FLASHCHAIN Theory for Rapid Coal Devolatilization Kinetics. 11. Tar

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FLASHCHAIN® Theory for Rapid Coal Devolatilization Kinetics. 11. Tar Hydroconversion During Hydrogasification of Any Coal Stephen Niksa Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b01614 • Publication Date (Web): 15 Jun 2018 Downloaded from http://pubs.acs.org on June 16, 2018

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FLASHCHAIN Theory for Rapid Coal Devolatilization Kinetics. 11. Tar Hydroconversion During Hydrogasification of Any Coal Stephen Niksa Niksa Energy Associates LLC, 1745 Terrace Drive, Belmont, CA 94002 (650) 654 3182; [email protected] ABSTRACT This paper introduces a FLASHCHAIN-based reaction mechanism for oils production during tar hydroconversion with any coal for any hydrogasification conditions. Oils are generated by the hydrogenation of tar monomers in two stages. In the first stage, the tar monomers released as primary tars are rapidly hydrogenated into oils at the monomer hydrogenation rate. Since elevated pressures always shift primary tar molecular weight distributions toward lighter species, monomers constitute substantial fractions of primary tar, and as much as half the ultimate oils yield is produced soon after the onset of tar hydroconversion. In the second stage, additional tar monomers are gradually released by hydrocracking of larger tar molecules and then hydrogenated into oils, while control of the oils production rate shifts from monomer hydrogenation to hydrocracking. Oils yields are uniform with H2 pressures higher than 1 MPa because rates of monomer hydrogenation and hydrocracking accelerate for progressively higher

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H2 pressures to compensate for diminishing primary tar yields. Predicted oils yields grow for progressively hotter temperatures. The analysis shows that aliphatic tar components must be incorporated into oils along with their aromatic nuclei during monomer hydrogenation, and constitute half or more of the oils yield at the highest H2 pressures. Primary tar composition and, especially, their structural components determine the maximum oils yields from different coals. The sample-to-sample variability in primary tar yields is apparent in their associated oils yields. In combination, the mechanisms for hydropyrolysis, tar hydroconversion, and char hydrogasification accurately interpreted a database representing coals of rank from lignite to anthracite; heating rates from 1 to 104 C/s; temperatures from 475 to 900 C; coal contact times from 1 to 900 s; gas contact times from 2 to 42 s; and H2 pressures from 0.3 to 15 MPa.

Keywords:

Hydropyrolysis,

Hydrogasification,

Oils,

Tar,

Reaction

Mechanism,

FLASHCHAIN


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Introduction Throughout the 1980s, coal hydropyrolysis was aggressively developed to produce chemical feedstocks and transportation fuels from coal as a technological response to the OPEC oil shocks. Mixtures of single-ring aromatic compounds were the primary focus of worldwide R&D activities, and a huge database of product distributions was compiled to identify the coals and hydrogasification conditions that maximized oils yields.

Reaction mechanisms have been

developed, albeit recently, to quantitatively interpret how coal quality and the processing conditions affect total coal conversions during hydrogasification.1,2 But no mechanism had ever accurately depicted oils yields from diverse coals across the hydrogasification operating domain. This paper combines the FLASHCHAIN-based mechanism for coal hydropyrolysis1,3 with a new reaction mechanism for tar hydroconversion to accurately predict oils yields from any coal at any hydrogasification condition. Oils yields from hydropyrolysis alone are small fractions of the ultimate yields.

So the most direct evidence for tar hydroconversion during coal

hydrogasification is an abundance of oils, light gaseous hydrocarbons (GHCs), and moisture with very little polynuclear aromatic hydrocarbons (PAH) at moderate temperatures, and that the product distributions relax to methane and moisture at hotter temperatures, with minor amounts of ethane, carbon oxides, NH3, and H2S. The gross simplification of primary products under elevated H2 pressures contrasts with the predominance of PAH and, ultimately, soot under inert atmospheres, along with GHCs, oxygenated gases, H2, HCN, and H2S.4 Once all polynuclear tar compounds have been hydroconverted, the distribution of oils and noncondensable gases is determined by reforming chemistry in the gas phase, which explains why CH4 and moisture are the ultimate products given sufficient contact time and thermal severity under elevated H2 pressures.


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This paper first reviews the underlying process chemistry and the formal mathematical development of the tar hydroconversion mechanism, then presents quantitative interpretations for variations in heating rate, temperature, reaction time, H2 pressure, and coal quality.

The

following sections first describe the phenomenology and then, in series, the state variables that describe tar hydrogenation and hydrocracking; the associated conservation equations; and the model validation work. Mathematical Analysis Phenomenology The proposed tar hydroconversion mechanism describes the disintegration of a tar molecular weight distribution (MWD) into oils and additional noncondensables. It does not describe the elimination of substituents from oils; the decomposition of oils into alkanes and olefins; the conversion of GHCs into CH4 and C2’s; water-gas shifting; and other prominent stages of homogeneous reforming chemistry. Validated elementary reaction mechanisms are already available to easily simulate the chemistry of mixtures of single-ring compounds and lighter organic species, including pollutant formation. Indeed, phenomenological tar hydroconversion chemistry represents a bridge from phenomenological reaction mechanisms for primary hydropyrolysis to the knowledge-base on hydrocarbon reforming chemistry developed during the last 50 years. The present analysis enables this approach within any temperature range, although target applications almost always have temperatures below about 900 C judging from the domain of test conditions in the literature. Heterogeneous tar hydroconversion from a free stream on char or other reactive solids is omitted. The proposed mechanism therefore describes the homogeneous hydroconversion of C/H/O/N/S in primary hydropyrolysis tar into oils, GHCs,


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CO, CO2, H2O, H2S, NH3, and H2, but omits the succeeding conversion of oils into additional GHCs and the reforming of noncondensables into CH4 and moisture. Simulations that explicitly couple the mechanisms for hydropyrolysis, tar hydroconversion, homogeneous reforming, and char hydrogasification are forthcoming. The tar hydroconversion mechanism incorporates all the steps in the FLASHCHAIN-based mechanism for tar decomposition under inert gases,4 including those for soot production. Even though sooting would be completely disrupted under commercial hydrogasification conditions, it is included in the analysis to span the range of low-to-moderate H2 pressures in conventional gasification applications where hydroconversion can interfere with, but not completely eliminate soot production under some conditions. Unfortunately, the available database does not identify the threshold H2 pressure that completely suppresses soot production. Three roles for H2 are proposed for tar hydroconversion, the first of which is analogous to the roles proposed in primary hydropyrolysis in the condensed coal phase:1 (1) Hydrogenation of labile bridges and peripheral groups in tar fragments without any transformations of aromatic nuclei or bridge scissions, accompanied by suppression of recombinations among the ends of tar fragments that would otherwise shift the tar MWD toward heavier fragments, and thereby diminish the precursors to oils; (2) Hydrocracking of the labile and hydrogenated bridges and char links in tar to produce smaller tar fragments without any transformations of aromatic nuclei; and (3) Hydrogenation of isolated tar monomers into oils, moisture, H2S, and NH3. All three processes utilize ambient H2 at rates that accelerate for progressively higher H2 pressures. Hydrogen may react with the components of labile bridges in various ways, including rupture of hydroaromatics, saturation of olefins into aliphatics, and conversion of carboxylic acids into alcohols. The elimination of carboxylic acids is especially important because carboxylic acids


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are widely regarded as crosslinking agents that skew bridge conversions toward the spontaneous generation of refractory char links away from scission of longer fragments into smaller ones. Once a tar bridge has been hydrogenated, its only decomposition pathway is scission because its potential for spontaneous conversion into a char link has been eliminated. Accordingly, bridge hydrogenation shifts the tar MWD toward lighter fragments, away from the size range that may spontaneously nucleate into soot, and also enhances oils yields by promoting the production of tar monomers. Once a bridge has been hydrogenated, it may also interfere with another charring process, bimolecular recombination of tar fragments.

Whenever a hydrogenated bridge breaks, its

remnants will remain attached to the newly formed ends of the two new fragments. A fragment end that had been hydrogenated, either with or without the remnants of its parent hydrogenated bridge, is regarded as capped by stable functionalities and therefore unable to produce a char link in combination with another fragment end. According to the tar decomposition mechanism for inert atmospheres, without hydroconversion the ends of tar fragments can recombine regardless of whether or not the end contains the remnants of broken bridges.

