High-Level Computer Molecular Modeling for Low-Rank Coal

Oct 16, 2008 - Low-rank coal is a complex mixture; consequently, it is necessary to develop simpler molecular representations for computational modeli...
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Energy & Fuels 2008, 22, 3994–4005

High-Level Computer Molecular Modeling for Low-Rank Coal Containing Metal Complexes and Iron-Catalyzed Steam Gasification G. Domazetis,*,†,‡ B. D. James,† and J. Liesegang§ Physics and Chemistry Departments, La Trobe UniVersity, Melbourne, Victoria, 3086, Australia, and Clean Coal Technology Pty. Ltd., Melbourne, Victoria, 3111, Australia ReceiVed June 13, 2008. ReVised Manuscript ReceiVed September 4, 2008

Low-rank coal is a complex mixture; consequently, it is necessary to develop simpler molecular representations for computational modeling. Our modeling objective has been to develop molecules suitable for semi-empirical (SE) computations of low-rank coal containing transition-metal complexes. These molecular models contain oxygen functional groups that are macro-ligands, forming coordination complexes with specific three-dimentional (3D) orientations; consequently, we develop models that encapsulate the properties of low-rank coals and can form metal complexes. The large computer resources required for SE calculations of these molecules limited their size; of the models examined, those containing numerous short links between phenyl groups caused excessive strain and were unsuitable to model transition-metal complexes. Computations (SE) of our models provided data on (i) hydrogen bonds of coal containing water, (ii) formation of aqua-inorganic species and transition-metal complexes, (iii) pyrolysis chemistry involving transformations of metal hydroxide/oxides, (iv) routes for H2 and CO formation, and (v) mechanism of iron-catalyzed steam gasification. Our char models, on the basis of transformations of the coal model, were consistent with low-temperature pyrolysis; these were disordered structures with some phenyl groups spaced between 0.35 and 0.4 nm. Smaller models of char and chars containing transition-metal clusters were optimized with SE and density functional theory (DFT) computations; these models were useful in modeling the mechanism of catalytic steam gasification. Our modeling of the mechanisms of iron-catalyzed steam gasification was consistent with experimental data.

Introduction The development of molecular models of coal is important for a better understanding of coal use; environmental problems associated with coal use necessitate improvements in the efficiency of coal usage, and these may be obtained through a deeper understanding of the properties of coal. Insights at a molecular level of processes, such as pyrolysis and catalytic steam gasification, are of fundamental importance in the development of new clean coal technologies. Semi-empirical (SE) and ab initio density functional theory (DFT) calculations are attractive methods for computer molecular modeling studies, but such studies are hampered by the absence of a distinct molecular structure of coal. This is because coal is a heterogeneous substance formed after lignocelluloses or plant remains, comprising lignin, polysaccharides, protein, lipids, resins, pigments, and lesser amounts of other materials, were buried and had undergone a wide range of chemical transformations over geological time-scale periods.1-3 It is necessary to develop a molecular model for coal, as a simplified representation of the coal organic mixture, suitable for quantum mechanics molecular computations, but the nature * To whom correspondence should be addressed. Fax: 61-3-9479-1399. Telephone: 61-3-9841-9142. Mobile: 61-3-0402-817-501. E-mail: [email protected]. † Chemistry Department, La Trobe University. ‡ Clean Coal Technology Pty. Ltd. § Physics Department, La Trobe University. (1) Stout, S. A.; Boon, J. J.; Spackman, W. Geochim. Cosmochim. Acta 1988, 52, 405–414. (2) Levine, J. R. AAPG Stud. Geol. 1993, 38, 39–77. (3) Shevchenko, S. M.; Bailey, G. W. Crit. ReV. EnViron. Sci. Technol. 1996, 26, 95–153.

