fractures-isolated pores at multiple scales.

4 Conclusion

1. Fissure width and pressure synergistically regulate methane adsorption energy distribution in TDC. Narrow fissures (2 nm) exhibit multi-peak energy distribution due to molecular crowding, while wide fissures (10 nm) show single stable peaks; increasing pressure reduces energy dispersion (44% reduction in half-peak width for 5 nm pores at 20 MPa) and enhances adsorption stability by promoting molecular close packing. This finding clarifies the quantitative coupling relationship between pore geometry and pressure in controlling adsorption energy states.

2. Deformation degree controls methane adsorption capacity through pore structure evolution. Moderately deformed coal (ML) has the highest adsorption capacity due to a well-connected multi-scale pore network. Micropores provide strong adsorption potential under low pressure, while mesopores and mesofissures facilitate methane diffusion under high pressure, achieving synergistic adsorption. Weakly deformed coal (TL) relies on large isolated pores, leading to early saturation under high pressure and a slow growth rate of adsorption capacity. Strongly deformed coal (JN) forms fragmented narrow fissures and isolated tiny pores, resulting in severe diffusion barriers and “trap adsorption,” with the lowest adsorption capacity and early saturation even under low pressure.

3. A unified “multi-scale pore-fracture synergy adsorption mechanism” is proposed to clarify the core control law of methane adsorption in TDC: Tectonic deformation regulates the connectivity and spatial distribution of multi-scale pores (micropores - mesopores - macropores) and fissures, and the synergy between adsorption potential (dominated by micropores) and diffusion capacity (dominated by mesopores/macropores and fissures) determines the final adsorption behavior. Weak deformation leads to poor pore-fracture connectivity, resulting in isolated adsorption with local saturation bottlenecks; moderate deformation constructs an optimally connected multi-scale pore-fracture network, realizing synergistic adsorption with high efficiency across the entire pressure range; strong deformation causes excessive pore fragmentation and disordered distribution, leading to trap adsorption with severe diffusion barriers. This unified mechanism integrates the different adsorption manifestations under varying deformation degrees, providing a systematic theoretical framework for understanding methane adsorption in TDC.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

LW: Writing – original draft, Writing – review and editing. JL: Conceptualization, Writing – review and editing. GL: Software, Writing – original draft, Writing – review and editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the National Natural Science Foundation of China (No. 42402181) and the Fundamental Research Program of Shanxi Province (No. 202203021221230, 202203021212475), Key Research and Development Program Project of Shanxi Province, Grant No: 202502080302019.

Acknowledgements

The authors acknowledge the financial support from the National Natural Science Foundation of China and Fundamental Research Program of Shanxi Province.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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