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Large Scale Molecular Model Construction of Xishan Bituminous Coal Zhiqiang Zhang, Qiannan Kang, Shuai Wei, Tao Yun, Guochao Yan, and Ke-Feng Yan Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b02623 • Publication Date (Web): 24 Jan 2017 Downloaded from http://pubs.acs.org on January 30, 2017
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Large Scale Molecular Model Construction of Xishan Bituminous Coal Zhiqiang Zhanga,*, Qiannan Kanga, Shuai Weia, Tao Yuna, Guochao Yana,b, Kefeng Yanc,d
a
College of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, P. R.
China b
Research Center of Coal Resources Safe Mining and Clean Utilization, Liaoning Technical
University, Fuxin 123000, P. R. China c
Key Laboratory of Gas Hydrate, Guangzhou Institute of Energy Conversion, Chinese Academy
of Sciences, Guangzhou 510640, P. R. China d
Guangzhou Key Laboratory of New and Renewable Energy Research and Development,
Guangzhou 510640, P. R. China
ABSTRACT
The molecular structural information on a Chinese Xishan bituminous coal was obtained using elemental analysis, high resolution transmission electron microscope (HRTEM), laser desorption time-of-flight mass spectrometry (LD-TOF MS), solid state
13
C nuclear magnetic
resonance (NMR), and X-ray photoelectron spectroscopy (XPS) techniques. The size and distribution of aromatic structures have been determined by HRTEM, providing 300 base aromatic skeletons for coal model. Aliphatic side chains and heteroatoms were introduced into these aromatic skeletons according to
13
C NMR and XPS results, which created 300 individual coal
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fragments. The individual fragments were cross-linked randomly with aromatic-aromatic, aromatic-aliphatic, aromatic-oxygen, aliphatic-aliphatic and aliphatic-oxygen linkages to match the molecular weight distribution observed in LD-TOF MS. As a result, the coal model was constructed. The proposed model was comprised of 62 unique individual molecules with a composition of C7972H4882O115N50S30, which is reasonable consistent with the structural and molecular properties determined by experiments. They were also assembled into three dimensional (3D) structure, followed by molecular simulation. The refined 3D model was also verified through the matched helium density between calculated and experimental data. This is the first large scale Chinese bituminous coal model incorporation of diverse molecular weight and structure, which may lead to a further understanding of coal structure–behavior relationship from the molecular level.
1. INTRODUCTION
It is well known that coal is a highly heterogeneous material in nature, comprised of mainly of organic macerals and some inorganic minerals. The organic macerals, our subject of interest, is composed of C, H and O with lesser amounts of S and N. Even within a single maceral a considerable degree of complexity was shown1, 2. The coal structure have been characterized by various analytical techniques, regardless of its inherent complexity and heterogeneity. Conventional analyses such as proximate analysis, ultimate analysis and density provide only bulk properties. With a number of advanced analytical techniques, such as high resolution transmission electron microscope (HRTEM), solid state
13
C
nuclear magnetic resonance spectroscopy (NMR), Fourier transform infrared spectroscopy (FTIR),
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X-ray photoelectron spectroscopy (XPS) and laser desorption time-of-flight mass spectrometry (LD-TOF MS), much more detailed information of coal structure has been obtained. Molecular models provide valuable insights of coal structure at atomistic scales which could contribute to improved understanding about the structure-behavior relationships for coal. Molecular models of coal have gradually populated the coal literature over the past 70 years3. According to Mathews et al.3, more than 134 structural representations of coal have been published. With advances in computational power and software tools, computer-aided molecular design has been used to construct coal molecular representation. Carlson4 introduced the use of computational three-dimensional (3D) representations to various coal models and manifested that molecular modeling should be a valuable tool to study coal. Faulon et al.5 developed the SIGNATURE program designed to automatically generate structurally diverse coal molecules using experimental data. Hatcher et al.6 constructed a molecular model of high volatile bituminous coal using data obtained from elemental analysis,
13
C NMR, and mass spectrometry. The
molecular model of Zao Zhuang bituminous coal and Upper Freeport coal were examined by Takanohashi and co-workers7-9 by a combination of molecular dynamics and 13C NMR chemical shift calculations. Mathews et al.10 also generated the molecular structures of Upper Freeport and
Lewiston–Strockton vitrinites. Molecular structural unit of Fushun nitric-acid-oxidized coal was constructed based on FTIR and
13
C NMR analysis11. These coal models were small−scale (100