Since hydrogenation

eliminates unsaturated components from bridges, and since such components readily condense further into aromatics, and since aromatics are essential to the refractory character of char links, hydrogenation suppresses bimolecular recombination. Hydrocracking destroys labile and hydrogenated bridges and char links in a tar fragment. Each of these channels produces two smaller product fragments which have labile, hydrogenated, or capped ends, depending on the original linkage.

These reactions incorporate ambient H2,

although the stoichiometric coefficients are deemed to be negligible because the explicit purpose of hydrocracking is to disintegrate tar fragments into smaller ones and, ultimately, to promote


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monomer production and thereby enhance oils production. None of these channels produces noncondensable gases, so hydrocracking is solely a scission process. In the tar decomposition mechanism, oils form from a tar monomer, provided that one of the two sites for end groups contains either a labile or hydrogenated peripheral group to act as a hydrogen donor. All the carbon in the nucleus is incorporated into the oils, whereas all carbon in the fragment ends becomes noncondensable gases.

In contrast, the proposed monomer

hydrogenation process generates oils from monomers with two end groups of any form attached to an aromatic nucleus, including capped and open ends. The types of the end groups determines how much oils form, because all the carbon in a monomer – both aromatic and aliphatic - is converted into oils, and also whether H2 and H2O act as reactants or products, because oils contain oxygen and hydrogen in fixed proportions.

For example, with two hydrogenated

peripheral groups, H2 could conceivably be released if their H-contents exceeds the Hrequirement of oils; and with two open or capped ends, the oxygen requirement in oils may need to be supplied by moisture as a reactant. Regardless of the forms of the end groups, all the carbon in the monomer is incorporated into oils so that the stoichiometry for oils production will be a weighted sum over all possible end group configurations. Tar Constitution The feedstock into the analysis is a stream of volatiles with primary tars from rapid hydropyrolysis. In abstract terms, primary hydropyrolysis is easily distinguished from secondary chemistry: Primary hydropyrolysis is the result of chemistry within the condensed coal phase, whereas secondary chemistry occurs in the gas phase beyond the interfacial area around the condensed phase. Even though the interface between the condensed and vapor phases is


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conceptually well-defined, numerous ambiguities still arise in practical applications. This analysis assumes that primary tars are generated at heating rates so fast that their transit time to the external particle surface is too short to sustain any tar conversion during transport. The threshold heating rate is about 1C/s for the sizes and temperatures in common coal utilization technologies. Primary tars may spontaneously react as soon as they are released into an ambient stream if the temperatures are sufficiently high, or they may be transported at cooler temperatures into a second, dedicated environment for their sequential hydroconversion. In the proposed tar hydroconversion mechanism, tars' macromolecular structure is rendered in terms of the structural components of FLASHCHAIN1 as a mixture of chain molecules ranging in size from a monomer to a specified degree of polymerization, 2J*. The diverse assortment of structural components in real tars is rendered coarsely with the same four structural components used for the parent coal: aromatic nuclei (A), labile bridges (B), char links (C), and labile peripheral groups (S), along with new structural components for hydrogenated bridges (B*) and peripheral groups (S*), and open fragment ends that had lost hydrogenated peripheral groups (I). Ends of fragments that lost labile peripheral groups are denoted by E. The model is formulated in terms of scaled molar concentrations, in units of moles per volume in the gas phase. All species concentrations are scaled with respect to the initial concentration of aromatic nuclei in coal, A0, expressed as a gas phase concentration, AGAS, which couples the coal loading into the analysis.4 Whereas the symbols that denote tars’ structural components are the same as those used previously for fragments in the condensed coal phase, the tar symbols have units of a gas phase concentration, rather than a concentration in the condensed coal phase. The proportions and elemental compositions of the structural components A, B, B*, C, S, S*, E, and I are specified from the predicted ultimate analysis of primary tar with the tar constitution submodel,


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which implements the same relations as FLASHCHAIN’s coal constitution submodel for hydropyrolysis.1,5 These assignments constitute the most important reactant specifications for the proposed tar hydroconversion mechanism. The aggregate amounts of tar, oils, and gas are denoted by T, O, G, and G*, respectively, where G originates from labile bridges and peripheral groups and G* only comes from hydrogenated peripheral groups. For the tar lump which is distributed in size, the concentration of chains of degree of polymerization j (i.e., j linked nuclei) is denoted by tj. The degree of polymerization of the largest tar chain is 2J*, which is twice that of its largest precursor in the condensed coal phase, called Metaplast, because primary tar fragments may recombine in the vapor phase during tar conversion. In principle, tar weights extend to 2000 to 4000 g/mol, depending on the parent coal constitution, but for the elevated H2 pressures in the target applications, extents of the MWDs of primary tar are only half as large. Longer tar chains are omitted because tj concentrations fall off sharply for progressively greater degrees of polymerization. Aromatic nuclei are refractory units having the characteristics of the hypothetical aromatic cluster inferred from 13C NMR spectra. They also contain all the nitrogen and thiophene sulfur (Sth). Except for NH3 production from their nitrogen and the decomposition of Sth into H2S, nuclei are immutable if they are linked to other nuclei. But the individual nucleus in an isolated tar monomer may be hydrogenated into oils, moisture, NH3, and H2S. Nuclei are interconnected by labile bridges, hydrogenated bridges, and char links. Labile and hydrogenated bridges are groups of aliphatic, alicyclic, and heteroatomic functionalities, not distinct chemical bonds. They contain all the oxygen, aliphatic carbon, hydrogen, and non-thiophene sulfur, but no aromatic components except aromatic sulfides. Labile and hydrogenated peripheral groups are the remnants of broken bridges that have the same C/H/O/S composition as their respective


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bridge precursors. Labile bridges that decompose into char links during tar conversion leave a fraction of their oxygen in the char link. This residual oxygen is released as CO at high temperatures. Hydrogenated bridges do not decompose into char links. A unit within a tar molecule comprises an aromatic nucleus plus, if intact, both its linkages or, if on a chain end, its linkage and peripheral group, if there is any. Chains cannot be resolved for accounting purposes into identical monomeric units because linkages within these units can be char links, labile bridges, or hydrogenated bridges even in primary tars, and chain ends may or may not contain labile or hydrogenated peripheral groups or half a char link. As seen below, various probabilities describe the proportions of each kind of link and of chain ends having any form of peripheral groups versus open ends which had or had not been previously hydrogenated, in the tar molecules initially and throughout their conversion. On a mass basis, each labile bridge is further resolved into a char link and two gas precursors; similarly, labile peripheral groups are resolved into one-half char link plus one gas precursor. Consequently, a half-link is permanently attached to each chain end that had never been hydrogenated, but the associated gas precursors are transitory. But neither hydrogenated bridges nor hydrogenated peripheral groups contain char components. The initial MWD of primary tars and its dependence on the operating conditions are predicted by FLASHCHAIN® for hydropyrolysis from the proximate and ultimate analyses for the parent coal. Throughout primary tar production, precursor fragments in the condensed phase disintegrate as bridges break and reintegrate as char links form, so that the MWD changes continuously. The chemical constitution of even the primary tar molecules changes throughout hydropyrolysis because the constitution of Metaplast, their precursors in the condensed phase, changes throughout hydropyrolysis. There are proportionally more ends among the shortest


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chains so Metaplast fragments tend to be more aliphatic initially, when all ends have peripheral groups. As primary hydropyrolysis proceeds, the Metaplast tends to become relatively enriched in char links, because of bimolecular recombination and spontaneous bridge charring. Since all tar molecules devolve from Metaplast, it is clear that the chemical constitution of primary tar changes throughout hydropyrolysis. Instantaneous probabilities describe the average chemical constitution of chains of a particular size. Seven probabilities are required: ptj(t), the instantaneous fraction of all potential links within tj fragments which are intact; ptjl(t), the fraction of all potential links which are labile bridges; ptjl*(t), the fraction of all potential links which are hydrogenated bridges; ptjS(t), the fraction of all chain ends which have a labile peripheral group; ptjS*(t), the fraction of all chain ends which have a hydrogenated peripheral group; ptjE(t), the fraction of all chain ends which were previously labile but no longer have a peripheral group; and ptjI(t), the fraction of all chain ends which were previously hydrogenated but no longer have a peripheral group. These probabilities are evaluated from the following expressions:

pt j 

p

l tj

Bt j  Bt*j  Ct j jt j



Bt j



and

jt j

j 1 j

p

l* tj

(1a)



B t*j jt j

(1b)

so that p tl j ptj



Btj ( j  1) t j

*

and

p tl j

ptj



B t*j ( j  1) t j

(1c)

Equation 1c gives the proportions of labile and hydrogenated bridges among j - 1 links in a tar fragment with j bound nuclei. For the ends of a fragment,


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ptSj 

ptEj 

p

S* tj



ptIj 

St j

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(1d)

2t j Et j

(1e)

2t j S t*j

(1f)

2t j Itj

(1g)

2t j

In turn, these relations specify the proportions of labile peripheral groups; eliminated labile peripheral groups; hydrogenated peripheral groups; and eliminated hydrogenated peripheral groups on fragment ends. Once the concentrations of all tj have been determined, pT, the total intact-link probability in the entire tar lump is assigned from 2J*

pT 

B  B * C 2J*



j 1

 1

jt j

t j 1

j

2J*



j 1

jt j

(1h)

Both summations are evaluated from the concentrations of tj. Analogous relations specify the other structural probabilities for the entire tar fragment population. Proposed Reactions Fifteen chemical processes, diagrammed in Table 1, represent the spontaneous hydroconversion of tar fragments: Hydrogenation of labile bridges and peripheral groups; hydrocracking; monomer hydrogenation into oils; scission of labile and hydrogenated bridges; spontaneous charring of labile bridges; bimolecular recombination; elimination of labile and hydrogenated peripheral groups; release of oxygen from nascent char links; release of nitrogen from nuclei;


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Table 1. Diagrams for the fifteen proposed reactions. Reaction Diagram Hydroconversion Labile bridge hydrogenation tj-k–B–tk + HYH2 tj-k–B*–tk Labile peripheral group hydrogenation tj·S+ (HY/2)H2  tj·S* t -(B,B* or C)–tk  (S,S* or E)·tj-k + Hydrocracking j-k (S,S* or E)·tk (S,S*,E or I)-t1-(S,S*, E or I) + MHH2 Monomer hydrogenation O,MHO + H2O,MHH2O Tar Decomposition t –(B or B*)–tk  (S or S*)·tj-k + Scission of labile and hydrogenated bridges j-k (S or S*)·tk Spontaneous charring tj-k–B–tk  tj-k=tk + νCG Bimolecular recombination tj·S + tk  tj=tk + (νC/2)G Elimination of labile and hydrogenated t ·(S or S*)  tj + (νG*G* or (νC/2)G) peripheral groups j Release of char-O C-OC  CO + C’ Release of N in nuclei A-N  NH3 + A’ Release of Sth in nuclei A-Sth  H2S + A’ Oil production t1·(S or S*)  bOO + ( bi Gi or bi*Gi*) Soot Nucleation tj  RjR + cij Gi ; J*+1 < j < 2J* Soot Addition tj + R (Rj+1)R + cijGi ; 1 < j < J* Oil Addition O + R (R,O+1)R + ci,OGi release of Sth from nuclei; oil production from tar monomers; nucleation of the largest tar molecules into soot; addition of smaller tar molecules onto soot; and addition of oils to the soot phase. Rates of these reactions only partially determine rates of product evolution, because of the independent influence of macromolecular configuration.

The tar hydroconversion

mechanism comprises the 11-step reaction mechanism in the FLASHCHAIN-based tar decomposition mechanism4 plus four new reactions. The only changes to the tar decomposition mechanism are that scission now opens both labile and hydrogenated bridges; gases are produced via elimination of both labile and hydrogenated peripheral groups; and oils form from monomers with either labile or hydrogenated peripheral groups. Otherwise their characteristics and rate expressions remain the same and will not be reiterated. Only the four reactions that incorporate


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ambient H2 are considered further. The labile bridge hydrogenation rate is developed in terms of the H2 concentration in the gas phase, CH2, in moles/vol. The bridge hydrogenation reaction is based on

B  HY H 2  B *

(2a)

where B and B* are the molar concentrations of labile and hydrogenated bridges in tar summed over all fragment sizes, respectively; and HY is the stoichiometric coefficient for complete hydrogenation. The global bridge hydrogenation rate is given by

RHY  k HY BCHnHY2

(2b)

where kHY is a distributed-energy rate constant and nHY is an empirical reaction order. The stoichiometric requirement for hydrogenation is based on complete hydrogenation of all carbon, oxygen, and sulfur in the labile bridge. FLASHCHAIN’s tar constitution submodel4 already defines the average numbers of these three elements per bridge, CNB, ONB, and SNB. The carbon is hydrogenated into a mixture of CH4 and C2H4, in proportions that maintain an H/C ratio of three. All oxygen becomes H2O and all sulfur becomes H2S. Hence, hydrogenation leaves only short methylene hydrocarbon chains capped by methyl groups and alcohol functional groups in the hydrogenated bridge, which is the theoretical maximum extent possible. This limiting structural situation specifies the stoichiometric requirement for hydrogenation as the difference between the H-numbers of hydrogenated and labile bridges, according to

 HY 

3 C N B  2( O N B  S N B )  H N B 2

(2c)


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where HNB is the number of H-atoms per labile bridge in hydropyrolysis tar. This value already accounts for the assortment of mostly unsaturated functional groups in the original bridges, including carboxylic acids. As always, labile bridges decompose in independent pathways for scission and spontaneous condensation, and the selectivity for bridge conversion is fixed throughout. But hydrogenated bridges never spontaneously condense into refractory char links plus noncondensables, because of insufficient aromaticity. Hydrogenated bridges may only decompose via scission into two hydrogenated peripheral groups. The scission rate is evaluated with the decomposition rate of labile bridges, without any scission selectivity coefficient. Noncondensables are not released during the scission, although the resulting hydrogenated peripheral groups may subsequently decompose into noncondensables. Bridge hydrogenation also suppresses bimolecular recombination reactions if either one of the participating fragment ends holds the remnants of a broken hydrogenated bridge, or is bare but had been hydrogenated previously. The interference is imposed even if the remnants of the hydrogenated bridge were previously expelled as noncondensable gases, because the condensation of aromatics is strongly activated by aliphatic and olefinic groups on the peripheries of the aromatic structures. Condensed ring structures without any peripheral groups must be activated directly before they can recombine, and this is the assumed rate-limiting step in the condensation process.. Consequently, hydrogenation directly shifts the bridge decomposition process toward scission by eliminating the decomposition pathway that produces char links, and further suppresses char link production by eliminating bimolecular recombinations for selected fragment end configurations.


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It thereby generates smaller fragments for progressively greater extents of bridge hydrogenation. Since more monomers will also be generated, hydrogenation enhances oils yields. And since all bridge elements may ultimately be converted into noncondensables because no char links form from a hydrogenated bridge, hydrogenation also enhances noncondensables yields.

Bridge

scissions also inhibit the production of the largest fragments which are the only ones that can nucleate soot. So bridge hydrogenations suppress soot production when tars are converted under H2, albeit as only one factor among others. The hydrogenation of labile peripheral groups and their subsequent decomposition into noncondensables are completely analogous to their counterparts for labile bridges because labile peripheral groups have the same compositions as labile bridges. The only difference is that peripheral groups are half as large. Consequently, the same hydrogenation kinetics are applied to both structural components. The hydrocracking process is uniformly applied to labile and hydrogenated bridges and char links with a common set of kinetic parameters, according to RHC , B  k HC BCHnHC2

; RHC , B*  k HC B*CHnHC2

; RHC ,C  k HC CCHnHC2

(3)

where kHC is an Arrhenius rate constant and nHC is an empirical reaction order. Each rate entails the same rate constant and H2 dependence, so the individual linkage levels determine the relative hydrocracking rates. In actuality, the hydrocracking kinetics should be different among these linkages, but neither the theoretical foundations nor the empirical validation database are sufficient to specify distinctive kinetic parameters for each linkage type. For the same reasons, the reaction order with respect to H2 pressure is the same for each linkage. None of the hydrocracking channels produce noncondensable gases, so hydrocracking is solely a scission


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process. Each channel produces two smaller product fragments but the ends may be labile, hydrogenated, or capped, depending on the reactant linkage. Similarly, the rate of monomer hydrogenation into oils is deemed to be independent of the types of fragment ends attached to the nucleus, although the stoichiometry differs among the various end configurations because all carbon in the monomer is incorporated into oils. The monomer hydrogenation process is based on

t1  MH H2  O,MH O  H2O,MH H2O  NH3 ,MH NH3  H2S ,MH H2 S

(4a)

where t1 is the molar concentration of tar monomers; and MH, O,MH, and H2O,MH are the stoichiometric coefficients for H2, oils, and moisture, respectively.

The associated rate of

monomer hydrogenation is

RMH  kMH t1CHnMH 2

(4b)

where kMH is an Arrhenius rate constant and nMH is an empirical reaction order. Oils are mixtures of benzene, toluene, and xylene (BTX) with phenol, creosol, and xylenol (PCX). To simplify the accounting, the stoichiometric coefficients are specified for a fixed composition of oils from all coals, based on the reported yields of BTX and PCX from the rapid pyrolysis of 17 diverse coals.6 On average, the oils contained 13.7, 17.5, and 15.5 mole % BTX, and 28.5 and 24.8 % phenol and cresol, which gives 6.73 C-atoms/mole oil; 7.47 H; and 0.53 O, for a mean molecular weight of 96.7 g/mol. These assignments determine the stoichiometric coefficients for monomer hydrogenation. Monomers contain two ends of any configuration. Since no end configuration is excluded, each form contributes its carbon to the oil product


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Page 18 of 57

weighted by its instantaneous probability in the tar population, along with the carbon in a nucleus, so that the stoichiometric coefficient for oils is given by C

 O , MH 

N A  2  C N S pTS  C N S * pTS *  C N E pTE  C

(4c)

NO

where CNK is the number of carbon atoms in structural component K, where K denotes nuclei, labile and hydrogenated peripheral groups, capped labile peripheral groups, and oils (in the denominator). Open hydrogenated peripheral groups do not appear in this relation because they have no mass. Since the end configurations are transformed throughout hydroconversion, O,MH also changes. The coefficients for H2O and H2 are determined by the difference between these compounds in the monomer and the products, according to

O   C O

 H O , MH  2  O N S pTS O N S * pTS * O N E pTE  C NO O , MH  2

(4d)

where (O/C)O pertains to oils, based on 6.73 carbons and 0.53 oxygens per mole of oils. The coefficient for H2 is

H

H

2 , MH



H N N  3  2 S al  2  H N S pTS  H N S * pTS *  H N E pTE  C N O O , MH    2 H 2O , MH  C O (4e) 2

where (H/C)O pertains to oils, based on 6.73 carbons and 7.47 hydrogens per mole of oils; and  is the average number of N-atoms per nucleus, which is released as NH3 during oils production. The coefficients for H2O and H2 may be either positive or negative, depending on the compositions and proportions of the different end groups. Finally, the rate of oils production from monomer hydrogenation is given by


18

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Energy & Fuels

RO , MH   O , MH kMH t1CHnMH 2

(4f)

Analogous expressions describe the rates of H2 consumption, and production of H2O, NH3, and H2S with their respective coefficients. Species Conservation Equations Rate equations were developed for the proposed reaction set with the analytical approach used for FLASHCHAIN.5 These equations are the same as those reported previously for tar decomposition under inert gases,4 with additional equations for the new state variables, B* and S*, and their new decomposition products, G*, and new probabilities for the associated structural components. Only these new equations are included here. The conservation equation for hydrogenated bridges is * l* l* l l*   2 J *  p l  p l 1 ptk  ( j  1)( j  2)  pt j  ptk 1 ptk    t k  t k    k B B  2 B k B ( j  1)    tk  tj  pt  pt  B pt    pt  B pt  2 dt k  j 1 pt k   k  k    k  j  k

dBt*

j

* tj

* * 2  ptljk ptlk kR ( pTS  pTE )  j 1  ( j  k  1)  tk t j  k (k  1) 2 p pt jk  1  k t k  

*   ptl  J *    2( j  1)  j  t j  tk    pt j  k 1      

* l*     2 J * pl p   ( 1)( 2) j j t  t  j  t j   k HY Bt CHnHY  k HC CHnHC2 Bt*j  2k HC CHnHC2 ( j  1)  k tk  j 2  pt j   2 k  j 1 ptk     * *  ptl   dt  ptlj j [kSC R  kSN ]( j  1) t j  ( j  1)  j    (5a)  pt j   dt  FC pt j   FC

The first term accounts for scission of hydrogenated bridges in j-mers. The two terms collected as a common factor multiplying 2kB represent the addition of hydrogenated bridges in the fragment class by scission of larger molecules, and hydrogenated bridge transfer to smaller molecules via disintegration of tj. The two terms collected as a common factor multiplying


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Page 20 of 57

kR(pMe+pCe)2/2 account for the addition of hydrogenated bridges into tj via recombination of smaller fragments, and for hydrogenated bridge loss when a tj recombines with any tar fragment. The form of eq. 5a for fragments with J*+1 < j < 2J* nuclei omits the recombination terms. Then hydrocracking both eliminates hydrogenated bridges and brings them into the size class by disintegrating larger fragments. Then labile bridge hydrogenation adds hydrogenated bridges. The soot deposition rate is proportional to the instantaneous soot concentration, but only for fragment sizes that participate in recombination. Finally, hydrogenated bridges are replenished by the bridges in additional primary tar. One tacit assumption underlying eq. 5a is that the likelihood of an intact link being a hydrogenated bridge is independent of its location within the fragment. This is not strictly correct for fragments which are affected by recombination. Once the Btj* have been determined, the hydrogenated bridge probability for the tar lump is determined from eq. 1b. Hydrogenated peripheral groups in tar evolve according to the following rate equation: TD

dS T* 2 p He  dt1    k G S T*  k H Y S T C Hn H2Y  2 k B BT*   e e e e dt  p M  p H  2  ( p M  p H )   dt  O IL J*

t1  2 k HC C HnHC2 BT*  2 k SC RpTS *  t j  2 k SN pTS * 2 pTS * k MH C HnMH 2 j 1

2J*



j  J *1

t j  2  pTS * 

 dt j   j 1   FC J*

FC

  dt

(5b) In succession, the source terms represent spontaneous conversion of hydrogenated peripheral groups to noncondensables; their formation by hydrogenation of labile peripheral groups; their formation by scission of hydrogenated bridges; their destruction during oil production via both spontaneous monomer decomposition and monomer hydrogenation; two terms for their destruction during soot production; and their addition with new primary tar. Recombination does not affect the pool of hydrogenated ends because fragments with these ends cannot recombine.


20

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Energy & Fuels

The rate of spontaneous monomer decomposition is given by TD

 dt1  TD S S* S S*    kO ( pT  pT )(2  ( pT  pT ))t1  dt  OIL

(5c)

At least one and, perhaps, two peripheral groups are converted per mole of oil produced by spontaneous decomposition, because aliphatics are essential to this chemistry. Once ST* is computed, ptjS* is evaluated from eq. 1f, and then used to specify pS*T for the entire fragment population. The total concentration of inert fragment ends that had previously been hydrogenated is determined by J* J * dt 2J*  j 2 pTI dI  dt1  nMH I I I I * 2 2 2 2 p k C t k Rp t k p t p  kG ST             T MH H SC T j SN T j T 1  S S*  2 FC dt 2   pT  pT   dt OIL j 1 j  J *1 j 1  dt  FC TD

(5d) This concentration is affected by the elimination of hydrogenated peripheral groups; oils production by monomer decomposition provided that the monomer precursor contains only one inert end; monomer hydrogenation; soot production from any tar fragment; and addition of primary tar that contains inert ends. Once I is computed, ptjI is evaluated from eq. 1g, and then used to specify pIe for the entire fragment population. Noncondensable products generated from hydrogenated peripheral groups are described by

dG *  B*  kG ST*  dt 2


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Page 22 of 57

 S*   MWC pTE MWB*  MWB*  S S* 1 S* 2 1 p p p 2 (1 )(  )  pTS  1OG*      T  )   ( pT ) ( OG*  T T OG* E I TD pT  pT 2MWG* 2MWG*  2MWG*   dt1      S S*     pTS  pTS*  2  ( pTS  pTS*) pT  pT  2  ( pTS  pTS* )   dt OIL       * l*  J*   2J*      ptl j p t  B* k SC R    ( j  1)  pTS * t j    B* k SN    ( j  1) j  pTS * t j  pt j pt j  j 1   j  J *1              (5e)

where

vC 

MWB  MWC MWG

MWB*

and  B* 



MWG*

MWG MWC  2vHY MWH vC  MWG* MWG*

(5f)

and 1OG* and 2OG* are the amounts of gas formed if the monomer contains one or two hydrogenated peripheral group, which are evaluated from

 OG 

1

*

MWN 

MWB*

  O MWO 2 MWG*

and

 OG 

2

*

MWN  MWB*   O MWO MWG*

(5g)

where O is the stoichiometry for oils during monomer decomposition. Results Parameter Assignments All the parameters in the 11-reaction tar decomposition mechanism were assigned to fit Chen et al.’s datasets7 for 800 to 1100 C with extensive soot production, and fixed for all coals. However, the soot nucleation rate was voided for all cases in this paper except for one test series at 0.3 MPa H2 in Figure 2, below. When soot nucleation was included, the predicted soot yields were never more than a few weight percent for H2 pressures of 1 MPa and higher. In principle, the four-step tar hydroconversion mechanism introduces fourteen adjustable


22

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Energy & Fuels

parameters, three each in the distributed-energy rate constants for hydrogenation of labile bridges and peripheral groups; two each for hydrocracking and monomer hydrogenation; plus reaction orders for all four steps. In practice, there are only eight new parameters, because the same distributed-energy rate is applied to the hydrogenation of bridges and peripheral groups since their compositions are the same, and because the same order for H2 pressure of unity is applied to all four reaction processes. For all coals in the model validation database, the bridge hydrogenation rate was specified with AHY = 103 (s-mol/cm3)-1; EHY= 105 kJ/mol; and HY= 8.4 kJ/mol. These specifications are imprecise because bridge hydrogenation was relatively unimportant under all test condition. Also for all coals, the hydrocracking rate was specified with AHC = 3.2x103 (s-mol/cm3)-1 and EHC= 83.7 kJ/mol; and the monomer hydrogenation rate was specified with AHC = 6x108 (s-mol/cm3)-1 and EHC= 125.5 kJ/mol. The only exception is that to eliminate a persistent under-prediction, the coals in Xu et. al.’s dataset8 were interpreted with AHC = 104, which is three times greater than the value used for all other datasets. For char hydrogasification, the assigned activation energy of 81.5 kJ/mol and the order of onehalf are more secure, since these are the same values used to previously interpret hydrogasification conversions for 21 coals.1 Whereas these parameters were fixed for all coals, the pseudo-frequency factor for hydrogasification was tuned-in to match the reported total weight loss for each sample, and presented in Figure 7, below. The same enthalpy of hydrogasification was applied to all coal types, based on the hydrogasification of pure carbon into methane. Validation Database and Simulation Protocol The simulations predict the distribution of primary hydropyrolysis products with


23

Energy & Fuels

25

20

Primary Tar, daf wt.%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 57

15

10

5

0 0

10

20

30

40

50

Measured Tar + Oils, daf wt.%

Figure 1. Predicted primary tar yields from hydropyrolysis vs. sums of reported yields of tar plus oils. Open symbols below the parity line are from () Fallon et al.12 and () Chen et al.13 FLASHCHAIN, then subject the primary tars to simultaneous decomposition and hydroconversion, and then simulate char hydrogasification in a third calculation sweep. The tar hydroconversion simulations use the predicted yields and compositions of primary tar as essential input information, but none of the literature datasets on the products of hydrogasification reported primary tar yields. Consequently, the most basic qualification standard for validation datasets is to demonstrate that the reported yields of tar and oils throughout a hydrogasification test are smaller than the predicted primary tar yield for these conditions. As seen in Fig. 1, most but not all the reported product distribution satisfy this standard. The bulk of the data fall along a line parallel to the parity line, such that the primary tar yields are roughly 3 daf wt. % greater than the sums of secondary tar plus oils, presumably due to the elimination of tar components as noncondensable gases. All the data reported by


24

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Energy & Fuels

Ikura and Last,9 Xu et al.,8 and Tang et al.10 satisfy the standard, and all but the data for the two coals of highest rank reported by Finn et al.11 satisfy it as well. These two discrepancies are for tar yields that are comparable to the measurement uncertainties. However, the yields reported by Fallon and Steinberg12 and nearly all those reported by Chen et al.13 do not meet the standard and will, therefore, not be qualified for model validations. Excluding catalysts and other external agents, the only means to generate tar yields greater than 20 daf wt. % at elevated pressures is to very slowly heat coal under elevated H2 pressures. But Fallon and Steinberg reported heating rates faster than 104 C/s, and Chen et al. imposed 650 C/s. So neither test series could have given liquids yields as great as shown in Fig. 1. The validation database comprises four datasets compiled in two free-fall reactors (FFR),8,10 an entrained flow reactor (EFR);9 and a hot-rod reactor in series with an unpacked tubular flow reactor for tar hydroconversion.11 Collectively, these datasets represent heating rates from 5 to almost 104 C/s; temperatures from 475 to 900 C; coal contact times from 1 to 900 s; gas contact times from 1 to 42 s; H2 pressures from 0.3 to 15 MPa; and 28 coal samples representing the entire rank spectrum. An ideal validation dataset contains product distributions with sufficient resolution to close balances on mass and C/O/N/S for both primary hydropyrolysis and hydrogasification, supported by accurate determinations of the contact times for both coal and gases. Unfortunately, such datasets have not yet been reported, and all four validation datasets are ambiguous in some way or another. The most complete product distributions were reported by Ikura et. al. and included char, tar, oils resolved as molecular species, C1 and C2 GHCs, carbon oxides, and moisture.9 The distributions close the mass balances to within 5 daf wt. %, which exceeds the reproducibility in


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Page 26 of 57

the liquids yields for similar operating conditions. Xu et al.’s dataset resolves all major Cbearing products and also includes selected weight loss data for both primary devolatilization and hydrogasification.8 But the main ambiguity is that the tabulated product distributions are markedly different from the cumulative C-distributions shown in figures for the same nominal operating conditions.8 In particular, the oils yields on figures are typically three times greater than the tabulated values. The cumulative C-distributions were used here because these oils yields are in line with other literature values for similar operating conditions. Moisture yields were estimated to account for a percentage of coal-O devolatilization that varies from 70 to 85 % for coals of progressively higher rank, in accord with an established tendency for primary devolatilization.14 Tang et al. reported total weight loss and C-conversions to tar, oils, C1 and C2 GHCs, and carbon oxides plus moisture levels10 and coal-N conversions.15 The exceedingly long 42 s contact time for gases raises concerns about how buoyancy circulation could have been controlled with such very low gas flowrates at such high temperatures and pressures. Finn et al. reported mass conversions to tar, oils, and C1 and C2 GHCs,11 so neither mass nor elemental balances could be formulated. Due to these ambiguities, it is hard to ascertain the measurement uncertainties on the reported oils, tar, and total yields. Tang et al.’s replicate measurements for oils and tar are within ±1 daf wt. % of the average value, and within a few daf wt. % for total yields. But none of the other datasets contain replicate cases. In the quantitative interpretations in this paper, the nominal measurement uncertainties are taken to be  1 daf wt. % for oils;  2 % for tar; and  4 % for weight loss.


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Energy & Fuels

With FFRs and EFRs, thermal histories are almost never measured and calculated histories are subject to uncertainties on convective mixing patterns near fuel injectors. Fortunately, all the flow reactors in the validation database imposed coal contact times long enough to achieve ultimate hydropyrolysis yields for all test conditions. Even though estimated heating rates were subject to considerable uncertainties, the yield enhancements due to faster heating become inconsequential for the very high pressures in all these tests.14 The simulations imposed the reported operating conditions in each test. To accommodate the disparate contact times for coal and gases, each tar hydroconversion simulation was run sequentially after the hydropyrolysis simulation, so that the ultimate mixture of primary hydropyrolysis products was independently converted throughout the gas contact time. As noted in the previous section, all rate parameters in the tar decomposition and tar hydroconversion mechanisms were the same for all coals, except that the frequency factor for hydrocracking was increased by a factor of three to interpret Xu et al.’s dataset.8 The same values for AHP for hydrogenation in the coal phase during hydropyrolysis and AHG for char hydrogasification were used for every simulation with a particular sample. Whereas the char hydrogasification simulations determined the amounts of associated CH4, noncondensable gas yields are not considered in this validation study due to the omission of reforming chemistry among carbon oxides, moisture, and GHCs. Whenever ultimate primary devolatilization yields were reported, parameters in FLASHCHAIN were adjusted to match the predicted weight loss to a measured value, to sharpen the focus on the products of tar hydroconversion. Each simulation required less than a second on an ordinary personal computer. Hydropyrolysis Tar Characteristics


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Page 28 of 57

Table 2. Predicted characteristics of hydropyrolysis tars. Coal

Coal-C

Rapid Heating10

XL ZN SB HX SF SY FS DS1 DS2 HF DT XS YQ JC

69.6 70.3 73.7 75.0 75.1 75.1 80.2 81.0 81.1 81.6 84.1 85.7 86.3 89.7

BR DM LN LV AN DW GW CB

70.0 79.9 82.6 84.4 84.5 86.8 91.3 93.1

Slow Heating11

YTAR

15.7 15.2 16.8 18.1 16.5 16.0 18.5 19.6 15.6 17.7 17.3 16.7 11.6 8.0 13.6 16.7 15.8 14.5 13.9 13.3 3.5 1.9

Mn

Ultimate Analysis C H O

306.5 372.7 346.2 374.8 254.1 305.4 288.1 228.7 276.7 250.1 257.0 224.2 201.9 198.1 846.8 445.0 361.7 322.1 318.1 283.1 174.4 133.0

73.5 73.9 76.7 77.4 78.6 78.4 82.4 83.4 82.7 84.3 85.1 86.5 87.3 89.4 67.1 77.5 80.1 83.2 82.1 85.3 87.8 89.0

5.9 7.8 7.6 8.4 5.6 6.9 7.1 5.0 6.9 6.6 6.5 6.2 4.6 4.4 10.5 9.8 9.2 9.3 8.8 8.1 5.9 3.4

18.6 15.5 13.8 12.2 13.8 12.6 8.2 9.7 8.5 5.8 6.3 4.7 4.8 3.7 21.4 10.4 8.2 4.9 6.6 4.1 1.9 0.9

N

S

1.6 1.9 1.7 1.7 1.8 1.7 1.5 1.8 1.8 1.8 1.8 1.9 1.9 2.0 0.8 1.4 2.0 1.6 2.0 1.8 1.6 1.4

0.3 0.8 0.2 0.4 0.2 0.4 0.8 0.2 0.2 1.4 0.3 0.7 1.4 0.5 0.2 0.9 0.6 1.1 0.5 0.7 2.7 5.3

(H/C)B

(O/C)B

MH

1.97 2.12 2.08 2.14 1.91 2.01 2.00 1.85 1.98 1.96 1.94 1.91 1.82 1.80 2.20 2.26 2.18 2.16 2.13 2.05 1.89 1.77

0.47 0.29 0.27 0.21 0.37 0.27 0.17 0.30 0.18 0.13 0.14 0.11 0.16 0.13 0.30 0.16 0.13 0.08 0.11 0.08 0.05 0.04

11.9 15.5 14.5 16.2 9.9 12.5 12.0 8.3 11.5 10.3 10.4 9.1 6.8 6.6 37.1 18.6 15.7 15.1 14.1 11.7 8.0 4.3

Table 2 compiles the predicted characteristics of primary hydropyrolysis tars for the two test series that subjected suites of diverse coals to the same hydrogasification conditions. Tang et. al.’s FFR heated dilute suspensions at 7000 C/s to 750 s with 42 s gas contact under 4 MPa H2.10 Finn et al. heated a packed coal bed at 5 C/s, and converted the volatiles at 850 C with 4 s contact time under 15 MPa H2. Only the tests at 5 C/s could have hydrogenated tar precursors in the condensed coal phase, and thereby affected tar constitution.1 For both datasets, predicted primary tar yields pass through a weak maximum for hv bituminous coals, then fall off sharply for low volatility coals, while tars become lighter for coals of progressively higher rank.


28

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Energy & Fuels

The tars contain more carbon and much more hydrogen than their parent coals, but less oxygen and comparable amounts of nitrogen and organic-S. These trends are also evident in the atomic H/C and O/C ratios for labile bridges. Since the tar yields for comparable coals are similar in both datasets, hydrogenation during hydropyrolysis partially compensates for the impact of the higher pressure and slower heating rate in Finn et al.’s tests. Moreover, extensive hydrogenation is clearly apparent in the substantially greater (H/C)B -values and correspondingly lower (O/C)B –values for the tars prepared with slow heating. For both datasets, the H2 requirement for monomer hydrogenation (MH) diminishes for coals of progressively higher rank, which reflects the elimination of coal-O across the rank spectrum. Whereas essentially the same kinetic parameters for tar hydroconversion were implemented for all coals in the validation database, it is important to recognize that the primary tar characteristics from the hydropyrolysis mechanism display important tendencies across the rank spectrum and, especially, exhibit substantial sample-to-sample variability among coals of the same nominal rank. Indeed, the sample-to-sample variability in the primary tar characteristics is responsible for the sample-to-sample variability in the associated oils yields from tar hydroconversion, as seen below in Figs. 4 and 5. Validation Cases In Figures 2 – 6, the measured values appear as filled data points and the calculated values appear as curves, line segments, or open points connected by line segments. The first case in Figure 2 covers variations in H2 pressure and temperature with a subbituminous coal for rapid heating and 3 s gas contact time. The measured oils yields surge from 0.3 to 1 MPa, then remain essentially constant for all higher H2 pressures, while the measured secondary tar yields decay


29

Energy & Fuels

35

25

30

Primary Tar

25

Primary Tar 20

15

Oils

HCL Yields, daf wt.%

20


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 30 of 57

15

Oils 10

10

Secondary Tar 5

5

Secondary Tar 0 0

1

2

3

4

5

0 600

650

H2 Pressure, MPa

700

750

800

850

900

Temperature, C

Figure 2. (Left) Evaluation of yields of () oils and () secondary tar from a subbituminous coal for heating at 2000 C/s to 800 C under various H2 pressures; and (Right) Evaluation for different temperatures under 3 MPa H2. Predicted primary tar yields appear as the dashed curves. Both test series imposed 1.8 s coal contact time and 3 s gas contact time in a FFR.8 very gradually across the entire pressure range. The predicted oils yields are within measurement uncertainties throughout, whereas secondary tar yields diminish slightly faster than the measured values, although the discrepancy is significant only at 0.3 MPa. This case is the only one in this paper that included soot nucleation and growth in the simulations, so that the 12.7 daf wt. % tar yield in Figure 2 is actually a sum of 5.2 % tar plus 7.5 % soot. The decay in the predicted tar yields corresponds with the decay in the predicted primary tar yields from 32 % at 0.3 MPa to 21 % at 5MPa. Despite this reduction in the precursors to oils, the tar hydroconversion mechanism accurately depicts the saturation in the oils yields above 1 MPa. Higher H2 pressures accelerate monomer hydrogenation to compensate for the diminishing primary tar yields.


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Predicted oils yields for 625 to 850 C under 3 MPa H2 almost double, and remain within measurement uncertainties across the entire range. But the predicted tar yields are grossly at odds with the measured values except for temperatures hotter than 800 C. This discrepancy exposes a problem with the measured values rather than the predictions. Primary tar yields always increase for progressively hotter temperatures before they saturate to an asymptotic, ultimate value for a particular heating rate and pressure.14 Such behavior is clearly apparent in Figure 2 in the predicted tar yields, which saturate at roughly 700 C. Since primary tar is the precursor to oils and secondary tar, the measured sums of these yields should mimic the behavior of primary tar, as they do in the pressure sweep in Figure 2. But the measured sums in the temperature sweep actually diminish sharply for progressively hotter temperatures, which never happens in actuality. Moreover, the 26 daf wt. % sum for 625 C is much greater than any reported primary tar yield for 3 MPa. The expected behavior is apparent in the evaluation in Figure 3, where the EFR tests covered a temperature sweep from 665 to 790 C, but with gas contact times from 14 to 23 s. The measured tar yields diminish from 4 to 1 % while oils yields increase from 6.5 to roughly 10 %, so that the sums gradually increase across the temperature range, in tandem with the predicted primary tar yields in Figure 3. The predicted tar yields are within measurement uncertainties throughout, and the oils yields are also accurate, albeit within the considerable scatter in the measured yields. The notable exception is the very large over-prediction for the oils yield at 790 C, at 11 % vs. 1.5 %. This discrepancy reflects the omission of oil hydrogenation into CH4 in the hydroconversion mechanism, which is relatively slow and therefore comes into play only for very long contact times and very high H2 pressures,11,16,17 like the 20 s contact time and 12.9 MPa H2 in this particular test. This effect will be depicted by combining the hydroconversion


