Construction of a Multicomponent Molecular Model of Fugu Coal for

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Construction of a multi-component molecular model of Fugu coal for ReaxFF-MD pyrolysis simulation Mingjie Gao, Xiaoxia Li, Chunxing Ren, Ze Wang, Yang Pan, and Li Guo Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b04434 • Publication Date (Web): 16 Mar 2019 Downloaded from http://pubs.acs.org on March 20, 2019

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Construction of a multi-component molecular model of Fugu coal for ReaxFF-MD pyrolysis simulation Mingjie Gao,†,‡ Xiaoxia Li,*,†,‡ Chunxing Ren,†,‡ Ze Wang,† Yang Pan,§ and Li Guo,*,†,‡ †State

Key Laboratory of Multiphase Complex Systems, Institute of Process

Engineering, Chinese Academy of Sciences, Beijing 100190, P. R. China ‡University

§National

of Chinese Academy of Sciences, Beijing 100049, P. R. China

Synchrotron Radiation Laboratory, University of Science and Technology

of China, Hefei, Anhui 230029, P. R. China

ABSTRACT: Proper description of chemical structure diversity is necessary for a coal model in exploring coal pyrolysis mechanism by reactive molecular dynamics (ReaxFF-MD) simulation. This paper presents a strategy for constructing large and reasonable coal models manually with varied chemical structures. A multi-component molecular model containing 23,898 atoms was constructed for Fugu subbituminous coal following the proposed strategy on the basis of characterization data obtained from the proximate and ultimate analysis, 13C NMR, and solvent extraction experiments. The model consists of 75 macromolecules of 20 varied averaged structures for structural diversity and 29 varied small compounds to capture the mobile phase. The elemental 1 / 39

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composition and key structural parameters of the multi-component model agree with the analytical data of Fugu coal sample on the whole. The weight loss profile obtained from slow heat-up (2 K/ps) ReaxFF-MD simulations agrees fairly with the observations from thermo-gravimetric experiments reported in literature. The temporal evolution of a representative product (C2H4) from long-time (2000 ps) isothermal ReaxFF-MD simulations shows qualitative agreement with the results of the synchrotron radiation vacuum ultraviolet photoionization time-of-flight mass spectrometry (SVUV-PI-TOFMS) pyrolysis experiments. These examinations indicate the applicability of the constructed model in ReaxFF-MD simulations to explore coal pyrolysis mechanism. The proposed strategy suggests a feasible approach for manually constructing reasonable large coal models based on limited conventional characterization data.

1. INTRODUCTION Molecular models of coal aid in understanding the complexity of coal chemical structure and exploring coal pyrolysis mechanism by ReaxFF-MD simulation. ReaxFFMD method combines molecular dynamics with ReaxFF reactive force field proposed by van Duin and Goddard et al.[1]. This method allows for simulating the dynamic evolution of radical intermediates and products in coal pyrolysis, which is hard to capture experimentally even with state-of-the-art techniques,[2-3] thus provides a promising approach for investigating the complex chemistry and diverse reaction pathways in coal pyrolysis system. Large coal models allow for better description of the structural diversity of coal, thus permit better description of coal pyrolysis process as coal reactivity is closely related 2 / 39


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to its chemical structure. There is growing interest in exploring coal pyrolysis mechanism by ReaxFF-MD simulation with large-scale molecular models of >10,000 atoms.[4-7] Zheng et al.[8] investigated the model scale effects by comparing the simulation results of three Liulin coal models with varied model scales (2338, 13,498 and 98,900 atoms). They concluded that ReaxFF-MD simulations with small-scale coal model of ~1000 atoms can facilitate observation of reactive sites and reaction pathways in the initial pyrolysis process, while a large-scale molecular model of >10,000 atoms is vital for reproducing the important reaction pathways and reasonable evolution trends of representative products by ReaxFF-MD simulation. Based on large-scale molecular models of Illinois No. 6 coal containing >50,000 atoms, Castro-Marcano et al.[5] performed ReaxFF-MD simulations to investigate the complex coal pyrolysis chemistry, and to further analyze the role of organic sulfur forms permitted by the large scale of the model. Zheng et al.[6-7] also performed ReaxFF-MD simulations to explore the initial reaction mechanism and product distribution in pyrolysis of Liulin bituminous coal using a large molecular model of 28,351 atoms. The overall product evolution tendencies observed from the simulations showed fair agreement with the experiments reported in literature. In particular, the simulated evolution trends of representative tar products (naphthalene, methyl-naphthalene and dimethylnaphthalene) with temperature were found consistent with Py-GC/MS experiments.[6] These work further demonstrated that ReaxFF-MD method combining with large-scale molecular models of coal can provide a promising approach for exploring coal pyrolysis mechanism. 3 / 39