of coal, however, presents a challenge for molecular modeling. Advances in the development of structures of coal have taken place, with impetus from studies related to coal liquefaction, particularly of high-rank coals.4-8 Structural aspects of lowrank coals have also been discussed; for example, liquefaction in tetralin of cuticular liptobioliths at the brown-coal stage (a natural concentration of liptinite) provided asphaltenes and polar and nonpolar resins, which served as a basis for low-level computations of a three-dimensional structure.9 Low-rank coals are perhaps the most heterogeneous because the mixture of vegetation and forest timber is at a relatively early stage of the coalification; thus, models of low-rank coals have included ones based on decomposing trees found in the coal seam.10-14 Lowrank coals contain a relatively large proportion of organic oxygen functional groups, which impart hydrophilic properties, (4) (a) Shinn, J. H. Fuel 1984, 63, 1187–1196. (b) Carlson, G. A.; Granoff, B. Coal Science II. ACS Symp. Ser. 1989, 159-170. (5) Nakamura, K.; Takanohashi, T.; Iino, M.; Kumagai, H.; Sato, M.; Yokoyama, S.; Sanada, Y. Energy Fuels 1995, 9, 1003–1010. (6) Takanohashi, T.; Kawashima, H. Energy Fuels 2002, 16, 379–387. (7) Mathews, J. P.; Hatcher, P. G.; Scaroni, A. W. Energy Fuels 2001, 15, 863–873. (8) Derbyshire, F.; Marzec, A.; Schulten, H.-R.; Wilson, M. A.; Davis, A.; Tekely, P.; Delpuech, J.-J.; Jurkiewicz, A.; Bronnimann, C. E.; Wind, R. A.; Maciel, G. E.; Narayan, R.; Bartle, K.; Snape, C. Fuel 1989, 68, 1091–1106. (9) Patrakov, Yu. F.; Kamyanov, V. F.; Fedyaeva, O. N. Fuel, 2005, 84, 189–199. (10) Faulon, J.-L.; Carlson, G. A.; Hatcher, P. G. Org. Geochem. 1994, 21, 1169–1179. (11) Hatcher, P. G.; Lerch, H. E., III; Koytra, R. K.; Verheyen, T. V. Fuel 1988, 67, 1069–1075. (12) Hatcher, P. G.; Clifford, D. J. Org. Geochem. 1997, 27, 251–274. (13) Hatcher, P. G. Org. Geochem. 1989, 16, 959–968. (14) Drobniak, A.; Mastalerz, M. Int. J. Coal Geol. 2006, 66, 157–178.

10.1021/ef800457t CCC: $40.75  2008 American Chemical Society Published on Web 10/16/2008

Computer Molecular Modeling for Low-Rank Coal

thus retaining a great deal of moisture and which also act as macro-ligands that participate in chemical interactions with inorganic species. The development of a molecular model requires a strategy that commences with a particular rank. The rank of coal is generally based on the calorific value and the vitrinite reflectance; rank-specific data include volatile matter, fixed carbon, elemental composition, carbon and hydrogen ratios, moisture content, and distribution of functional groups. Additional insights are obtained using methods that provide fragments (e.g., liquefaction and pyrolysis), and spectroscopic data (e.g., solid 13C NMR, FTIR, and XPS). Experimental methods are often hampered by mass-balance errors, as observed when the formation of CO2 is taken as a measure of carboxyl groups, and ruthenium-catalyzed oxidation used to assess the presence of