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15.0 70

12.5

Primary Tar

10.0

Total & Volatiles Yield, daf wt.%


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Oils

7.5

5.0

2.5

Secondary Tar

Wt. Loss 60

50

Extent of Hydrogasification

40

Predicted Volatiles Yield

30

0.0 650

700

750

800

650

675

Temperature, C

700

725

750

775

800

Temperature, C

Figure 3. (Left) Evaluation of yields of () oils and () secondary tar from a high volatile (hv) bituminous coal blend for heating at 8000 C/s to different temperatures under 12.9 MPa H2 with coal contact times from 3.7 to 6.5 s and gas contact times from 14 to 23 s.9 Predicted primary tar yields appear as the dashed curve. (Right) () Measured and ( connected by line segments) predicted total weight loss and ( connected by dashed line segments) predicted volatiles yields for the same test conditions. mechanism with an elementary reforming mechanism. The contribution from char hydrogasification is also resolved in Figure 3 as the difference between the measured or predicted weight loss and the predicted hydropyrolysis yield for each test condition. In these simulations, the same hydrogasification rate was used for each set of test conditions. Predicted weight loss is within measurement uncertainties for all tests, and exhibits the step-change at 745 C when the coal contact time was increased from 3.7 to 5.5 s. For this particular coal and these operating conditions, hydrogasification was responsible for about 45 % of the total coal conversion, which is so high because of the extreme H2 pressure in this test


32

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20

15


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Energy & Fuels

Primary Tar 10

Oils

5

Secondary Tar 0 70

75

80

85

90

95

Carbon Content, daf wt.%

Figure 4. Evaluation of yields of () oils and () secondary tar from diverse coals for heating at 5 C/s to 600 C for 900 s under 15 MPa H2 with hydroconversion is a second reactor stage at 850 C with 4 s gas contact time.11 Predicted products appear as corresponding open symbols connected by solid line segments. Predicted primary tar yields appear as () connected by dashed segments. series. Hydrogasification generated 35- 40 daf wt. % CH4, and minor amounts of H2O, NH3, and H2S. The previous two evaluations covered tests with rapid heating rates, for which tar yield enhancements during hydropyrolysis would be minimal.1 The evaluation in Figure 4 covers heating at 5 C/s to 600 C in a first reactor stage, with tar hydroconversion in a second unpacked flow reactor at 850 C with 4 s transit time.11 As seen in Figure 4, the predicted primary tar yields are as large as those for heating rates approaching 104 C/s in Figure 3, which definitely reflects tar yield enhancement due to hydrogenation in the condensed coal phase under


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these test conditions. Consequently, the oils yields are also as large as those for much faster heating rates. The predicted oils yields depict the observed coal quality impact, whereby oils yields pass through a weak maximum for hv bituminous coals before falling off sharply for low volatility coals. They are within measurement uncertainties through 85 daf wt. % C, except that they do not depict the distinctive low oils yield for one of the coals with 84 % C because that primary tar yield is also not relatively much smaller. The accuracy deteriorates for the low volatility coals; this must be due to under-predicted primary tar yields for the two coals of highest rank rather than problems in the hydroconversion mechanism, because the predicted primary tar yields are much lower than the measured oils yields. The measured secondary tar yields are approximately 2 % until they diminish for both anthracites, whereas the predicted tar yields are insignificant for all coals. A separate test series in this study varied the temperature of the first reactor stage from 575 to 700C, for which the oils yields varied from 9 to 12 daf wt. % with no consistent tendency with reactor temperature. The predicted oils yields varied from 9.6 to 10 % over this temperature range, in agreement with the observed insensitivity to the carbonization temperature. The sample-to-sample variability among oils yields from coals of the same nominal rank is apparent in the evaluation in Figure 5, based on Tang et al.’s dataset for rapid heating of 14 coals to 750 C under 4 MPa H2.10,15 Whereas the coal contact time of 2 s is comparable to the contact times in Xu et al.’s FFR and Ikura and Last’s EFR, the 42 s gas contact time is the longest, by far, in the validation database. This distinctive condition factors into the explanation for an apparent discrepancy in the predicted oils yields. The hydroconversion mechanism regards oils as mixtures of BTX and PCX in fixed proportions for all coals. These predicted values in Figure


34

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15.0

25

12.5

20

Oil Mixture 10.0

Tar Yields, daf wt.%

Oils Yield, daf wt.%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

7.5

5.0

Adjustment to C6H6

15

Primary Tar

10

5

2.5

0.0 70

75

80

85

90

Secondary Tar

0 70


75

80

85

90


Figure 5. Evaluation of yields of () oils and () secondary tar from diverse coals for heating at 7000 C/s to 750 C for 2 s under 4 MPa H2 in a FFR with 42 s gas contact time.10,15 Predicted products appear as corresponding open symbols connected by solid line segments. The left panel also shows the predicted oils mixtures of substituted BTX + PCX as () connected by dotted line segments. Predicted primary tar yields appear in the right panel as () connected by dashed segments. 5 are consistently greater than the measured oils yields by 3 to 4 daf wt. % across the rank spectrum. However, the literature database on tar hydroconversion firmly establishes that oils mixtures are not stable under hydrogasification conditions; rather, they eliminate their substituents as CH4 and H2O, which eventually renders oils mixtures into pure benzene.9,11,16 Given sufficient time at a sufficiently high H2 pressure, benzene is reformed into CH4, so that reported oils yields often pass through a maximum for progressively hotter temperatures.11,12,17 The discrepancies for the oils mixtures in Figure 5 were almost completely eliminated by arithmetically converting the predicted BTX + PCX mixtures into benzene, by applying a ratio of the molecular weights of benzene to oils or 78/96.7 to the predicted oils mixtures. The predicted


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benzene yields are within the measurement uncertainties for all coals through 85 daf wt. % C, except for two coals with about 81 % C. Although the predicted benzene yields diminish for the three low volatility coals, the discrepancies are larger; however, the discrepancies are overpredictions for these tests, in contrast to the under-predictions for the two anthracites tested by Finn et al. (cf. Figure 4). Whereas Tang et al. did not resolve oils as molecular species, they reported independent yields for the BTX and PCX lumps.10 Their oils contained, on average, less than 15 wt. % PCX, which is four times smaller than the 60 % PCX in the predicted oils mixture. In addition, Zhu et al. imposed the same conditions on two lignites as Tang et al.,16 and reported that BTX and PCX were entirely reduced to benzene and xylenol, respectively, in tests at 750 C with 42 s gas contact time. So the adjusted oils yields in Figure 5 are corroborated by direct measurements for these conditions. This explanation raises the question as to why the oils were not completely eliminated for the very long gas contact times in these tests, when complete elimination was invoked to rationalize the very low oils yield reported for 790 C in only 20 s in Figure 3. The hotter temperature is one factor to counteract the shorter gas contact time behind Figure 3, but the predominant consideration is the much greater H2 pressure, at 12.9 vs. 4 MPa. A quantitative resolution to this issue remains to be demonstrated with an elementary reforming mechanism. Returning to Figure 5, the predicted secondary tar yields vary from 2 to 4 daf wt. % vs. measured tar yields from 5 to 8 %. Whereas the quantitative discrepancies are comparable to those in Figure 4, note that the hydroconversion mechanism correctly predicts residual secondary tar for 42 s under 4 MPa H2, but none for 4 s under 15 MPa. Another important feature in Figure 5 is that the predicted primary tar yields clearly illustrate that the sample-to-sample variability in the


36

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60


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Energy & Fuels

50

Measured Wt. Loss


40

30

Predicted Volatiles Yield 20

10

0 70

75

80

85

90


Figure 6. () Measured total weight loss and ( connected by dashed line segments) predicted volatiles yields for the test conditions in Figure 5.10 tar yields is responsible for the variability in the yields of oils and secondary tar, rather than any coal quality impacts on any aspects of the tar hydroconversion mechanism. In other words, it is impossible to depict the sample-to-sample variability of hydroconversion products without first predicting the distinctive tar yields for particular coal samples from hydropyrolysis. Predicted extents of char hydrogasification for these tests appear in Figure 6 as the difference between the predicted ultimate hydropyrolysis yields and the measured total weight loss. The predicted weight loss is not shown because this dataset represents only one set of operating conditions for each coal, and AHG was adjusted to match the predicted weight loss to the measurement for each coal. The hydrogasification contributions are approximately 20 % of the reported coal conversion for all coals except for all but one of the bituminous coals, which have much greater contributions. The relatively low contributions for nonbituminous coals reflect the coal contact time of only 2 s and the moderate H2 pressure, whereas the enhanced conversions of the bituminous coals reflect accelerated reactivities, as shown below in Figure 7.