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In addition to large model scale, it is vital to incorporate the structural diversity to study coal pyrolysis mechanism. A large number of molecular level representations of coal have been reported over the past decades[9], including the well-known Given[10], Solomon[11], Wiser[12], and Shinn[13] models. Although useful for revealing some structural features of coal, the majority of these early models are small-scale (10,000 atoms becomes practical and prevail. Narkiewicz and Mathews[15] reported a large molecular model of Pocahontas No. 3 low-volatile bituminous coal that contained ~22,000 atoms within 215 separate molecules. The model incorporated a meaningful molecular weight distribution ranging from 78 to 3286 amu determined via the combination of high-resolution transmission electron microscope (HRTEM) lattice fringe image analysis and laser desorption ionization mass spectrometry (LDIMS). Construction of the aromatic fragments in the large coal model was made feasible with an automated structure generation protocol called Fringe3D on the basis of HRTEM lattice fringe images.[16] The same approach was employed by Castro-Marcano et al.[14] to construct a large molecular model of 50,789 atoms for Illinois No. 6 Argonne Premium coal. The model contained 728 separate molecules that captured a broad and continuous molecular weight distribution in accordance with LDIMS data ranging from 100 to 2850 amu. Recently, Zhang et al.[17] proposed a molecular model for Chinese Xishan bituminous coal using protocols similar to that of Mathews’ group. The model with a composition of 4 / 39


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C7972H4882O115N50S30 was comprised of 62 unique individual molecules and captured the molecular weight distribution to some extent. However, the automated model generating protocols for incorporating molecular weight distribution require various structural characterization techniques, which is not readily accessible. Due to the small fringe length, the distribution of benzene could not be unequivocally distinguished from noise with these protocols,[17-18] limiting their application in low rank coals. It should be noted that the large coal model by Zheng et al.[6] was constructed mainly on the basis of the proximate and ultimate analysis, 13C NMR, and bulk density data of Liulin coal sample. The model gave reasonable description of pyrolysis behavior when employed in ReaxFF-MD simulation. Therefore, it is still of great practical significance to develop a feasible approach for constructing large and reasonable coal models manually on the basis of conventional characterization data of specific coal sample. Construction of large and reasonable coal molecular model is still challenging due to the high heterogeneity of coal. The objective of this work is to present a feasible approach for constructing a large-scale molecular model that can be used to ReaxFFMD simulations of pyrolysis for Fugu subbituminous coal. Section 2 will describe the experiments to characterize Fugu coal sample, the 7-step model construction strategy, and the model examination method. Section 3 will present the coal model constructed step-by-step on the basis of characterization data obtained from proximate and ultimate analysis, 13C NMR, and solvent extraction experiments. The comparison of the results obtained from ReaxFF-MD simulations and the pyrolysis experiments will also be

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presented in section 3 to examine the constructed model. The last section will give a brief conclusion of this work. 2. EXPERIMENTS AND MODEL CONSTRUCTION STRATEGY 2.1 Characterization of Fugu Coal. Fugu coal is subbituminous rank from Shaanxi province of China. Its proximate and ultimate analysis data is listed in Table 1. To examine the chemical structure features, 13C CP/TOSS NMR analysis was performed on a Bruker AVANCE III 400 NMR spectrometer. The frequencies for 13C and 1H are 100.38 MHz and 399.16 MHz respectively, with a recycle delay of 2 s and a contact time of 3 ms. This method has been used in some other literatures.[19-21] The structural parameters derived from the NMR spectrum are listed in Table 2. Table 1. Proximate and ultimate analysis of Fugu coal[22] Proximate analysis (wt %, dry)

Ultimate analysis (wt %, daf)

Volatile

Ash

Fixed Carbon

C

H

N

S

O

35.91

3.70

60.39

81.15

4.90

1.25

0.26

12.44

Table 2. Structural parameters of Fugu coal obtained from 13C NMR[22] Structural fa

fa′

faC

faH

faN

faP

faS

faB

fal

falH

fal*

falO

parameter Value 67.11 62.92 4.19 31.17 31.75 7.76 11.18 12.79 32.89 20.62 6.48 4.72 (%) Note: Fractions of SP2-hybridized carbon: fa = total carbon; fa′ = in an aromatic ring; faC = carbonyl; faH = protonated and aromatic; faN = non-protonated and aromatic; faP = phenolic or phenolic ether; faS = alkylated aromatic; faB = aromatic bridgehead. 6 / 39


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Fractions of SP3-hybridged carbon: fal = total carbon; falH = CH or CH2; fal* = CH3 or non-protonated; falO = bonded to oxygen. Solvent extraction experiments of Fugu coal were conducted in a three-necked flask with two steps of treatments. In the first step, 4 g coal sample and 100 ml toluene were mixed in the three-necked flask and refluxed at 110 °C for 3 hours. The extraction residue was then collected by centrifugation and quantified. In the second step, the residue was further extracted with 100 ml methanol at 70 °C for 3 hours. The two extractions were analyzed using GC/MS after removing the solvents by vacuum evaporation. The extraction yield and extract composition are listed in Table 3. Table 3. Extraction yield and extract composition of Fugu coal[23] Toluene extract