atoms to 5, 000 atoms) average molecular structures that ignored meaningful molecular weight distribution and therefore cannot accurately illustrate coal behavioral issues. Although useful for illustrating some structural features of coals, the exploration about the structure behavior relationship of coal is limited. In addition, most of these models were built by hand, which is
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time-consuming, challenging, and should require great expertise3. A leap occurred with the model of Pocahontas No. 3 coal 12. This model contained more than 20, 000 atoms and included a broad molecular weight distribution. Mathews et al.12-14 developed a construction solution of macromolecular model of coals by the aid of various analytical techniques, especially HRTEM and LD-TOF MS. All the previous models have been constructed utilizing the information obtained from indirect techniques. HRTEM technique provides the opportunity to observe and quantify the size and distribution of the aromatic layers in coal15. Meanwhile, LD-TOF MS can identify the molecular weight distribution of cross-linked aromatic moieties, extending the known range of molecular masses in coal by about 100 times over methods previously used16. Compared to use personal favorite to obtain the average molecular structure, the method used by Mathews’ group is an important improvement and a needed step for building large-scale coal models to better capture the structural features of coal. These models were used to study the CO2 sequestration17, solvent-swelling and extraction18, pyrolysis19 and combustion20.. For China, coal provides 70% of primary energy supply and 80% of power generation. It contributes significantly to environmental issues, such as emission of greenhouse gas, and air, water and solid waste pollution. The clean and efficient conversion and utilization of coal is a major problem that remains unresolved at present. This opens new possibilities for coal models which could make a contribution in a meaningful and predictive manner to many aspects of coal conversion and utilization21. The molecular structure and properties of coal will be different as the diversity of origin, such as maturation and coalification history. A general coal molecular model classified by coal rank is infeasible to predict the behavior of specific coal well at all. The only feasible method is to build
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molecular model for the specified coal. In this paper, a Chinese Xishan bituminous coal model comprised of 62 unique individual molecules is proposed. This model is different with previously proposed average coal molecular model due to the fact that the meaningful molecular weight distribution and diversity of coal molecule have been incorporated. This is the only one in this new type of models except those developed in Mathew’s group, which will provide an opportunity to explain coal behavior in a variety of applications. In addition, the construction protocol described in this paper is more efficient than earlier modeling efforts. Here the construction procedure begins with an aromatic skeleton and simply incorporates the correct type and distribution of heteroatoms and aliphatic structures when those smaller-scale molecular models of coals require comparison and reduction of error between data and model.
2. MATERIALS AND METHODS
2.1 Sample and Preparation
A typical run-of-mine bituminous coal was obtained from Xishan coalfield (Taiyuan, Shanxi, China). The coal sample was dry-ground and sieved through a 74 µm sieve. Demineralization was performed using a HCl/HF/HCl acid treatment procedure detailed elsewhere22 to minimize the mineral matter effect during analyses. The precipitate was washed with distilled water until the pH value of the filtrate became neutral and dried until constant weight.
2.2 Conventional Analyses
Mean-maximum vitrinite reflectance was conducted in terms of GB/T 6948-2008 (Method of determining microscopically the reflectance of vitrinite in coal). Volatile matter, ash yield and
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fixed carbon content of raw coal were determined by thermo-gravimetric analysis. The ultimate analysis for the demineralized sample (C, H, N, S and O) was performed using a Thermo Scientific Flash 2000 elemental analyzer. The true density value of the demineralized sample was obtained by means of a JW-M100A helium pycnometer.
2.3 Solid State 13C NMR Spectroscopy
NMR analyses were performed to quantify the structural parameters of the coal sample using a Bruker AVANCE III 600 spectrometer, operating at 150.9 MHz (13C) using methods previously described23. To determine the carbon aromaticity of this coal, a variable contact time cross polarization (CP) magic angle spining (MAS)
13
C NMR experiment was conducted with 11
different contact times in the range from 5 µs to 8 ms. In addition, a dipolar dephasing (DD) experiment was conducted at a 2 ms contact time with 11 different dephasing time from 20 µs to 120 µs for quantifying protonated and non-protonated aromatic carbons. A standard CP MAS 13C NMR was conducted with a contact time of 2 ms to completely polarize all carbons in the coal sample. The chemical shift of 13C was externally referenced to tetramethylsilane. Regarding data processing, each spectrum was baseline-corrected. Integration reset points were taken from the publication of Solum et al.23.