large aromatic clusters.15 The determination of oxygen groups in coal is difficult, and various techniques have been used to account for total oxygen and the distribution of oxygen functional groups.16-18 Large variations are observed in the amount of moisture in low-rank coal, of which a relatively small proportion is hydrogen-bonded to the coal molecular matrix, with the remainder present as “bulk” water within the capillaries and macropores. Inclusion of inorganic species within the macromolecular matrix of low-rank coal introduces additional complexity. A large proportion of the carboxyl and hydroxyl functional groups in coal form extensive hydrogen bonds and also form coordination bonds with aqua mono- and multinuclear hydroxyl transition-metal complexes; these groups also participate in pH-dependent aqueous chemistry with cations, including Na+, Ca2+, Mg2+, and K+.19-21 Molecular structures for coal are usually constructed using organic molecular fragments, assumed to be identical to the components comprising the 3D coal macromolecule and are connected with various links to construct a coal model structure. The large number of fragments and numerous connections inevitably yield many possible 3D structures. While the elemental composition of such a 3D structure could reflect the major measured properties of a coal, developing coal molecular models is inherently uncertain and the result is necessarily a simplification. Coal molecular models, consequently, reflect the preferences and interests of the chemists who construct them; the main criterion of the suitability of such models is utility, i.e., the usefulness of the model in achieving particular research objectives. When coal models are used for studies of the molecular chemistry of coal and mechanisms of the various coal processes involving transition-metal complexes, quantum mechanics methods should be employed; this imposes significant constraints on the size of such models. The size limitation may eventually be overcome by advances in computer codes and computing power, but computer modeling also requires a greater understanding of the complex coal system. High-level computation modeling provides data on the fundamental properties of the coal molecular model, such as the total energy of the molecule, heat of formation, bond lengths and angles, hydrogen (15) Murata, S.; Tani, Y.; Hiro, M.; Kidena, K.; Artok, L.; Nomura, M.; Miyake, M. Fuel 2001, 80, 2099–2109. (16) Kelemen, S. R.; Afeworki, M.; Gorbaty, M. L.; Cohen, A. D. Energy Fuels 2002, 16, 1450–1462. (17) Domazetis, G.; Raoarun, M.; James, B. D.; Liesegang, J.; Pigram, P. J.; Brack, N.; Glaisher, R. Energy Fuels 2006, 20, 1556–1564. (18) Murata, S.; Hosokawa, M.; Kidena, K.; Nomura, M. Fuel Process. Technol. 2000, 67, 231–243. (19) Domazetis, G.; James, B. D. Org. Geochem. 2006, 37, 244–259. (20) Domazetis, G.; Liesegang, J.; James, B. D. Fuel Process. Technol. 2005, 86, 463–486. (21) Domazetis, G.; James, B. D.; Liesegang, J. J. Mol. Model. 2008, 14, 581–597.

Energy & Fuels, Vol. 22, No. 6, 2008 3995

bonds, partial atomic charges, and the interactions of functional groups with water (hydrophilic properties) and with various inorganic species. Very large molecular structures, however, require unrealistically large resources for high-level studies; consequently, molecular models of low-rank coals must be restricted to a molecular size imposed by the requirements of SE and DFT computations. In this paper, we discuss the development of a number of coal molecular models and provide results from SE and DFT computations, particularly of models containing transition-metal complexes. Low-rank coal models are discussed in terms of (i) the measured properties of low-rank coals, (ii) the ability of the 3D molecular structure to provide data on properties such as hydrogen bonding involving oxygen functional groups and water molecules situated in the coal, and (iii) the formation of aqua-metal and transition-metal complexes involving carboxyl and hydroxyl functional groups. Our results are discussed in terms of the transformation of coal and inorganic complexes upon heating to form char containing metal species and ironcatalyzed steam gasification studies. Computation Details of computation methods have been given previously;21 briefly, fragments and 2D models were initially examined using the ACD/Chemsketch package.22 Molecular mechanics (MM) and SE computations using the PM5 Hamiltonian were carried out with the Fujitsu CAChe ab initio, version 5.04 package;23 final computations were carried out with MOPAC200224 at the Australian Partnership for Advanced Computing National Facility, Australian National University, Canberra, Australia (APAC-NF). DFT calculations for selected molecular models (limited to a maximum of 300 atoms) were carried out using the Schro¨dinger Jaguar package25 at the Victorian Partnership for Advanced Computing Facility, Melbourne, Victoria, Australia (VPAC). Molecular modeling calculations were carried out in the order (i) MM with MM3 force field, (ii) single-point self-consistent field with the PM5 Hamiltonian (1scf ) a self-consistent field computation for any specific geometry of a molecular structure), and (iii) SE optimization with the PM5 Hamiltonian of the structure to a ground state. A full treatment of coal molecular models containing transition-metal complexes requires multi-electron configuration interaction (MECI) calculations, which required extremely large computer wall time, and only 1scf MECI calculations could be performed.21 SE optimization was also complicated by interactions between the transition metal and adjacent hydrogen atoms, which usually formed short M · · · H and H · · · OH2 distances, and in these cases, each optimized structure was manually examined to assess the extent of such interactions. SE calculations for these difficult structures were performed by varying the minimum allowed ratio for energy change in MOPAC and also by optimizing to a trust radius of 0.2 to 1 as single bond, and so on. A comprehensive bond matrix can also be printed by MOPAC, which splits bonds into σ-π-δ components; this is useful data for bonds involving transition metals. MOPAC provides the default net charges or partial charge on each atom as the Coulson charge; Mulliken populations and partial charges are also provided by MOPAC. Computations of low-rank coal containing water were performed by adding water molecules into the 3D space of a model; MOPAC may also compute the impact of water using the conductor-like screening model method (COSMO), which was carried out for a number of molecular models. For the former method, the molecular models containing water molecules were optimized to a ground state with e20 wt %; models containing a greater number of water molecules were optimized with the additional water molecules located “outside” of the 3D structure by MOPAC. Larger amounts of water required additional 3D space defined by more than two molecular structures of coal, with the excess water situated in the space between them; these models were large and could only be optimized using the MOZYME routine in MOPAC, which uses localized molecular orbitals for closed shell systems and requires lower memory and computer wall time (this generates a Lewis structure, which identifies all hydrogen, σ, and π bonds, lone pairs, and if present, anions and cations).24 These calculations produced the ground state of the low-rank coal molecular model with e20 wt % water; larger amounts of water could not be accommodated within the molecule and were placed “outside” of the coal molecule. Initial DFT calculations of transition-metal complexes and small organic molecules were carried out with CAChe 5.04 DGauss 4.1/ UC-4.1, using Becke 1988; Perdew and Wang 1991 theory, with a triple-ζ-valence uncontracted, 63321/531/41 Gaussian basis set (DZVP, A1) and Li-Rn pseudo-potential, which includes relativistic effects for heavy atoms, as described previously.20 DFT geometry optimization was carried out for all final structures, including small char models (consistent with char produced at 800-900 °C) and these char models containing transition metal, using Jaguar; 1scf-DFT calculations were also carried out for these char models to examine reaction routes for hydrogen and CO formation, as previously described.21,28,29 These char models usually consisted of three molecular fragments, and the geometry optimization provided total energy for a given configuration of the ensemble; the method used in these computations produced an output file, in which each optimization step provided a molecular geometry and its total energy. The data from these output files was used to manually construct a graph of an energy profile to locate the lowest energy configuration of the molecular model. A number of coal models were examined, including ones containing various amounts of water, aqua-inorganic species for Na+, K+, Mg2+, and Ca2+, and transition-metal complexes. The energy changes because of the added species were calculated as the difference between the coal model containing the particular species and the same coal model with the inorganic species placed at an “infinite distance”. This method was difficult to implement for coal models containing transition-metal complexes, because the stereochemistry of these complexes is dependent upon water

Domazetis et al. molecules coordinated to transition-metal centers. For these models, the relative change in energy of the coal model with transitionmetal complexes containing water molecules coordinated to the metal centers was compared to that of the same coal molecular model with the appropriate number of water molecules in the coal structure. Molecular models of coal contained mono- and dinuclear aqua-transition-metal complexes for divalent Cr, Fe, Co, and Ni and trivalent Cr and Fe; these and other coal models containing multinuclear transition-metal species were used to develop models for char containing metal oxides and reduced metal oxides/metals. The transformation of these models was based on experimental data obtained from the pyrolysis of acid-washed coal samples and coal samples containing iron and cobalt complexes. The transformation of the coal models into char models was performed by removing functional groups from the brown coal model based on the pyrolysis chemistry of the loss of carboxyl, carbonyl, ether, and hydroxyl groups.26-29 The resulting molecular structures were acceptable if computations were carried out to a self-consistent field and, for all char models, if optimized to a ground state. Char models containing small metal clusters (Cr, Fe, Co, Ni, and Cu) were also optimized using SE and DFT. Smaller char models, with a maximum of 300 atoms, were constructed for DFT computations; the composition of these structures was similar to chars formed at 800 °C.

Development of Coal Models Coal has been conceptualized as either a solid macromolecular structure (or component) or a two-component structure, in which a mobile component is trapped or clathrated inside a threedimensional cross-linked macromolecular structure.8 1H NMR studies indicate the relationships between the mobile/macromolecular phase model and molecular dynamics and are much more complicated than previously thought.30 Studies of samples of petrified wood samples found in seams of brown coal have led to a postulated structure of modified lignin.9-12 Molecular representations of bituminous coals have been discussed, and fragments identified from solvent extraction studies have been used to develop molecular representation of such coal.4-6 A number of approaches to constructing molecular structures of coals have been discussed, such as a statistical approach,31 a knowledge-based method,32 and a combination of experimental data and computational techniques on a specific maceral, such as vitrinite.7,33 We have developed a molecular model suitable for studies of low-rank coal containing metal complexes, especially octahedral complexes of transition metals; to this end, we have examined various coal molecular models (of a size suitable for SE computations). We examine the impact of the following factors on the total energy and the ∆Hf value of the SE 3D optimized structure: (i) the number of fragments and type of links used in constructing the structure, (ii) the relative numbers of hydrogen, σ, and π bonds in the molecule, (iii) the elemental composition and resulting functional groups distribution, (iv) inclusion of water molecules, and (iv) the addition of inorganic species, especially transition-metal complexes. The model of woody brown coal was not used in our computational studies because it was too large for our purpose; a few computations of this structure indicated the orientation and distances between carboxyl groups were unfavorable for transition-metal complexes (this result is consistent with the smaller amount of added (26) Domazetis, G.; Raoarun, M.; James, B. D. Energy Fuels 2005, 19, 1047–1055. (27) Domazetis, G.; Raoarun, M.; James, B. D. Energy Fuels 2006, 20, 1997–2007. (28) Domazetis, G.; Raoarun, M.; James, B. D. Energy Fuels 2007, 21, 2531–2542. (29) Domazetis, G.; Raoarun, M.; James, B. D.; Liesegang, J Appl. Catal., A 2008, 340, 105–118. (30) Xiong, J.; Maciel, G. E. Energy Fuels 2002, 16, 791–801. (31) Faulon, J.-L.; Carlson, G. A.; Hatcher, P. G. Energy Fuels 1993, 7, 1062–1072. (32) Ohkawa, T.; Sasai, T.; Komoda, N. Energy Fuels 1997, 5, 937– 944. (33) Takanohashi, T.; Kawashima, H. Energy Fuels 2002, 16, 379–387.

Computer Molecular Modeling for Low-Rank Coal Table 1. Properties of the 2D Model Fragments and 3D Coal Model and Typical for Brown Coal. composition MWt analysis density C(ar)/C(tot) H(ar)/H(tot) oxygen groups composition analysis MWt density composition MWt analysis C(ar)/C(tot) H(ar)/H(tot) oxygen groups

analysis C(ar)/C(tot) H(ar)/H(tot) oxygen groups

2D Molecular Fragment Data (I) C79H71NO22S 1418.5 au C, 66.89%; H, 5.05%; N, 0.99%; O, 24.81%; S, 2.26% 1.47 ( 0.06 g/cm3 0.61 0.28 O(OH), 33%; O(COOH), 19% 2D Molecular Fragment (II) C109H103NO30 C, 68.65%; H, 5.44%; N, 0.73%; O, 25.17% 1906.9 au 1.50 ( 0.06 g/cm3 3D Molecular Model Data C258H256N2O78S 4664.9 au C, 66.4%; H, 5.5%; O, 26.8%; N, 0.6%; S, 0.7% 0.6; (O/C) atomic ratio, 0.3 0.2; (H/C) atomic ratio, 1.0 O(COOH), 21%; O(Ph-OH), 34%; O(O-CH3), (C-O-C),(C-OH), 25%; O(CdO), 11%; other, 9% Measured Data for Brown Coal17 C, 67.8%; H, 4.9%; O, 26.4%; N, 0.3-0.6%; S, 0.3-0.6% 0.57-0.65; (O/C) atomic ratio, ∼0.3 ∼0.3; (H/C) atomic ratio, ∼0.9 O(COOH), 17-23%; O(Ph-OH), 35-38%; O(O-CH3), ∼12%; O(R-OH), ∼4%; O(RCdO), ∼23%