Methanol extract

2.22

1.22

Tetracyclic aromatic hydrocarbon

5.53

--

Tricyclic aromatic hydrocarbon

19.70

17.33

Dicyclic aromatic hydrocarbon

4.79

3.52

Phenolics

1.08

57.33

Aliphatics

43.60

10.58

Acid/esters

8.58

7.51

Alcohols/ketons

14.56

3.50

Total extraction yield (wt %) Composition (wt %)

2.2 Coal Model Construction Strategy. To capture the structural diversity of coal, this work aims at constructing a large molecular model containing multiple components 7 / 39


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for Fugu coal. Experimental data including the elemental composition obtained from the ultimate analysis, the structural parameters from 13C NMR spectrum, and the small molecule composition from the solvent extraction experiments were used as constraints for the target large coal model with multiple components. The 7-step construction strategy employed for the multi-component molecular model is shown in Figure 1. To facilitate the final match of the multi-component model with experimental data, an averaged strategy that makes the constraints applied to each of the macromolecular components was employed.

Figure 1. Construction strategy of the multi-component molecular model As indicated in Figure 1, the empirical formulas for each averaged macromolecule were derived from the elemental composition in Table 1 (Step-I). Then the type and amount of the aromatic nucleus (Step-II), the functional groups and side chains (StepIII) as well as the cross-links (Step-IV) were determined by combining the empirical 8 / 39


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formulas and the structural parameters in Table 2. The heteroatoms of O, N, and S were considered in this stage. The structural units were connected together manually with ChemSketch software[24] to generate the averaged macromolecules that act as major components of the multi-component model (Step-V). To better describe the structural diversity, different averaged macromolecules with varied molecular size and chemical structures were constructed. To capture the two-phase character of coal, both covalently cross-linked macromolecules (immobile phase) and low molecular weight compounds physically trapped within the macromolecular networks (mobile phase) were considered in the model construction process. The composition of the small molecules were derived from the solvent extraction data in Table 3 (Step-VI). The target multicomponent model was constructed by assembling both the averaged macromolecules with varied chemical structures and small mobile molecules into a cubic box using the Amorphous Cell Module of Materials Studio and optimized using the Forcite Module of Materials Studio (Step-VII).[25] 2.3. Model Examination Method. The multi-component molecular model was examined by combining ReaxFF-MD simulations with pyrolysis experiments. The fast pyrolysis experiments were conducted using the pyrolysis apparatus with the volatile species detected by SVUV-PI-TOF-MS at National Synchrotron Radiation Laboratory, China. A detailed description of the pyrolysis apparatus employed can be found in Weng et al. paper.[26] Briefly, the experimental apparatus consists of a pyrolysis chamber with a Shimadzu pyrolysis furnace, a photoionization chamber for introducing the SVUV light, and a TOF mass spectrometer. Nitrogen was used as carrier gas to 9 / 39


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bring the volatile products to the photoionization chamber at a constant flow rate. In our experiments, the furnace was first heated to the specified temperature. The coal sample was then introduced into the middle of the furnace with a quartz pole. Four different temperature conditions (500, 600, 700 and 800 °C) were adopted to investigate the temperature effects on coal pyrolysis. The volatile products were entrained into the photoionization region by the carrier gas and ionized with SVUV light. The background signal was obtained by measuring a blank sample at the same condition. The mass spectra were collected at varied photon energy of 10.0, 11.0, and 12.0 eV. To avoid secondary reactions, the pyrolysis chamber was maintained at low pressure (2.3 mTorr). Slow heat-up pyrolysis simulations were performed in the temperature range of 300 to 2500 K at a heating rate of 2 K/ps to obtain the overall scenario of coal pyrolysis and to compare the weight loss behavior with thermal-gravimetric experiments in literature. Isothermal pyrolysis simulations were performed for 2000 ps to explore the distribution and evolution of major pyrolysis products at varied temperatures (1400, 1600, 1800 and 2000 K) that were subjected to comparisons with what obtained from the SVUV-PITOF-MS pyrolysis experiments. All the simulations were carried out on a single GPU of C2050 using the GPU-enabled ReaxFF-MD code (GMD-Reax) developed in the authors’ group.[27] The parameters of ReaxFF force field used were developed by Mattsson et al.[28] and obtained from the reax package in LAMMPS.[29] The NVT ensemble was used in the simulations with a time step of 0.25 fs. The simulation temperature was controlled using the Berendsen thermostat[30] with the damping constant of 0.1 ps. The bond-order and non-bonded cutoff were set to 0.3 and 10 Å, 10 / 39