2.4 HRTEM and Image Process
Lattice fringe imaging of the demineralized coal sample was analyzed using HRTEM proposed by Sharma15. In the present study, microgram amounts of coal were ground to fine powder using a mortar and pestle in ethanol and sprayed over a copper microgrid for HRTEM observation using a JEOL JEM 2010 transmission electron microscope at 200 kV. To capture the
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lattice images, the wedge-shaped particle were located and magnified, which then subjected to image processing to extract the lattice fringes. Five fringe images were analyzed for length distribution. The methodology utilized to extract lattice fringes has been described in the literature24. The whole image process and analyses were accomplished utilizing a graphical user interface developed in MATLAB.
2.5 LD-TOF MS
LD-TOF MS was conducted using a Micromass MALDI mass spectrometer equipped with a N2 UV laser. The instrumentation and procedures have been described elsewhere25. Briefly, coal sample were mixed with Milli-Q water. The dispersed slurry was deposited onto the sample plate, and the water was removed from the plate by vacuum. The analyzer was operated at reflector model by using a reflectron mode pulse voltage of 2, 300 V, a source voltage of 15, 000 V and a reflectron voltage of 2, 000 V. Since the detector could be oversaturated by the high abundance of these compounds, no analysis was performed for compounds below 70 m/z.
2.6 XPS Spectra
The coal was examined in a PHI-5000C ESCA spectrometer (Perkin Elmer) using monochromatic Al Kα radiation operated at 250 W. The high voltage was kept at 14.0 kV with a detection angle of 54°. The pass energy of 93.9 eV was applied to ensure sufficient sensitivity. Binding energies were calibrated based on the graphite C 1s peak at 284.6 eV.
2.7 Molecular Model Construction and Evaluation
Individual molecules were constructed using structural data obtained above. The construction of
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the individual molecules was performed using Perl scripts, which was similar to that of Mathews’ group12, 13. The individual molecules were also geometry optimized and packed in a three-dimensional (3D) periodic cell using Packmol26. Molecular dynamics simulation was performed with LAMMPS software27 and the polymer consistent force field, PCFF. A 2.0 ns isothermal-isobaric (NPT) molecular dynamics simulation was carried out at 1 atm and 298.15 K to bring molecules together to a stable conformation using Berendsen thermostat and barostat28. A 1.0 fs time step has been used to integrate the particle motion. The van der Waals interactions were cut off at 15.5 Å, and the Ewald Summation method was used to account for electrostatic interactions. After that, the true density of this coal was estimated based on a minimum criterion following a method similar to that described by Nakamura et al.29.
3. RESULTS AND DISCUSSION
3.1 Information from Conventional Analyses
The results of conventional analyses are summarized in Table 1. From the proximate analysis and the value of mean-maximum vitrinite reflectance, this Xishan coal is a high rank bituminous coal (Chinese Classification of Coals, GB/T 5751-2009). Thus, the influence of maceral structural diversity is reduced, that facilitates the coal model construction30. The ultimate analysis provides the overall percentage of C, H, N, S and O elements present in demineralized sample. The element content of C, H, N, S and O in Xishan coal sample were 91.9, 4.7, 0.7, 0.9 and 1.8 in dry, mineral matter free basis, respectively, which is believed to be the most important parameter for coal model construction13. The measured helium density of this demineralized coal is 1.30 g/cm3.
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3.2 HRTEM Analysis
Currently, HRTEM is the only technique available for observing the coal aromatic structure directly, which has enabled investigators to assign length and number of aromatic fringes to the extracted HRTEM micrographs. In the HRTEM image, The aromatic layers are seen as dark lines when the aliphatic fragments are not readily observed31. Five HRTEM lattice fringe images of Xishan coal were analyzed in order to obtain a statistically representative fringe distribution. Figure 1a show one representative image. The extracted fringe length from these HRTEM images was determined using MATLAB image analyses from skeletonized image. Figure 1b shows the skeletonized image of Figure 1a. The aromatic fringe lengths were quantified using the method proposed by Mathews et al. 13, 32
, assuming that aromatic fringes consist of aromatic structures. Small aromatic molecules used
the following cutoffs:
