Experimental investigation and ReaxFF simulation on pore structure evolution mechanism during coalification of coal macromolecules in different ranks

Abstract

This analysis revealed the alterations in the pore structure of large organic molecules in coal during the process of coal pyrolysis. Nine models of macromolecular structures in coals, representing distinct coal ranks, have been built. The research results show that along with the increasing coal rank, the average microporous volume of medium rank coal is 0.0287 cm³/g. The average microporous volume of high-grade coal is 0.0662 cm³/g. The micropore volume and specific surface area of coal samples decrease in the order of high rank, low rank, and middle coal. The experimental measurements align with the ReaxFF pyrolysis simulation calculations, indicating a decrease in the hydrogen to carbon ratio and oxygen to carbon ratio of all coal molecules. Additionally, the pore volume and specific surface area exhibit a pattern of initially decreasing and then increasing. The simulation results of gas probes indicate that a majority of the pores with a diameter larger than that of CH₄ molecules are found in the macromolecular structure models of low rank coal and medium to high rank coal. The conclusions are useful for us to understand the formation and development process of pores in coal reservoir. A two-dimensional representation of coal’s macromolecular structure was constructed using ChemDraw software. The Forcite module in Materials Studio software was used to perform geometric optimization and annealing kinetics simulation of a two-dimensional macromolecular structure model. The ReaxFF-MD module in Amsterdam Modeling Suite (AMS) 2020 software to model the pyrolysis of XJ coal macromolecules.

Introduction

Coal is a complex substance composed of both organic materials and inorganic minerals, with a significant portion derived from biological matter. The molecular structure of coal, much like living matter, is intricate and multifaceted, consisting of various macromolecular components^1,2. Over the years, scholars have developed several classic macromolecular structural models to explain coal’s organic composition across different geological times and regions^3–5. For example, the molecular model of low-rank coal focuses primarily on its pore structure, chemical composition, and interaction with water, particularly for lignite^6–11. Similarly, molecular models of high-rank coal have been used to simulate gas adsorption and chemical behavior under various conditions^12–15. Other models consider the presence of heteroatoms, interactions between organic matter and clay minerals, and the inclusion of elements such as sulfur (S), phosphorus (P), and germanium (Ge)^16,17. These models are foundational in evaluating elemental composition, density, and chemical structure, forming the basis for studying coalification processes, coalbed methane adsorption–desorption, coal pyrolysis, and coal classification and utilization.

Researchers have also leveraged macromolecular models to validate theoretical predictions and simulate chemical reactions. For instance, Zhou et al. and other researchers employed the macromolecular structural model to analyze chemical spectra, confirming the accuracy of the molecular configurations^18–21. Zhao et al. focused on gas compositions under varying pressure and coal composition ratios through simulations^22–24. Scholars explored the chemical reaction pathways of coal macromolecular structures, emphasizing the growing use of ReaxFF molecular dynamics simulations in understanding pyrolysis in coal engineering^25–41.

However, variations in coal’s thermal maturity and material origins across different coal-producing regions lead to considerable differences in macromolecular structures. These structural variations directly influence coal’s pore characteristics, including porosity, pore size distribution, and pore connectivity. Previous studies have demonstrated that coal is a porous medium, containing a vast network of pores and fractures^42–47. The characterization of these pores—such as size, type, permeability, and wettability—has been widely studied^9,48–53. Furthermore, research has extended to understanding the fluid dynamics within these pores, particularly how gases and liquids behave in coal reservoirs^54,55.

The pore structure in coal exhibits substantial variability depending on the geological conditions of the coal reservoirs. Techniques for analyzing micro and nano pores, including low-temperature nitrogen adsorption and low-field nuclear magnetic resonance (NMR), have been extensively used to study pore characteristics^56–61. These advancements in technology have improved the accuracy and depth of pore analysis, contributing to a better understanding of pore formation, evolution, and classification.

Despite extensive research on coal pores, relatively little work has been conducted on the internal cavities of organic macromolecules in coal. The specific range of intermolecular pores within coal macromolecules, particularly micropores (< 2 nm) and ultramicropores (< 0.7 nm), remains underexplored. This gap in the literature presents an opportunity for further research into the relationship between molecular structures and pore formation, particularly through molecular simulations^62,63.

The pyrolysis of organic matter to generate hydrocarbons can result in the formation of pores. The alterations in these pores also serve as evidence for the occurrence of intermolecular pores. These pores are believed to result from imperfections in the molecular system’s internal structure. The size of these imperfections gradually expands, leading to the formation of ever larger pores. This process occurs in a certain sequence, starting with ultra micropores, followed by micropores, mesopores, and finally macropores. The macromolecular structure model system contains numerous theoretical pores that can be produced via MD molecular simulation. What is the relationship between these pores and real pores, and how can energy analysis be used to identify the potential locations of molecules and the limitations imposed by the surrounding pores? These intriguing matters require additional attention. Furthermore, prior scholars have extensively investigated the material composition, physical characteristics, and macromolecular structure system of coal, yielding numerous significant findings. However, additional investigation is required to study the specific attributes, origin, and development of the pore structure in coal at a molecular level, using both experimental and numerical simulations^64–68.

The aim of this study is to address existing knowledge gaps by developing macromolecular models for coal of different ranks and analyzing the pore structures of individual microscopic components. Specifically, the research focuses on simulating the formation of intermolecular pores within coal’s macromolecular system using molecular dynamics (MD) simulations, examining changes in micropores and nanopores during hydrocarbon generation and coal pyrolysis, and analyzing the evolution of adsorption pores and basic unit pores throughout the coal’s thermal evolution process. Additionally, the study investigates the relationship between macromolecular structural changes and pore distribution across different coal ranks, with particular emphasis on the transition from micropores to mesopores and macropores. By combining experimental data with quantum chemical simulations, the study provides new insights into the dynamic changes in coal’s pore structure during thermal evolution and pyrolysis.

Samples and experiments

Sample information

Sample source

This study examined specific coal seams from various mining areas across different provinces in China. The coal seams selected were the middle coal seam of Dalianhe Formation in Yilan Open pit Mine in Heilongjiang Province, No.2 coal seam in Sera Mine Field in Inner Mongolia, No.8 coal seam of Linnancang Mine in Kailuan Mining Area in Hebei Province, No.6 coal seam of Qinan Mine in Huaibei Mining Area in Anhui Province, No.4 coal sea of Shitai Mine in Huaibei Mining Area in Anhui Province, No.7 coal seam of Fangezhuang Mine in Kailuan Mining Area in Hebei Province, No.8 coal seam of Lujiatuo Mine in Kailuan Mining Area in Hebei Province, No.1 coal seam of Xiandewang Mine in Hebei Province, and No.3 coal seam of Xinjing Mine in Yangquan Mining Area in Shanxi Province. We collected one coal sample from each coal mine. These samples have been named as YL, SL, LNC, QN, ST, FGZ, LJT, XDW, and XJ. Table 1 displays the fundamental details of the samples. Nine coal samples display distribution characteristics corresponding to low, middle, and high rank, with their maturity progressively escalating. In order to guarantee the precision of the experiment, samples for NMR, low-temperature liquid nitrogen, and CO₂ adsorption tests were obtained from the identical coal block for each rank.

Table 1.

Sample details.

Samples	Formation	Coal seam number	Coal rank	Mad (%)	Ad (%)	Vdaf (%)
YL	Dalianhe formation	Middle coal seam	Low rank coal	5.71	1.19	47.60
SL	Shanxi formation	No.2	Low rank coal	9.66	12.73	35.76
LNC	Damiaozhuang formation	No.8	Medium rank coal	4.80	43.00	41.43
QN	Shanxi formation	No.6	Medium rank coal	1.15	17.75	34.70
ST	Shanxi formation	No.4	Medium rank coal	0.92	12.17	26.55
FGZ	Damiaozhuang formation	No.7	Medium rank coal	2.34	31.09	29.86
LJT	Damiaozhuang formation	No.8	Medium rank coal	1.22	24.91	20.86
XDW	Shanxi formation	No.1	High rank coal	1.33	20.70	10.74
XJ	Shanxi formation	No.3	High rank coal	1.16	9.50	10.06

M_ad, moisture, air-drying basis; A_ad, ash yield, air-drying basis; V_daf, volatile, dry ash-free.

Experimental methods

Porosity testing experiment

The formation and distribution of nano and micro pores in coal samples are intricate. There are several techniques available to accurately measure and describe the pore size distribution of coal. However, each method offers distinct advantages in different ranges of pore sizes. Hence, precisely characterizing the complete pore size structure of coal using a single approach is challenging due to inherent restrictions. This study thoroughly examined the nano and micro pores of various coal ranks using three testing techniques: low-temperature liquid nitrogen adsorption experiment, CO₂ adsorption experiment, and low field nuclear magnetic resonance experiment.

Low field nuclear magnetic resonance

The MesoMR12-070 H is a medium-sized nuclear magnetic resonance imaging analyzer manufactured by Newman. The testing approach involves utilizing the disparity in fluid relaxation time (T) across various apertures to determine the fluid distribution in each aperture based on the decay time of the transverse magnetization vector of hydrogen nuclei. All samples underwent dry sample testing in this investigation. Following the completion of the initial testing, a subsequent round of saturated water testing was carried out after a period of 48 h of saturation. Finally, the process of centrifugation dehydration was undertaken. Three tests were conducted in all.

Low temperature liquid nitrogen adsorption

The pore structure of coal samples was analyzed using the JW-BK100C single station specific surface area and mesoporous pore size analyzer. The analyzer has a theoretical testing pore size range of 0.35–500 nm. Prior to conducting the test, pulverize and crush the coal sample, then sift it through a 50–60 mesh sieve. Proceed by weighing approximately 10 g of the dried coal sample and placing it into a sample tube. Subject the coal sample to vacuum degassing in a drying oven set at 150 °C for a duration of 6 h, then allow the sample to cool. During the test, the coal sample was introduced into a chamber where nitrogen adsorption takes place. The sample is then heated to a temperature of 85 °C and subjected to vacuum degassing for a duration of 4 h. Afterward, it is cooled to room temperature before being further chilled to a low temperature of 77 K. The temperature is consistently kept at 77 K, while nitrogen is introduced at high pressure during the experiment to measure different pore properties of the coal sample.

Carbon dioxide adsorption

In this experiment, the Autosorb iQ CO₂ apparatus from Conta Instruments was used to measure CO₂ adsorption in different rank samples. The samples were pre-treated by drying to remove moisture and volatile components before being placed in the adsorption chamber. High-purity CO₂ gas was introduced under controlled temperature conditions, typically at room temperature or slightly elevated, to simulate coal seam conditions. The higher saturation vapor pressure and faster diffusion rate of CO₂, compared to liquid nitrogen, allowed it to efficiently occupy micropores and ultramicropores smaller than 1.0 nm in the carbonaceous material. As CO₂ gas was introduced, the adsorption quantity at varying pressures was recorded to generate adsorpti on isotherms. These isotherms were used to calculate the micropore volume and specific surface area of the samples. The higher sensitivity of CO₂ adsorption, due to its faster diffusion rate, enabled precise quantification of pore structures, especially in the smaller pores. This method provided a detailed and accurate analysis of the pore characteristics in the coal samples.

MS simulation

The organic geochemical data acquired from elemental analysis, solid-state nuclear magnetic resonance spectroscopy analysis, and Fourier transform infrared spectroscopy analysis studies were utilized to construct a two-dimensional representation of coal’s macromolecular structure using ChemDraw software. The Forcite module in Materials Studio software was used to perform geometric optimization and annealing kinetics simulation of a two-dimensional macromolecular structure model. The objective was to determine the three-dimensional configuration with the lowest energy for coal macromolecular structures of varying coal ranks. Describe the pertinent physical components of the assembled aggregate state structure.

ReaxFF-MD pyrolysis simulation

Investigate the interaction between the pore structure and macromolecular structure of coal, and employ the ReaxFF-MD module in AMS 2020 software to model the pyrolysis of XJ coal macromolecules. The ReaxFF-MD molecular dynamics simulation allows for the observation of the dynamic response of physical and chemical parameters as the structure of coal macromolecules undergoes changes. Additionally, it can model the pyrolysis of XJ macromolecules with a heating rate of 2 K/ps.

Results

The macromolecular structure of coal in different ranks

This study performed organic chemical analysis on the vitrinite microscopic components of the coal samples under investigation. Table 2 displays the vitrinite reflectance, H/C ratio, O/C ratio, O/N ratio, H/O ratio, and unit molecular formula of 9 coal samples. Through the implementation of elemental analysis, solid-state nuclear magnetic resonance spectroscopy analysis, and Fourier transform infrared spectroscopy analysis studies on 9 coal samples, 9 distinct macromolecular structure units across various coal ranks were successfully identified and established. The Material Studio software was utilized to display and rotate the two primary molecule structures in a three-dimensional manner, with the objective of minimizing their energy. Figure 1 depicts the procedure of creating coal macromolecules and the 3D molecular structural unit models for 9 distinct coal ranks, with a focus on energy minimization.

Table 2.

Organic geochemical parameters of different coal ranks.

Samples	Ro, max %	H/C	O/C	O/N	H/O	Molecular formula
YL	0.53	0.10	0.28	2.58	0.37	C111H136N2O23
SL	0.58	0.075	0.192	13.72	0.39	C167H150N2O24
LNC	0.80	0.092	0.18	3.12	0.44	C228H169N3O15S
QN	0.91	0.083	0.079	6.86	1.05	C202H202N2O12
ST	1.39	0.078	0.02	1.71	0.26	C197H176N2O3S
FGZ	1.59	0.076	0.014	1.143	5.44	C192H174N2O2S
LJT	1.61	0.082	0.032	3.43	2.59	C168H166N2O6
XDW	2.46	0.041	0.014	1.44	1.94	C182H116N4O4
XJ	2.18	0.048	0.012	1.71	2.20	C182H106N2O3S

Fig. 1.

Molecular structural units of different coal ranks (a) The unit molecular structure of YL; (b) The unit molecular structure of SL; (c) The unit molecular structure of LNC; (d) The unit molecular structure of QN; (e) The unit molecular structure of ST; (f) The unit molecular structure of FGZ; (g) The unit molecular structure of LJT; (h) The unit molecular structure of XDW; (i) The unit molecular structure of XJ)

The data in Table 2 demonstrates that as the vitrinite reflectance of coal samples increases, the thermal maturity of the coal also increases. Additionally, the H/C and O/C atomic ratios of the coal samples exhibit a declining pattern, indicating a comprehensive transformation of the coal elements involving dehydrogenation, deoxidation, and carbon fixation during the coalification process.

Figure 1 illustrates that the macromolecular structures of various coal ranks predominantly consist of aromatic core structures, accompanied by alkyl side chains and functional groups containing oxygen, nitrogen, and sulfur. During coalification, the macromolecular structure of coal undergoes continuous changes. More precisely, the aromatic core of the fundamental building blocks of coal macromolecules undergoes a gradual expansion, resulting in a progressive increase in the number of condensed rings within the core. Simultaneously, the length and quantity of alkyl side chains decrease rapidly as the coal degree rises, while the presence of oxygen-containing functional groups diminishes significantly. With the steady increase in carbon content, the number of aromatic rings in the fundamental structural units of coal macromolecules experiences a fast rise, eventually transitioning into a graphite structure.