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respectively. Three parallel simulations for each simulation condition were performed to ensure a better description of coal pyrolysis process. During all ReaxFF-MD simulations, periodic boundary conditions were applied in all directions in the cubic box. The pyrolysis simulation trajectories were analyzed using VARxMD software developed in the authors' group.[31] 3. RESULTS AND DISCUSSION 3.1 Multi-component Molecular Model. This work aims at a feasible approach for manually constructing large and reasonable coal models that incorporate structural diversity to some extent on the basis of conventional characterization data of the coal sample. For practical computational cost of ReaxFF-MD simulations, a multicomponent molecular model containing 23,898 atoms was constructed for Fugu coal. The model consists of 75 averaged macromolecular components with 20 varied chemical structures and 29 small mobile molecules. The macromolecular components were listed in Table 4 with their chemical formulas. Each macromolecular component with the same chemical formula represents three varied coal molecular structures. The composition and chemical structures of the low molecular weight compounds are presented in Table 5. The construction ideas and the consequent structure information will be presented and discussed in the following sections. Table 4. Composition of the multi-component molecular model for Fugu coal Number of Component

Molecular formula

Varied structures molecules

M-I

C76H63NO9

3 11 / 39


30

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M-II

C151H128N2O18

3

15

M-III

C227H191N3O27

3

9

M-IV

C303H258N4O35

1

6

M-I-S

C76H63NO8S

3

3

M-II-S

C151H128N2O17S

3

3

M-III-S

C227H191N3O26S

3

3

M-IV-S

C303H258N4O34S

1

6

Small molecules

--

29

Table 5. Composition and chemical structures of the small mobile molecules Category

Formula

Schematic

Number

Tetracyclic C16H11N

1

C14H10

3

Tricyclic

C14H11N

1

aromatics

C13H9N

1

C12H9N

1

Dicyclic

C10H8

1

aromatics

C9H7N

1

C11H11NO

1

C11H10O

1

aromatics

Phenolic compounds

C10H8O

& 12 / 39


2

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C8H10O

2

C7H8O

&

2

C6H6O

2

C16H32O2

1

C18H34O2

1

C21H44O

1

C22H42O

1

C21H44

3

C23H48

1

C22H44

2

Acid/esters

Alcohols/ketons

Aliphatic hydrocarbons

3.1.1 Empirical formula of component macromolecules. To facilitate the construction of the averaged component macromolecules, the elemental composition should be derived first and expressed in the form of molecular formula. In general, the sulfur element with the lowest content and highest atomic mass among C, H, O, N, and S should be chosen as a reference to determine the empirical molecular formula. However, the molecular formula with one single S atom would be C832H602O96N11S due to the fact that the content of sulfur in Fugu coal is extremely low. Such a molecular size is too large as one of the component structures of a multi-component coal model of ~20,000 atoms. Therefore, nitrogen, the second leanest element, was chosen as the reference for model construction. The consequent basis set for the empirical formula of the averaged component macromolecules can be expressed as (C76H55NO9S1/11)n. To incorporate a molecular weight distribution to some extent in the target coal model 13 / 39


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while manageable manually, molecular formulas of four varied size were chosen to have parameter n assigned to 1, 2, 3, and 4, respectively. However, even the largest component of (C76H55NO9S1/11)4 can contain less than one S atom. To solve this problem, both component macromolecules with and without sulfur element were constructed. The empirical formula and corresponding elemental composition of the averaged component macromolecules are presented in Table 6. Table 6. Empirical formula and elemental composition of the averaged macromolecules Models

Formula

C/%

H/%

N/%

O/%

S/%

--

81.15

4.90

1.25

12.44

0.26

M-I

C76H63NO9

80.49

5.56

1.24

12.71

0

M-II

C151H128N2O18

80.32

5.67

1.24

12.77

0

M-III

C227H191N3O27

80.38

5.63

1.24

12.75

0

M-IV

C303H258N4O35

80.62

5.72

1.24

12.42

0

M-I-S

C76H63NO8S

79.37

5.48

1.22

11.14

2.79

M-II-S

C151H128N2O17S

79.76

5.63

1.23

11.97

1.41

M-III-S

C227H191N3O26S

80.00

5.61

1.23

12.22

0.94

M-IV-S

C303H258N4O35S

80.33

5.70

1.24

12.02

0.71

Ultimate Analysis

3.1.2 Aromatic nucleus in component macromolecules. It is widely accepted that the chemical structure of low-rank coal is characterized with repeated similar aromatic nucleus linked by various linkages. The carbon structure information of Fugu coal 14 / 39


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sample has been characterized by

13C

CP/TOSS NMR analysis. Such skeletal

information denoted by the structural parameters in Table 2 provides important reference for deducing the composition of the aromatic nucleus. Size and amount of the aromatic clusters. The fraction of aromatic carbon (fa′) and aromatic bridgehead carbon (faB) are two important parameters for describing the aromatic clusters. Solum et al.[32] introduced χb (χb = faB/fa′) as a new parameter to estimate the average aromatic cluster size and proposed an empirical function to correlate χb with the average carbon number in the aromatic clusters. According to this function, the χb value of 0.20 indicates an average cluster size of 10 carbon atoms in Fugu coal, corresponding to bicyclic clusters. So monocyclic, bicyclic, and tricyclic aromatics were selected as the major aromatic structural units, and a small number of larger aryl units were considered for the larger component molecules to expand the structural diversity of the target large-scale model. To make it simple, we first assumed that the aromatic clusters are composed of six-member carbon ring and PAH condensed from six-member carbon ring. Based on the empirical molecular formula, the structural parameters fa′ and faB, and the number of aromatic carbon and aromatic bridgehead carbon in various aromatic clusters, the number of the aromatic nucleus in every component macromolecules were derived. However, some modifications are necessary to have the influence of heteroatom-containing aromatics considered in the component molecules of the target large-scale coal model. Heteroatom-containing aromatic rings. As mentioned previously, the content of sulfur element in Fugu coal is extremely low so that it was introduced by replacing one 15 / 39


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O atom in some component macromolecules. Organic oxygen exists mainly in the form of O-containing functional groups such as carboxyl (−COOH), carbonyl (>C=O), hydroxyl (−OH), methoxyl (−OCH3), and ether (−C−O−C) in coal structure.[33] These O-containing groups usually situate in the side chains of aromatic carbon skeletons thus not considered in the heteroatom-containing aromatic rings. While the majority of organic nitrogen in coal structure exists in the form of pyrrolic and pyridinic, with small amount of aromatic amines.[34] The hetero-nitrogen containing structures exhibit different features in terms of their skeleton carbon atom number. Specifically, the pyrrolic structures have two less skeleton carbon atoms than that of the aromatic clusters condensed from six-member carbon rings, while the pyridinic structures have one less, and aromatic amines have none. With these in mind, the hetero-nitrogen atoms were introduced by adjusting some of the aryl rings to pyrrolic or pyridinic structures. The aromatic carbon atoms reduced by the introduced hetero-nitrogen atoms were complemented by benzene rings. The modified aromatic cluster distribution in the averaged component macromolecules adopted in the target coal model are presented in Table 7. It should be noted that the results in Table 7 are among the many candidates that can meet the constraints. It is beyond the manual construction capability to cover many more possible component molecules in the coal model. Table 7. Distribution of aromatic clusters in the averaged macromolecules Model

monocyclic

bicyclic

tricyclic

tetracyclic

pentacyclic

χb

M-I-a

2

2

1

0

0

0.17

M-I-b

2

2

1

0

0

0.17

16 / 39


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M-I-c

2

2

1

0

0

0.17

M-II-a

3

5

2

0

0

0.19

M-II-b

4

3

3

0

0

0.19

M-II-c

4

3

3

0

0

0.19

M-III-a

5

6

3

1

0

0.21

M-III-b

6

4

4

1

0

0.21

M-III-c

6

5

3

1

0

0.20

M-IV

8

7

3

1

1

0.21

3.1.3 Functional groups and cross-links in component macromolecules. Besides of the aromatic nucleus, deducing of the functional groups, side chains, and cross-links are equally important for the construction of a reasonable coal model. Functional groups and side chains were mainly derived based on the structure parameters in Table 2, which also related closely to the linkage type and link positions. The composition of specific structures in the averaged component macromolecules is presented in Table 8. The phenolic structures correspond to the parameter faP, while the carboxyl and carbonyl groups are closely relevant with faC. The distribution of these functional groups was the result of compromise between constraints of the corresponding structural parameters and the elemental composition, especially the oxygen content. The aliphatic bridges and loops as well as ether bridges that link different aryl units correspond to the parameters as fal*, falH and falO. While the cross-link type and link positions between the aliphatic structures and the aromatic nucleus are closely related to the parameter fap and faS. 17 / 39


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Table 8. Distribution of structural functionalities in the averaged macromolecules Model

phenolic

carboxyl

carbonyl

CH3

CH/CH2

O-bonded carbon

M-I

6

1

2

5

18

4

M-II

12

2

5

10

31

9

M-III

18

3

7

15

45

13

M-IV

24

3

10

20

60

18

3.1.4 Structures of component macromolecules. The averaged macromolecular structures were generated manually by connecting the aromatic nucleus, cross-links, and functional groups together with ChemSketch software[24]. Although the number of these structural functionalities for each component macromolecule were derived, assembling them into the target molecular structures was trivial but not straightforward. The multiple constraints of elemental composition and various structural parameters make it a multi-objective task. With the knowledge on coal structures in mind, the constraints were met with a higher priority for the aromatic structures, the oxygencontaining functional groups of carboxyl and carbonyl groups as well as the phenolic and ether structures. The aromatic nucleus were first linked together with ether bridges, aliphatic bridges, and ester structures. Then the oxygen-containing groups and aliphatic side chains were added randomly to the cross-linked structures. The macromolecular structures were adjusted by varying the number of CH/CH2 units, i.e., the length of aliphatic bridge and side chains at last. The well-known wiser bituminous model[12] was referenced for the connection forms between different aromatic nucleus. The S atom was introduced by replacing O randomly in some of the averaged macromolecules with 18 / 39


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ChemSketch[24]. The structures and major properties of two representative average molecules M-III (C227H191N3O27) and M-IV-S (C303H258N4O33S) are provided as examples in Figure 2.

Figure 2. Structures and properties of two representative average macromolecules: (a) M-III (C227H191N3O27) and (b) M-IV-S (C303H258N4O33S) 19 / 39


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As indicated in Table 6, broad agreement was achieved for the elemental composition between the averaged component macromolecules and the ultimate analysis results except for the content of sulfur, of which the relative deviation reaches 173% at least for the models containing it. The deviation of the sulfur content can be attributed to its extremely low content and relatively high atomic mass, and the molecules would be very large to match the sulfur content, as discussed in section 3.1.1. Fortunately, this problem can be well resolved by mixing the component molecules with and without sulfur element according to specific proportions in the process of constructing the largescale coal models. Despite of this, the averaged components reproduced the elemental composition of Fugu coal sample on the whole. To expand structural diversity, three varied representations were constructed for each of the macromolecular components denoted as M-I, M-II, and M-III in Table 4. The structure of the three representations of M-III (C227H191N3O27) are presented in Figure 3 as an example to illustrate the structural variation among them. The high-lighted structural variations imply for the varied reaction environment in pyrolysis simulations for the aryl units (marked in red solid rectangle) and functional groups (marked in blue dashed rectangle) in the Fugu coal model. Here the aromatic nuclei and aliphatic linkage units were kept unchangeable while the linking manner varied remarkably among the three representations. The tetracylic aromatic cluster (marked in red solid rectangle) in M-III-a locates at the molecular terminal and links to its parent molecule by an ether bridge (Car−O−Car). While in M-III-b, the counterpart connects to its parent molecule by an aliphatic linkage (−Cal−Cal−) with an additional phenyl group attached 20 / 39


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through an ether bridge. In M-III-c, the counterpart connects itself in a more complex manner to its parent molecule by two aliphatic and ether linkages, with an additional large indolyl group linked through an ether bridge. In addition, the distribution of the side functional groups changes along with the varied representations. This can be illustrated by the case of the methoxy group (−OCH3) marked in blue dashed rectangle, whose steric environment varies remarkably among the three representations. These variations increase structural diversity necessary for their closer pyrolysis reactivity in simulation to the real world.

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Figure 3. Structural variations of the three varied structures of M-III for Fugu coal 3.1.5 Large-scale multi-component model. To capture the two-phase model of coal,[35-36] the multi-component model with varied macromolecular structures and small 22 / 39


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molecules was finally constructed in this work to represent the cross-linked component macromolecules and the mobile phase therein. The composition of the low molecular weight compounds are derived from the solvent extraction experiments as listed in Table 5. Moisture is not considered in the multi-component model, though it may serves as small obstacles aiding prevention of spearing and interlocking of molecules during construction [14]. Water effects on pyrolysis of Hailaer brown coal were investigated by Zheng[37] with ReaxFF-MD simulations by adding 10 wt% H2O to the coal model. No significant effect of water on pyrolyzates distribution profiles was found in the temperature range of fast pyrolysis stage. However, adding H2O will increase the model size (e.g., increase the Fugu coal model size by ~3300 atoms for adding 10 wt% H2O). So the moisture was not considered in the Fugu coal model for practical computational cost and ReaxFF-MD pyrolysis simulation purpose. Using Materials Studio[25], the target large multi-component model for Fugu coal was obtained as shown in Figure 4. The constructed model contains 23,898 atoms in total with the empirical formula expressed as C11995H10363N159O1366S15. The equilibrated system in Figure 4 was assembled using the construction function of the Amorphous Cell Module of Materials Studio from geometry optimized structures of all components including the small molecules, following a typical model construction process. Geometry optimization of components were performed with Dreiding force field using the Forcite Module. The averaged component and small molecules packed into the cubic box can be found in Table 3 and 4. The 3D model is constructed initially at a low bulk density of 0.1 g/cm3 to avoid overlapping of aromatic rings and other important 23 / 39


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functional groups. To obtain a reasonable density, the initially constructed model was subjected to compression and decompression using NPT ensemble at pressures of 10 MPa and 0.1 MPa. Energy minimization was performed as the last step to optimize the model as much as possible using the steepest descent method coupled with conjugate gradient method. The equilibrated model has a bulk density of 0.99 g/cm3 that represents a relaxed coal model proper for fast simulation of coal pyrolysis resulted from a looser process from the initial configuration of the model close to true density around 1.28 g/cm3 (air dried basis).