iron observed in woody brown coal particles).26 We constructed a molecular structure suitable for modeling studies of low-rank coal; we did this by initially constructing 2D fragments, containing six substituted phenyl, one naphthalenyl, and three cyclic alkyls groups, linked with alkyl, ether, carbonyl, and ester groups. Three carboxyl groups were used: an aryl, an alkyl, and a tetrahydronapthoic group. The relative distribution of oxygen was based on published data16 and our values obtained for Victorian (Australia) and German brown coal samples using X-ray photoelectron spectroscopy (XPS).17 The oxygen groups were distributed as carboxyl, phenolic, hydroxyl, methoxyl, carbonyl, and ester. The composition of the 2D fragments was created to yield the observed properties of brown coal, including C(ar)/C(tot) and H(ar)/H(tot) ratios; they contained either a phenyl group or a sp3 carbon that linked three portions of this structure; Table 1 lists the properties of models and experimental data for brown coal. A coal structure suitable for SE computations, especially for coal models with transition-metal complexes, must enable the formation of octahedral and tetrahedral metal structures, and the orientation of functional groups, particularly carboxyl groups, must be suitable for bond formation about the metal center. Coal models that did not contain the preferred orientation of functional groups formed extremely strained and crowded structures, and high level computations could not be performed (although MM calculations could be carried out for these structure). A larger, less compact 3D structure was also constructed by using additional 2D molecular fragments; this structure was also modified to resemble the “two-phase” concept of coal. Adding transition-metal complexes to this model rendered it computationally very expensive, and only a few SE calculations could be conducted. For this large model, two relatively small and well-known organic molecules were chosen from the CAChe library file to represent a mobile phase; the organic molecules were chosen primarily because they did not significantly alter the elemental composition of the model. Our studies show that a rigorous approach to developing a two-phase coal molecular structure would be extremely complicated and is outside the scope of our present molecular modeling effort. The use of a few 2D molecules significantly decreased the number of possible 3D configurations and maintained the measured properties for the rank of coal for the various configurations that were examined. The relatively small amounts of nitrogen and sulfur

Energy & Fuels, Vol. 22, No. 6, 2008 3997 were varied for a number of molecular models, and it became apparent these did not impact the SE results. If a relatively large number of small aliphatic (-CH2-) or ether (-O-) links were used, the 3D structure became very strained and often coal models containing transition-metal complexes could not be optimized to a ground state; low-rank coals have been reported to contain a variety of bridging groups, with fewer long-chain hydrocarbons, whereas long-chain hydrocarbons have been suggested in coal-derived tar.34,35 Models 1-3 are of brown coal with differing amounts of N and S; three different configurations, labeled models 1a-c, are shown in Figure 1. Models 4 and 7 are also molecules of low-rank coal containing differing numbers of hydrogen, σ, and π bonds. The elemental analyses of models 4-6 are consistent with data obtained for coal progressing in rank from brown coal to subbituminous; the elemental analysis of model 8 is similar to that of a high-rank coal. Models 9, 9a, and 10 are all of brown coal, in which various methods were used to assess steric crowding; model 10 is the largest structure of brown coal studied by us and contains two small organic molecules to resemble the mobile phase within the large macromolecule. Molecular models containing ionic species, such as Na+, K+, Ca2+, and carboxyl anions, could be optimized to a ground state, with oxygen functional groups and water molecules within the coal molecular structure replacing the hydration sphere about the cations. A general approach to developing models of low-rank coals containing transition-metal complexes, however, is very difficult because of the considerable changes to the configurations of coal functional groups imposed by the stereochemistry of octahedral metal complexes; up to six oxygen functional groups of the coal molecule could participate in the octahedral complex. Water molecules within the coal molecule were often included, hydrogenbonded to the oxygen functional groups of the coal and also as water molecules coordinated to the metal center. The 3D character of the coal model is of paramount importance when developing viable structures containing transition-metal complexes, especially when these are modified to resemble experimental data from pyrolysis; in this case, the coal model containing the metal complexes is transformed into a model of char containing metal oxides and metals. Model 9 is an example of a brown coal molecule containing binuclear transition-metal complexes of Cr, Fe, Co, and Ni, constructed to be identical in all respects, with the exception of the transition-metal centers; this was performed to examine trends in the calculated properties of such molecular structures attributed solely to the transition-metal centers of these complexes. Attempts were made to construct coal models with lower strain by building them “around the transition-metal complex”; this was performed by first adding the 2D fragments via coordination bonds to the metal center and then connecting these fragments into a 3D structure. While this approach appeared to minimize strain within the structure, it did not eliminate all of the problems encountered with transition-metal complexes, because the 3D models were optimized into a compact conformation that maximized the number of hydrogen bonds; the relative size of the metal complex and the orientation of the coal oxygen functional groups worked against the compact structure. Model 10, however, was larger and more flexible and could accommodate transition-metal complexes; the size of this model rendered it extremely difficult for SE computations. Molecular models of char were developed by removing various functional groups from the coal model (mainly oxygen functional groups) to mimic the experimentally measured CO/CO2 ratios and weight loss during pyrolysis.21,28 This used experimental data obtained from the slow heating pyrolysis of acid-washed Victorian (Australia) and German brown coal and the same coal samples containing know amounts of iron and cobalt hydroxyl species. Briefly, these models were developed by (i) removing mainly carboxyl groups and some hydroxyl groups, as CO2, CO, and H2O, to give the experimental CO2/CO ratios and (ii) achieving a weight (34) Kidena, K.; Tani, Y.; Murata, S.; Nomura, M. Fuel 2004, 83, 1697– 1702. (35) Islas, C. A.; Suelves, I.; Carter, J. F.; Li, W.; Morgan, T. J.; Herod, A. A.; Kandiyoti, R. Rapid Commun. Mass Spectrom. 2002, 16, 774–784.