This study conducted a statistical analysis on the quantity and categories of aromatic structural components in 9 macromolecular structural units with varying levels of coalification, as presented in Tables 3 and 4. It is evident that as coalification intensifies, the concentration of aromatic carbon in the coal’s macromolecular structure grows dramatically, along with a progressive rise in the quantity of aromatic sheet-like structures containing multiple benzene rings, such as thiophene and pyridine.

Table 3.

Assuming the types and amounts of aromatic structural units.

Structure	Name	Number	Structure	Name	Number
	Benzene	a		Pyridine	e
	Napthracene	b		Pyrrole	f
	Anthracene	c		Thiophene	g
	Pyrene	d

Table 4.

The types and amounts of aromatic structural units.

Samples	a	b	c	d	e	f	g
YL	1	2	3	0	0	0	0
SL	1	2	3	0	6	0	0
LNC	7	0	3	2	4	1	2
QN	12	0	3	1	2	0	2
ST	9	0	3	2	2	0	3
FGZ	6	0	5	2	3	1	4
LJT	3	1	11	1	0	0	0
XDW	2	1	2	4	7	0	7
XJ	2	0	4	2	8	1	7

Characteristics of coal pore development

NMR experimental results

Once water permeates all the pores of the coal sample in a state of saturation, nuclear magnetic resonance testing accurately reveals the pore properties of the coal sample. The T₂ relaxation spectra of 7 coal samples, each with varying coal rankings, exhibit a pattern characterized by two to three distinct peaks. This pattern indicates a wide variety of pore size distribution within the coal samples. The coal samples can be classified into two categories based on the spatial arrangement of the peak values observed in the nuclear magnetic resonance spectra depicted in the figure. One category of coal sample has strong coherence among various peaks (QN, FGZ, LJT, XDW), suggesting excellent pore connection inside the coal samples. Conversely, there are noticeable discontinuities between the peaks of another category of coal sample (YL, ST, XJ), showing inadequate internal pore connectivity.

The relaxation time spectrum provides a realistic representation of the sample’s pore size distribution features, with longer relaxation times correlating to bigger pore sizes. The distribution characteristics of nuclear magnetic resonance T₂ spectra vary among coal samples of different coal grades. According to the nuclear magnetic resonance test results (Fig. 2), the highest proportion of adsorption pores with sizes less than 100 nm is observed in various coal ranks, reaching a maximum value of 94% (YL). The FGZ sample has a minimum fraction of adsorption pores, which amounts to 51%. Infiltration pores contribute to 2 − 24% of the sample, whereas fractures account for 3.9 − 38%. The nuclear magnetic resonance measurements of coal with varying coal ranks often reveal that the highest intensity signal is observed within the 0.01-2.5ms signal range, indicating the presence of distinct pore structures. With increasing coalification, the secondary peak signal gradually diminishes compared to the main peak signal, and the connectivity between different peaks deteriorates. Additionally, the degree of micropore and transitional pore development increases, while the development of mesopores decreases. The formation of macropores and microcracks exhibits a pattern of initial growth followed by subsequent decline.

Fig. 2.

NMR T₂ spectrum and aperture distribution.

The effective porosity, residual porosity, and total porosity of the sample were determined using the nuclear magnetic T₂ curve, as depicted in Fig. 3. The measured total porosity in the nuclear magnetic resonance experiment was approximately 8% for YL, whereas the remaining samples exhibited porosity levels below 6%. The porosity of QN, FGZ, and LJT was uniformly 2%. As coal rank increases, porosity experiences a rapid initial drop, followed by intermittent fluctuations in medium coal rank, and then resumes increasing in XDW and XJ which are in high coal rank. The analysis of pore size distribution in various coal ranks reveals the presence of a significant quantity of micro and nano pores in low coal ranks, which also function as adsorption pores. With a rise in coal rank, the size of adsorption pores gradually decreases, reaching its minimum at FGZ. This suggests a decrease in the overall pore volume below 100 nm. The possible explanation is that the presence of regular molecular side chains results in a reduction of pore size, thereby causing a decrease in the number of pores within the molecule.

Fig. 3.

Coal sample porosity in different states.

Low temperature liquid nitrogen experiment

The low-temperature liquid nitrogen adsorption experiment enables the measurement of pore characteristics in some micropores as well as all transition pores. The classification of pore types, namely open pores, semi-open pores, and closed pores, is determined by analyzing the degree of separation between the adsorption and desorption curves of liquid nitrogen. The adsorption desorption curves vary due to the distinct pore architectures and permeability of the coal samples, with their shape being directly influenced by the size and quantity of pores present. Figure 4 reveals that the hysteresis loops of coal samples with varying coal rankings in this experiment exhibit relatively small sizes, suggesting limited internal connection and the existence of numerous semi-enclosed pores, such as wedge-shaped or narrow slit-shaped pores. This phenomenon also accounts for the significant presence of micropores detected following nuclear magnetic resonance centrifugation.

Fig. 4.

Nitrogen adsorption process curve.

Based on the results of the low-temperature liquid nitrogen adsorption experiment (Figs. 5 and 6), it is evident that the specific pore volume change follows a similar pattern throughout various coal ranks. Once the pore size drops below 10 nm, the specific pore volume distribution in coal samples of varying coal rankings exhibits a consistent shift after reaching its highest point at 3–5 nm. Once the pore size exceeds 10 nm, there is a consistent increase in the specific pore volume as the pore size increases. The majority of pore diameters in different samples are smaller than 200 nm, with a comparatively high number of pores ranging from 0.363 nm to 10 nm. With the exception of QN samples, which make up approximately 15% of the total, all other samples exceed 20%. In order for nitrogen molecules to be adsorbed, the pore size distribution in all nitrogen adsorption tests must exceed 0.364 nm, which is the diameter of nitrogen molecules. Previous molecular simulations revealed that the molecular diameters of N₂ and CO₂ were 0.364 nm and 0.33 nm, respectively. This study conducted a statistical analysis of the majority of pores that are larger than methane molecules (0.38 nm). The findings revealed that pores ranging from 0.33 to 0.38 nm or 0.364–0.38 nm still constituted a specific proportion. Particularly within the range of 0.33 to 0.38 nm, the percentage surpasses 20%, reaching a maximum of 40%.

Fig. 5.

Pore diameter distribution curves of different coal grades.

Fig. 6.

Distribution of pore size of different coal grades.

Generally, when the coal rank rises, there is a noticeable decline in the pore volume of each individual microscale pore. The decrease in micropores and macropores is more significant when compared to transition pores. Medium and high rank coal have a lower abundance of macropores in comparison to low rank coal, but have a more pronounced development of micropores and transition pores. Table 5 indicates that the pore volume of low rank coal exhibits a pattern of initially decreasing and then increasing as the rank of the coal increases. In contrast, the average pore size remains relatively stable, with high rank coal generally having smaller average pore sizes compared to low rank and medium rank coal. The pore volume determined using low-temperature liquid nitrogen measurement exhibits a consistent pattern of low rank coal having a lower volume than medium rank coal, which in turn has a lower volume than high rank coal. Coal reservoirs have a greater development of ultra micropores (< 2 nm) as the degree of coalification increases. Given the constraints of low-temperature liquid nitrogen adsorption testing techniques, it is unfeasible to precisely assess the pore volume for pores smaller than 2 nm. This highlights the difficulties of relying solely on this testing method to define the pore structural attributes of reservoirs.

Table 5.

Specific pore volume of coal samples from different ranks.

Sample	LT-N2GA
	Pore volume /(cm3 g-1)	BET/(m2 g-1)	Average pore diameter /nm	Hysteresis loop type
YL	0.004	1.049	14.067	H3
QN	0.006	1.498	16.322	H3
ST	0.005	1.317	14.112	H3
FGZ	0.002	0.396	16.84	H3
LJT	0.002	0.442	15.516	H3
XDW	0.001	0.345	15.554	H3
XJ	0.004	1.332	12.215	H3

CO₂ adsorption experiment

The adsorption of CO₂ can be used to determine the microporous structural characteristics, namely the pore diameters ranging from 0.3 to 2.0 nm. The pore size distribution of various coal ranks exhibits a notable degree of similarity, as depicted in Fig. 7. When the size of the pores is smaller than 0.7, both the volume and surface area of the pores exhibit a multimodal pattern, occupying nearly all of the measured pore volume and specific surface area within the given range of pore sizes. When the pore size exceeds 0.7 nm, the variations in pore volume and specific surface area are negligible. Moreover, as the pore size grows, the pore volume experiences a gradual increase while the specific surface area undergoes a gradual decline.

Fig. 7.

Pore diameter distribution curves of different coal grades.

Table 6 presents the experimental results of CO₂ adsorption, showcasing the microporous volume and specific surface area of coal samples across different ranks. For low-rank coal, the microporous volume ranges from 0.0508 to 0.0624 cm³/g, with an average value of 0.0611 cm³/g, and the specific surface area varies between 159.64 and 217.27 m²/g, averaging 188.45 m²/g. Medium-rank coal exhibits a lower microporous volume, ranging from 0.0233 to 0.0314 cm³/g, with an average value of 0.0287 cm³/g, and a specific surface area between 70.91 and 112.72 m²/g, averaging 86.03 m²/g. In contrast, high-rank coal shows a microporous volume between 0.0648 and 0.0677 cm³/g, with an average of 0.0662 cm³/g, and a specific surface area ranging from 208.53 to 213.72 m²/g, with an average of 211.13 m²/g.

Table 6.

Experimental results of CO₂ adsorption.

Sample	Ro, max%	V3/ (cm3/g)	S3/ (m2/g)
YL	0.53	0.0508	159.64
SL	0.58	0.0624	217.27
LNC	0.80	0.0233	72.2
QN	0.91	0.0277	85.1
ST	1.39	0.0362	112.72
FGZ	1.59	0.0314	89.2
LJT	1.61	0.0253	70.91
XDW	2.46	0.0648	208.53
XJ	2.18	0.0677	213.72

The data indicate a general trend where high-rank coal has the highest microporous volume and specific surface area, followed by low-rank coal, with medium-rank coal having the lowest values. This trend reflects the structural changes in coal during the coalification process. As the rank increases from low to medium, the macromolecular structure becomes less stable, leading to the conversion of some micropores into mesopores and transition pores, which reduces the number of micropores (Fig. 8). However, as the rank progresses from medium to high, the arrangement and flexibility of aromatic layers improve, contributing to the formation of more compact micropores and a subsequent increase in microporous volume and specific surface area.