Figure 4. Snapshot of the equilibrated multi-component molecular model for Fugu coal with formula of C11995H10363N159O1366S15 The constructed model consists of 75 averaged macromolecules of 4 varied sizes and 29 varied small molecules, which exhibits a rough molecular weight distribution ranging from 94 to 4526 amu as displayed in Figure 5. The molecular weight 24 / 39


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distribution profile may be not that meaningful as what proposed by Mathews group for the Illinois No. 6 coal molecular model[14]. Such a good distribution profile is hard to achieve manually. Even so, the multi-component model exhibit somewhat a structural diversity with varied structures for each molecular size, which should be a feasible approach for manual model construction as discussed section 3.1.4. In addition, there are some micropores distributed randomly in the model constructed for Fugu coal. Restricted by the model size (~67 Å), however, the constructed model cannot hold large micropores of D>6 Å. The micropore size distribution of the multi-component model of Fugu coal was analyzed that the results can be found in Figure S1 of the supplementary materials.

Figure 5. Molecular weight distribution of the multi-component molecular model The elemental composition and key structural parameters of the multi-component model are comparable to the experimental data on the whole except for the H content, as indicated in Table 9. Particularly, the deviation of the sulfur content discussed previously has been eliminated successfully in the multi-component model by adjusting 25 / 39


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the component ratio. Besides, the aromatic ratio (fa) and the parameter characterizing the aromatic cluster size (χb) both agree well with the experimental data. The relatively large error of H content can be attributed to the averaged strategy. While facilitating the manual construction of the multi-component model, the strategy limits the flexibility of manipulation in generating the component structures and makes it difficult to fully satisfy the constraints for the constructed model. These results validate the reasonability of the final multi-component model constructed at certain extent, which demonstrates the advantage of the large model scale further. Table 9. Comparison between experiments and the constructed 3D multi-component model for Fugu Coal Composition (daf , %)

Structural parameters

C

H

N

S

O

81.15

4.90

1.25

0.26

12.44

fa

faN

faB

χb

67.1 Fugu coal

31.75 12.79 0.20 1 66.1

3D model

80.48

5.79

1.24

0.27

12.22

32.01 12.19 0.20 1

3.2 Model Examination. The multi-component molecular model was examined by comparing the ReaxFF-MD simulations of the model with pyrolysis experiments. Considering the computational cost, the elevated temperature strategy was used for the isothermal simulations. This strategy has been widely used in ReaxFF-MD simulations of coal pyrolysis and many other applications which have been proven to be effective to shorten the simulation time.[5-6,

38]

Reasonable dynamic evolutions of lumped 26 / 39


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pyrolyzates as small gas (C0~C4), light tar (C5~C13), heavy tar (C14~C40), and char of C40+ were obtained from both the slow heat-up and isothermal simulations of the multicomponent coal model using ReaxFF MD.[38]

Figure 6. Evolution of lumped pyrolyzates obtained from heat-up simulations on the multi-component model of Fugu coal at the heating rate of 2 K/ps As indicated in Figure 6, three pyrolysis stages were obtained following what proposed in our earlier publication on pyrolysis simulations of the constructed coal model[38]. Stage-I can be viewed as the activation stage of the whole pyrolysis process. Stage-II corresponds to the major pyrolysis stage, in which most of the weight loss during pyrolysis occurs. It can be further divided into Stage-IIA for primary pyrolysis and Stage-IIB for secondary pyrolysis. The macromolecules (C76+) in coal will break up into relatively small intermediates by rapid cleavage of the bridge bonds in StageIIA, which will crack further into even smaller pyrolyzates in Stage-IIB. Deep cracking and condensation reactions are the major chemical events in Stage-III. More detailed description of the pyrolysis behavior at different pyrolysis stages has been published.[38] 27 / 39


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Despite of the temperature deviation, the stage characteristics and major chemistry events in different pyrolysis stages obtained from ReaxFF-MD simulations agree fairly with the observation from thermo-gravimetric experiments reported in literature[39]. In addition to the lumped pyrolyzates, main volatile products obtained from ReaxFFMD simulations can be confirmed in Fugu coal pyrolysis experiments combined with SVUV-PI-TOF-MS. Compounds evolved from Fugu coal pyrolysis were identified by measurement of mass spectra at different pyrolysis temperatures and photon energies. The mass spectra obtained at the pyrolysis temperature of 700 °C and photon energy of 12.0 eV is shown in Figure 7. The corresponding main volatile products identified both in the experiments and ReaxFF-MD simulations are presented in Table 10. It should be noted that the chemical structures of some isomers are difficult to be identified due to their close ionization energy values with each other, especially for the compounds with large molecular weight. As indicated in Table 10, most of the pyrolysis products detected by SVUS-PI-TOF-MS were observed in the ReaxFF-MD simulations. Besides, the small products and their evolution profiles of H2, CH4, H2O, CO and CO2 were obtained in the ReaxFF-MD simulations, although not detected due to their high ionization energies. The evolution trends with temperature of three representative gas products (NH3, C2H4, and CH2O) were obtained both by ReaxFF-MD simulations and the SVUV-PI-TOF-MS pyrolysis experiment as shown in Figure 8. The profile of CH2O is similar, while the simulated profiles of NH3 and C2H4 are somewhat behind due to the limited simulation time.