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Domazetis et al.

Figure 1. Three configurations of model 1 optimized to a ground; each structure has identical elemental composition and functional groups, but portions of the structure have been manually changed to adopt a differing configuration. Table 2. Data for SE Optimization of Molecular Models of Low-Rank Coal number of bonds model model model model model model model model model model model model model model model model model model model a

1 1a 1b 1c 2 3 4 5 6 7 8 9 9aa 9a (K+) 10 1ab 1a FeIIIb 1a FeIIb

molecular formula (MF)

formula weight (FW)

total energy (eV)

∆Hf (kcal)

H

σ

π

C263H239NO90 C258H256N2O78S C258H256N2O78S C258H256N2O78S C259H265N3O77 C258H264N2O77 C246H229NO62 C279H265O54S C279H263N3O54S C327H305N3O90 C295H206N6O32 C231H237NO72 C231H265NO86 C231H264NO86K C389H395N5O119 C258H256N2O78S C258H258N2O82SFe2 C258H264N2O84SFe2

4853.73 4664.89 4664.89 4664.88 4651.92 4624.89 4191.42 4576.24 4554.19 5716.97 4346.89 4179.38 4431.59 4469.68 7044.36 4664.89 4842.59 4880.64

-60598.20 -57230.53 -57230.60 -57230.67 -57197.62 -56884.78 -50595.58 -53756.09 -53396.67 -69667.60 -48807.25 -51650.05 -55924.10 -55919.63 -86882.78 -57239.16 -59178.13 -59815.87

-3434.70 -3039.19 -3040.66 -3042.47 -2985.95 -2970.48 -2163.86 -1913.31 -1831.33 -3243.99 -94.53 -2776.70 -3621.90 -3708.72 -4568.64 -3239.23 -3307.45 -3441.16

17 17 17 19 12 18 6 6 13 0 12 28

631 630 630 630 639 636 646 642 772 596 571 599

69 57 57 57 51 51 69 69 63 104 42 42

30

962

75

Contains 14 H2O. b COSMO computations.

loss from the coal model similar to that observed experimentally. High CO2/CO ratios were indicative of temperature regions, in which decarboxylation chemistry is predominant (∼300 °C). The loss of all carboxyl, carbonyl, ether, and ∼40% of phenolic groups from the coal model provided a total weight loss of ∼44 wt % (similar to the weight loss observed for brown coal at 700-800 °C). Typical data for brown coal to char and values for coal model to char model were weight loss for aw coal of 13.6 wt % and weight loss from the brown coal model of 12 wt %. Composition of char: C, 70.1%; H, 4.1%; O, 25.4%. Composition of char model: C, 69.8%; H, 5.6%; O, 24.3%. Model 1 was used to develop char molecular models and char models containing transition-metal complexes, over the temperature range of 300-800 °C; these char models were used in studies of the reaction routes to H2 and CO formation. Although lowtemperature metal-mediated pyrolysis does not require a significant contribution from radical chemistry nor inclusion of the condensation of phenyl groups in the model, molecular models of char containing a significant proportion of condensed phenyl groups were nonetheless briefly considered. These char models were formed by manually reconstructing various phenyl groups in close proximity (or adding phenyl groups) into polyaromatic groups and optimizing the resulting structure to a ground state; these transformations were difficult to perform without changing the relative orientations of groups in the coal model, and further, these transformations could not be performed with transition-metal complexes in such a molecular model, indicating that such molecular representations are unsuitable. Calculations were also performed using small graphitic structures with the CtC edge.27 Computations were also performed using smaller isolated coal molecular models to obtain calculated infrared and NMR data; the major spectral features for these differed from experimental values for coal. The trends in these data, however, were qualitatively

similar to those observed experimentally for coal; e.g., the (CdO) stretch shifted significantly to a lower frequency when it was bound to a metal center, and the relative values of chemical shielding for atoms in substituted phenyl groups were similar to experimental values.

Results Table 2 lists SE data for the coal molecular models optimized to the ground state; the calculated and measured properties of a number of coals are listed in Table 3. Models 1a-c, shown in Figure 1, are of a brown coal model of identical elemental composition and functional groups but with portions of each structure changed to adopt a differing configuration. Model 1a shows various structural segments are at a greater distance from each other. Model 1b contains some segments in closer proximity, while model 1c attempts to compact the structure. While such changes alter the appearance of the structures, they were all optimized to a ground state that maximized the internal hydrogen bonds; the results were minor variations in ∆Hf (1000 kcal than the larger, crowded model 5 (C279H265O54S). These large differences are not due to the size of each molecular model but, instead, are due to the nature of the groups used to link the 3D configuration. The ∆Hf value for the coal model containing hydrogenbonded water within the molecule shows that such a model was energetically favored, compared to the same model with an equal number of water molecules placed at a distance from the molecule. Each of the molecular models and the same model containing various amounts of water were optimized to the ground state; the expected increased stability with water was indicated by heats of formation, calculated at -56.9 ( 2.8 kcal per H2O. Data for these coal models with the water molecules situated within the coal structure and with the same number of water molecules at a distance as water vapor, however, gave an additional difference of +4.6 kcal/H2O for water outside the coal molecule (showing that hydrogen-bonded water within lowrank coal is energetically favored). This result is underscored by the linear relationship observed between ∆Hf and the number of water molecules added to model 1, obtained using SE computations.21 The ∆Hf values for the low-rank coal models also correlate with the number of hydrogen bonds; a plot of ∆Hf and the number of hydrogen bonds for the optimized structures in Table 2 provided a reasonable fit (R2 ) 0.9). A similar plot of ∆Hf and the number of σ and π bonds, however, did not show any correlation, but the plot of the total energy and the formula weight of the models yielded a reasonable fit (R2 ) 0.9). Models of Low-Rank Coal with Aqua-Metal Species. Coals contain a large number of inorganic complexes chemically associated with the coal matrix and also occluded or extraneous mineral particles.36 Our models examined inorganic complexes associated with the coal matrix; low-rank coals with high moisture would contain significant amounts of aqua-metal complexes, and transition-metal species would include multinuclear aqua-metal complexes coordinated to oxygen functional groups in the coal molecular matrix.26-29 The relative changes

in the energy of a molecular model attributed to a particular aqua-ionic species in the coal (carboxylate and Na+, K+, Mg2+, or Ca2+) were relatively small and consistent with the ability of the cation to fit within the coal molecule with minimal disruption to hydrogen bonds. 1scf and SE results for a selected number of transition-metal complexes in low-rank coals are listed in Table 3. The 1scf results are for a given structure (initially optimized using MM); QM computations are carried out to achieve a scf (structures that fail to provide an scf result are rejected). The data in Table 3 generally show that the 1scf treatment was for structures that were significantly less energetically favored when compared to the ground state, obtained using SE. An estimate of the contribution by MECI to the energy of various models was obtained from 1scf calculations, and these are also listed at the bottom of Table 3. After 1scf, the structure was subjected to a full SE computation to provide a ground state. A systematic study of the impact of strain on the energy of a coal structure was made for the same coal model with the transition-metal complexes [M(OH)2 · xH2O]4+ (x) 13, M ) Cr, Fe, Co, and Ni); 1scf provided undistorted octahedral complexes with normal M-O and M r O bond lengths. ∆Hf values, for Cr, Fe, and Ni, show these complexes are all less stable (between 120 and 4 kcal) than the coal model without the transition-metal complex, but ∆Hf for the coal model containing the Co complex was more stable. SE results for fully optimized structures of coal containing multinuclear transition-metal complexes show that the stereochemistry about these metal centers was distorted. Coal models containing mono-, di-, or trinuclear complexes were often optimized with short bonds, or the computation terminated at a trust radius of