Fig. 8.

Map of specific surface area and volume distribution of different coal grades.

MS simulation experiment

We employed Materials Studio 7.0 software to create and refine three-dimensional molecular structure systems of various coal ranks. We chose aggregated coal macromolecular structure models for CO₂ and N₂ electron probe simulation studies from a pool of nine optimized macromolecular structure models of coal. Figure 9 displays the simulated structures.

Fig. 9.

CO₂ probe adsorption diagram of coal macromolecular model.

The molecular skeleton and types of functional groups primarily govern the pore structure of molecular systems. The arrangement of pores is regulated by the gaps between the skeletal structure and the micropores created by amorphous carbon. The molecule’s chaotic arrangement of atoms results in distinct variations in the active groups, which in turn causes a heightened level of randomization in the development of pores. The progression of coal from low to medium to high rank is characterized by a reduction in pore disorder. Figure 9 demonstrates that when the vitrinite composition matures, the formation of pores in the coal macromolecular structure model initially increases and subsequently declines. The high-order coal molecular structure model exhibits a uniform arrangement of pore structures in clusters. Throughout the process of transitioning from low coal rank to high coal rank, there is a constant detachment of functional groups, fat side chains, and other heteroatoms. This leads to a gradual increase in aromaticity and a gradual decrease in the presence of pores composed of fat side chains. The pores exhibit an initial decline, while the coalification process intensifies, leading to an increase in the aromaticity of coal macromolecules and the size of the aromatic nucleus. Consequently, the quantity of pores consisting of organized aromatic structures rises (Fig. 9a, e and i). The change trend of specific surface area and volume of coal macromolecules is similar, as depicted in Fig. 10. As coal matures, the specific surface area and volume of coal molecules in the low coal rank stage see a rapid increase. During the intermediate stage of coal maturation, the surface area and volume of pore space in the coal macromolecule model exhibit a fluctuating pattern resembling a zigzag as maturity increases. During the transition from medium coal rank to high coal rank, there is a progressive increase in both the specific surface area and the volume of pore space, which eventually reaches a stable state. Overall, during the development of the coal macromolecule structure model, there is an initial decrease followed by an increase in the pore volume, surface area, and volume of the coal macromolecule.

Fig. 10.

Adsorption structure distribution of CO₂ and N₂ probe (a) Specific surface area of coal pores; (b) Specific pore volume of coal)

Table 7 reveals that the molecular diameter of CO₂ is smaller than that of N₂ molecules, resulting in a higher volume porosity for CO₂ probes compared to N₂ probes. Furthermore, as the vitrinite composition matures, there is an observed pattern where the volume porosity and specific surface area initially increase, then decrease, and then increase again. This pattern aligns with the findings from porosity studies and molecular structure model simulation testing. This work examined the ratio of internal pores in several coal rank macromolecular structure models, using CH₄ as the boundary (Fig. 11). As coal matures, it undergoes a progressive transformation from low rank coal to medium rank coal and eventually to high rank coal. This transformation is accompanied by the development of many adsorption pores. The presence of adsorption pores in high rank coal is the main reason for its much better methane adsorption capability compared to low rank coal. The figure displays the analysis findings of the pore ratio for various coal ranks obtained by the utilization of CO₂ gas probes and N₂ gas probes in MS software. Figure 11 reveals that the macromolecular structure models of low rank coal and medium to high rank coal contain a significant number of pores larger than the diameter of CH₄ molecules, comprising more than half of the total. Moreover, high rank coal exhibits a higher proportion of pores capable of adsorbing CH₄ molecules compared to medium to low rank coal.

Table 7.

Gas adsorption simulation data sheet.

Sample	CO2 specific area (Å2)	CO2 volume porosity (Å3)	< CH4 pore ratio	> CH4 pore ratio	N2 specific area (Å2)	N2 volume porosity (Å3)	< CH4 pore ratio	> CH4 pore ratio
YL	1144.64	665.95	0.461	0.539	746.37	433.64	0.172	0.828
SL	2887.32	1667.12	0.467	0.533	2629.26	1091.64	0.176	0.824
LNC	7521.43	6999.53	0.194	0.806	6479.42	6031.15	0.065	0.935
QN	4317.07	3436.83	0.258	0.742	3465.59	2792.71	0.087	0.913
ST	3059.63	2127.14	0.467	0.533	2629.26	1091.64	0.185	0.815
FGZ	4655.52	3572.35	0.267	0.733	3777.36	2905.14	0.099	0.901
LJT	2270.24	1514.71	0.353	0.647	1701.76	1128.41	0.132	0.868
XDW	5255.4	4671.61	0.227	0.773	4363.15	3916.93	0.078	0.922
XJ	5001.71	4837.25	0.201	0.799	5001.71	4837.25	0.099	0.901

Fig. 11.

The proportion of pores larger than CH₄ in macromolecular structure model.

ReaxFF-MD simulation

Perform pyrolysis simulation experiments using the ReaxFF module in the AMS simulation package. Upload the enhanced XJ 3D model to AMS and do pyrolysis simulation experiments under vacuum conditions. Specify the desired temperature for the heating process as 3000 K and conduct a simulation using ReaxFF-MD with a heating rate of 2 K/ps. By conducting thermal simulation studies on hydrocarbon formation, the mechanism of pore alterations throughout the evolution of coal macromolecules can be elucidated.

Product distribution

The data illustrates the alterations in the product composition of the traditional pyrolysis process of XJ anthracite’s macromolecular structure model when exposed to an ample supply of oxygen, as well as the pyrolysis process conducted without the presence of water molecules, both performed at a temperature of 1000 K.

The pyrolysis of coal is analogous to its coalification process, as both include the enrichment of carbon, reduction of hydrogen, and reduction of oxygen. Hence, the pyrolysis experiment of coal can effectively assess the progression of coal macromolecules towards higher maturity. Figure 12 demonstrates that in the presence of abundant oxygen, the macromolecular structure of coal becomes more unstable, leading to a greater likelihood of chemical bonds breaking and combining with oxygen to produce hydrocarbon gases.

Fig. 12.

Product distribution under different pyrolysis states.

Evolution trend of pyrolysis pores

Figure 13 depicts the changes in internal pore volume and surface area of the XJ coal macromolecular structure model at different pyrolysis temperatures during the pyrolysis process. As the temperature rises during the first pyrolysis process, the chemical bonds of coal macromolecules progressively break and their internal structures become more compact, leading to a reduction in overall porosity. At a temperature of 1500 K, a critical juncture arises, and the progression towards larger pores is attributed to the secondary hydrocarbon production phenomenon. The recombination of initial product hydrocarbon gases results in an augmentation of porosity. Elevated temperatures can lead to the structural breakdown of the carbon skeleton in coal coke, causing certain microporous coal coke to transform into mesoporous and macroporous pore types. This transformation results in a consistent reduction in the porosity of the coal’s macromolecular structures.

Fig. 13.

Porosity variation diagram.

Figure 14 displays the electron probe pore diagrams illustrating the macromolecular structure of XJ coal at different temperatures: 300 K, 1500 K, 2000 K, 2500 K, and 3000 K. The precise data are displayed in Table 8. During the initial phase of coal macromolecular pyrolysis, at a temperature of 300 K, the internal structure of coal is characterized by a relatively disordered arrangement and exhibits strong connectedness, resulting in the development of many pores. With an increase in pyrolysis temperature, gas products are consistently generated within the molecular structure while the pores formed between its functional groups gradually diminish. This results in a decrease in larger pores and an increase in smaller pores. The total pore volume exhibits a declining pattern.

Fig. 14.

Schematic diagram of transient electron probe at different thermal simulated temperatures (300 K: Room Temperature; 1500 K: Initial Thermal Decomposition; 2000 K: Advanced Decomposition; 2500 K: High Thermal Decomposition; 3000 K: Complete Thermal Decomposition).

Table 8.

Gas adsorption simulation data sheet.

Pyrolysis temperature (K)	300	1500	2000	2500	3000
Volume porosity (Å3)	3623.98	543.52	871.28	774.96	758.02
Specific area (Å2)	3767.53	999.80	1448.22	1252.07	1170.93

Discussion

Comparative study on pore testing of different rank coal

The pore structure of coal varies significantly with coal rank, and understanding these variations provides insights into the coalification process and its effects on porosity and permeability. Various pore testing techniques, including nuclear magnetic resonance (NMR) centrifugation, low-temperature nitrogen adsorption, and CO₂ adsorption experiments, offer a comprehensive view of these changes.

The results from NMR centrifugation demonstrate that in coal samples of different ranks, most adsorption pores have diameters smaller than 100 nm. In contrast, effective infiltration pores, which contribute to fluid flow, are typically larger than 100 nm. As coal rank increases, the connectivity between infiltration pores and fractures improves, primarily due to the increased maturity of the vitrinite component. This enhanced connectivity in medium and high-rank coals allows for better permeability and fluid flow. Interestingly, the pore volume of adsorption pores and overall porosity initially decreases from low-rank to medium-rank coal, and then increases as coal continues to mature.

The low-temperature liquid nitrogen adsorption experiments reveal small hysteresis loops, indicating that many of the pores in coal samples are semi-closed, which limits internal connectivity. This finding aligns with the NMR results, which also suggest a significant presence of micropores. These micropores are critical for gas adsorption, but their limited connectivity restricts fluid flow, especially in medium-rank coals.

Additionally, the results of CO₂ adsorption experiments conducted on coal samples of various ranks further support these findings. The pore volume and specific surface area of coal samples decrease as coal transitions from low rank to medium rank. However, as coal matures into high-rank coal, these values increase again, indicating a more developed pore structure in advanced stages of coalification. This pattern is consistent across the three pore testing methods, confirming that coal’s pore structure undergoes significant changes during the coalification process.