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Figure 7. Mass spectra of volatile products from Fugu coal pyrolysis at 700 °C and 12.0 eV by SVUV-PI-TOF-MS experiments. Table 10. Main volatile products identified both from SVUV-PI-TOF-MS pyrolysis experiments and from ReaxFF MD simulations of Fugu coal Identified by ReaxFF MD m/z

Name or Type

Formula

Structure simulation

17

Ammonia

NH3

Yes

28

Ethylene

C2H4

Yes

30

Ethane

C2H6

Yes

30

Formaldehyde

CH2O

Yes

34

Hydrogen sulfide

H2S

Yes

42

Propene

C3H6

Yes

56

Butene/Isobutene

C4H8

Yes

66

Cyclopentadiene

C5H6

No

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67

Pyrrole

C4H5N

No

78

Benzene

C6H6

Yes

92

Toluene

C7H8

Yes

94

Phenol

C6H6O

Yes

C2-alkyl 106

Yes C8H10

benzene 108

Cresols

C7H8O

122

C2-alkyl phenol

C8H10O

Yes Yes

Figure 8. Evolution of representative products obtained from: (a) ReaxFF MD simulations and (b) SVUV-PI-TOF-MS pyrolysis experiments ReaxFF-MD simulation approach has the advantage of describing the dynamic evolution of pyrolyzates during coal pyrolysis process. Particularly, reasonable dynamic profiles of representative intermediates and products can be obtained by simulating large-scale coal models.[5-8] To examine the constructed coal model further, the simulated temporal evolution of C2H4 was compared with that obtained from pyrolysis experiments in which the volatile species was detected using online SVUVPI-TOF-MS. As indicated in Figure 9, the simulated evolution tendency of C2H4 shows 30 / 39


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qualitative agreements with the experimental results, though the simulation temperatures do not fall in the experimental temperature range. Specifically, the content of C2H4 increases gradually with the progressing of pyrolysis at relatively lower temperatures. While at high temperature (2000 K in ReaxFF-MD simulations and 800 °C in pyrolysis experiments), the C2H4 content increases fast in the initial stage and arrives at a plateau then. The simulation temperature for the fast generation of C2H4 falls right in the temperature range of the secondary pyrolysis stage (Stage-IIB) determined from the slow heat-up simulations. The reasonable results obtained from direct simulations of the constructed coal model indicates that the multi-component molecular model constructed is a good structure representation for studying the overall scenario and detailed reaction mechanism of Fugu coal pyrolysis process.

Figure 9. Temporal evolution of C2H4 obtained from: (a) ReaxFF MD simulations and (b) SVUV-PI-TOF-MS pyrolysis experiments Although the objective of this manuscript is to propose a feasible manual approach for constructing large-scale coal molecular models based on limited characterization data, the authors believe that more information about the coal structure, if accessible, will contribute greatly to the model construction process. The average strategy does 31 / 39


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demonstrate a practical manual construction approach for large and reasonable coal models, although it limits the flexibility of manipulation in generating the component structures to some extent. 4. CONCLUSION To get insight into coal pyrolysis mechanism using ReaxFF-MD simulations, a multicomponent molecular model containing 23,898 atoms was constructed for Fugu subbituminous coal. The model was constructed following a seven-step construction strategy on the basis of characterization data obtained from the proximate and ultimate analysis, 13C NMR, and solvent extraction experiments. The target model is comprised of 75 averaged macromolecules of 4 varied size and 29 small mobile compounds that incorporate molecular weight distribution to some extent. Three varied chemical structures were constructed for each averaged macromolecular component to expand structural diversity of the target model. The elemental composition and key structural parameters of the multi-component model agree well with the characterization data of Fugu coal sample. The dynamic evolutions of lumped pyrolyzates and major chemistry events in different pyrolysis stages obtained from ReaxFF MD simulations employing the constructed model agree fairly with the observation from thermo-gravimetric experiments reported in literature. The simulated evolution tendencies of representative products show qualitative agreement with the results of SVUV-PI-TOF-MS pyrolysis experiments, indicating the model’s applicability in ReaxFF-MD simulations to explore coal pyrolysis mechanism. The proposed construction approach suggests a feasible

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strategy for constructing reasonable large coal models manually based on limited conventional analytical data. ASSOCIATED CONTENT AUTHOR INFORMATION Corresponding Author *Phone: 86-10-82544944. Fax: 86-10-62561822. E-mail: [email protected]. Present Addresses State Key Laboratory of Multiphase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, No. 1 Zhongguancun North Second Street, Beijing 100190, P.R. China. Notes The authors declare no competing financial interest. ACKNOWLEDGMENT This work was supported by the National Key Research and Development Plan of China under Grant [2016YFB0600302], the National Natural Science Foundation of China under Grant [21606231, 91434105], the Foundation of State Key Laboratory of Coal Combustion under Grant [FSKLCCA1903], and China’s State Key Laboratory of Multiphase Complex Systems under Grant [MPCS-2017-A-03]. REFERENCES 33 / 39


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Construction of a Multicomponent Molecular Model of Fugu Coal for

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