Overall, the comparative analysis of different pore testing techniques reveals that coal rank has a significant impact on pore structure. Low-rank coals tend to have a higher proportion of micropores and macropores, while medium and high-rank coals exhibit a more pronounced development of transition pores and smaller micropores. The reduction in macropores is particularly noticeable as coal rank increases, contributing to a more compact and less permeable structure. However, as coal reaches high maturity, the formation of micropores and transition pores compensates for the loss of larger pores, resulting in increased pore volume and specific surface area. These findings offer valuable insights into how coalification influences pore development and highlight the complexity of coal’s evolving pore structure as it transitions from low-rank to high-rank coal^64,66.

Response mechanism of macromolecular structure models of different coal ranks

As coal gasification progresses, the carbon concentration in coal steadily rises, whereas the oxygen content and volatile matter steadily decline (Table 1). The level of aromatic condensation in low rank coal is rather minimal, but it exhibits a higher abundance of bridge bonds and functional groups, as well as a greater presence of low molecular weight compounds. Additionally, the structure lacks any discernible directionality. During the transition from low coal rank to medium-high coal rank, aromatic rings experience condensation, resulting in an increase in the elongation and stacking level of their aromatic layers. The presence of bridge bonds, side chain carbon, and functional groups eventually diminishes, leading to a steady increase in the molecular arrangement’s orderliness. The level of molecular alignment intensifies. Throughout its transformation process, the liberation of volatile substances and the slow breaking of molecular bonds cause alterations in its internal pore structure, ultimately leading to the production of many adsorption pores in high-grade coal. Figure 15 displays the graphic illustrating the pattern of evolution.

Fig. 15.

Macromolecular structure and micropore evolution model of coal.

By conducting simulation studies, we were able to determine the pore volume and surface area of coal molecules with varying coal rankings through the adsorption of CO₂ and N₂ on macromolecular structures of coal. The figure demonstrates a general pattern of initially decreasing and subsequently increasing pore volume and specific surface area, which aligns with the experimental principles governing pore measurement. During the ReaxFF-MD molecular dynamics simulation of coal macromolecules, the pore structure initially diminishes due to the rupture of chemical bonds, and subsequently expands as hydrocarbon gases are generated. The ReaxFF-MD molecular dynamics simulation of coal pyrolysis can be viewed as a progression towards higher coalification, encompassing carbonization, dehydrogenation, and deoxygenation. The porosity value exhibits a pattern of initial decline followed by subsequent increase.

The content and distribution of internal adsorption pores in coal are primarily influenced by the structure of coal macromolecules. Additionally, there is significant variation in the ratio of carbon and oxygen elements among different coal ranks. The macromolecular formulae of different coal ranks exhibit notable variations in their functional groups. As coalification progresses, the coal’s aromatic carbon content and condensation degree rise, leading to a more organized aromatic structure. These alterations have a significant impact on the spaces between the openings of coal macromolecules. Therefore, it is imperative to investigate the molecular process behind the creation of micropores between coal macromolecules.

Conclusions

1. Along with the increasing coal rank, the pore volume of each microscale pore exhibits a declining pattern. Low-rank coal has a microporous volume ranging from 0.0508 to 0.0624 cm³/g with an average specific surface area between 159.64 and 217.27 m²/g. Medium-rank coal, on the other hand, shows a significant decrease in these values, with microporous volumes ranging from 0.0233 to 0.0314 cm³/g and specific surface areas between 70.91 and 112.72 m²/g. In high-rank coal, these values increase again, reaching microporous volumes of 0.0648 to 0.0677 cm³/g and specific surface areas between 208.53 and 213.72 m²/g. The coal samples exhibit a general trend of high pore volume and specific surface area from high rank to low rank, with medium coal falling in between. Additionally, the proportion of adsorption pores initially falls and subsequently increases;

2. Variations in coal rankings result in notable disparities in the attributes of coal macromolecular structure models. The condensation level of aromatic hydrocarbons in low rank coal is comparatively low, characterized by a higher abundance of functional groups and fatty carbon side chains. As the substance matures, the aromatic rings start to condense and the molecular structure becomes more organized. The concentration of fatty side chains decreases, while the ratio of aromatic carbons increases;

3. The evolution of adsorption pores throughout the coal gasification process is closely related to the model of the coal’s macromolecular structure. During the coal gasification process, the molecular bonds inside the coal gradually weaken, causing the macromolecular structure to transition from a state of disorder to a state of order. This results in the formation of many adsorption pores;

4. The interior micropores of coal mostly expand through the elimination of hydrogen and oxygen atoms and the carbonization process that occurs during coal gasification. During the construction and absorption of coal molecules of varying ranks, an increase in coal rank leads to a decrease in both the hydrogen carbon ratio and oxygen carbon ratio of the molecules. Additionally, the pore volume and specific surface area exhibit a pattern of initially decreasing and then increasing.

Author contributions

Wu Li: Writing-Review & Editing, Funding acquisition, Minrui Cui: Writing-Original Draft, Visualization, Resources, Jin Li: Data Curation, Drawing, Editing, Zhonghua Du: Typesetting, Experimental, Xingyu Zhan: Data Curation, Drawing, Typesetting.

Funding

This work was supported by National Natural Science Foundation of China (Grant Nos. 42472225 and 41972169).

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.