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100000 80000 60000

-0.5 -1

40000

AHG atm s

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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20000

8000 6000 4000 2000 0 65

70

75

80

85

90

95


Figure 7. Assigned pseudo-frequency factors for char hydrogasification to interpret datasets on () 14 diverse coals from Tang et al.10; () 3 coals from Xu et al.8; () 1 coal blend from Ikura and Last9; and () for the 21 coals in the validations with coal conversions reported previously.1 Hydrogasification generated from 11 to 18 daf wt. % CH4, except for half as much from the coals of lowest rank and for 27 % from the coal with 86 % C. The assigned values for AHG to interpret this validation database are compared in Figure 7 with assignments based on total coal conversions for 21 coals reported previously.1 Assignments smaller than about 1000 atm-0.5-s-1 reflect small extents of char hydrogasification and may not be well-resolved from the measurement uncertainties. For the three coals tested by Xu et al.8 and the coal blend tested by Ikura et al.,9 the assignments are indistinguishable from the previous assignments, as are the assignments for ranks of subbituminous and lower and for the low volatility coal tested by Tang et al.10,15 But the assignments for the hv bituminous coals tested by Tang et al. are five to twenty times greater than the rest. In isolation, the assignments for Tang et al.’s dataset appear to indicate that hydrogasification reactivities increase for progressively higher coal rank until they diminish for low volatility coals. But in the context of all the


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assignments in Figure 7, only Tang et al.’s bituminous coals have markedly faster reactivities. It is worth reiterating that hydrogasification reactivities vary by only a factor of four for the bulk of coals tested across the rank spectrum. Discussion The postulated mechanism for tar hydroconversion accurately interprets how variations in H2 pressure and temperature affect oils yields. Accelerating rates of monomer hydrogenation and hydrocracking for progressively higher H2 pressures compensate for diminishing primary tar yields to maintain constant oils yields for pressures higher than 1 MPa. Increasing oils yields for progressively hotter temperatures simply reflect the substantial activation energies in the kinetics for hydrocracking and monomer hydrogenation. But the mechanism omits the hydroconversion of oils into CH4 that determines a maximum in oils yields vs. both temperature and pressure.11,12,17 Only one test in the validation database was affected by this omission, but it will come into play at the highest H2 pressures and longest contact times of interest. It remains to be demonstrated that incorporating an elementary reforming mechanism for oils accurately depicts their destruction. According to the postulated hydroconversion mechanism, oils form in two stages controlled by monomer hydrogenation and hydrocracking, respectively. The hydrogenation of labile bridges and peripheral groups is relatively unimportant. In the first stage, the tar monomers released as primary tars are rapidly hydrogenated into oils at the monomer hydrogenation rate. Since elevated pressures always shift primary tar MWDs toward lighter species, monomers constitute substantial fractions of primary tar, approaching half under some operating conditions. Consequently, as much as half the ultimate oils yield is produced soon after the onset of tar


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hydroconversion.

Page 40 of 57

In the second stage, additional tar monomers are gradually released by

hydrocracking of larger tar molecules and then hydrogenated into oils, while control of the oils production rate shifts from monomer hydrogenation to hydrocracking. Tests with finer time resolution are needed to establish that monomer hydrogenation occurs in two distinct stages, as proposed here, and that the apportioning of the ultimate oils yield is accurate. The mechanism has been validated across a broad range of coal and gas contact times, and correctly predicts that secondary tar persists for all but the highest H2 pressures. But two ambiguities persist in the predicted dynamics: First, predicted oils yields for the tests of Tang et al. became accurate only after an adjustment for the elimination of substituents from the original mixtures of BTX plus PCX. Whereas this elimination is well characterized in the testing literature,9,11,16 this aspect also remains to be demonstrated for the exceedingly long gas contact times in these tests with an elementary reforming mechanism. Second, the predicted conversion of secondary tar may be too fast, since measured ultimate tar yields usually exceeded the predicted values. This could signal a need for more robust kinetics although, alternatively, the small amounts of secondary tar that persist at even the longest gas contact times could also reflect linkage-specific hydrocracking rates. Currently, the same hydrocracking kinetics are used for labile and hydrogenated bridges and char links for lack of supporting information to resolve any differences. But if char links were more resistant to hydrocracking than bridges, then tar fragments bound by only char links would persist longer than the rest. The oils yields from a few dozen diverse coals have been accurately interpreted without any heuristic adjustments to any of the kinetic parameters, except that the rate of monomer hydrogenation was increased by a factor of three to eliminate a persistent discrepancy with Xu et al.’s dataset. This probably means that the rate constants may not have reached their final


40

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5

4

3

YOils/ATar

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

2

1

0 70

75

80

85

90

95

Carbon Content, daf wt. %

Figure 8. Ratio of predicted oils yields to the amounts of aromatic nuclei in primary tar vs. coalC contents for () 14 coals from Tang et al.10 where YOILS are the predicted BTX/PCX mixtures rather than the benzene-only values; () 3 coals from Xu et al.8; () 1 coal blend from Ikura and Last9 and () 8 coals from Finn et al.11 values, rather than that different kinetics will be required for different coals. Consequently, primary tar compositions and, especially, their structural components, determine oils yields from different coals.

The main trend is that oils yields pass through a weak maximum for hv

bituminous coals, then decay sharply for low volatility coals. Predicted oils yields for the low volatility coals in both validation datasets with the best coverage of coal quality were inaccurate. But the discrepancies were in opposite directions so it is hard to rationalize these flaws. The most interesting aspect of the coal quality impacts is the exceedingly large percentage of the material in aromatic nuclei incorporated into oils under the most favorable operating conditions with any coal type. Figure 8 presents the ratio of the predicted oils yield to the mass of all aromatic nuclei in primary tar, ATAR, vs. the C-content of the parent coal. Since tar nuclei can only ultimately appear in secondary tar and oils in the proposed mechanism, values less than


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Page 42 of 57

unity indicate that some primary nuclei remain in secondary tar. Conversely, values greater than unity indicate that aliphatic tar components have also been incorporated into oils. The ratio values in Figure 8 segregate into two groups as a function of H2 pressure. At 3 – 4 MPa, aliphatics make up one-third of the oils with low rank coals and slightly less with bituminous and low volatility coals, whereas at 12.9 – 15 MPa, they constitute half or more of the oils mass. Consequently, the notions that aromatic nuclei in primary tar, which have two to four rings with bituminous coals and fewer or more for coals of lower and higher rank, respectively, are either winnowed down or completely converted into single-ring compounds are incompatible with reported ultimate oils yields. Indeed, a trial rendition of the monomer hydrogenation process in which only the mass in nuclei became oils could not predict sufficient oils yields. However, the ultimate rendition demonstrates that monomer hydrogenation must also incorporate aliphatic peripheral groups into oils as well. The broad domain of operating conditions in the validation database gave rise to broad variations in the assigned extents of char hydrogasification. But these variations abided by the single, onehalf-order hydrogasification reaction within CBK/G that had previously been validated with a separate database; indeed, the same activation energy and standard deviation about the mean energy performed well with the newer validation database. However, the hydrogasification reactivity assignments for the hv bituminous coals tested by Tang et al. are five to twenty times greater than the rest, and only the bituminous coals have markedly faster reactivities. Pending laboratory characterization of the factors responsible for the enhanced reactivities, most of the assigned hydrogasification reactivities vary by only a factor of four across the rank spectrum, and hydrogasification appears to be much less sensitive to coal quality than gasification in steam or CO2.


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Conclusions 1)

Hydropyrolysis tars are hydroconverted through three main processes: (1) Hydrogenation

of labile bridges and peripheral groups in tar fragments accompanied by suppression of recombinations among the ends of tar fragments that would otherwise shift the tar MWD toward heavier fragments, and thereby suppress the precursors to oils; (2) Hydrocracking of the labile and hydrogenated bridges and char links in tar to produce smaller tar fragments without any transformations of aromatic nuclei; and (3) Hydrogenation of isolated tar monomers into oils and moisture. All these processes utilize ambient H2 at rates that accelerate for progressively higher H2 pressures, although bridge hydrogenation is relatively unimportant. 2) Oils yields are uniform with H2 pressures higher than 1 MPa because rates of monomer hydrogenation and hydrocracking accelerate for progressively higher H2 pressures to compensate for diminishing primary tar yields. Predicted oils grew for progressively hotter temperatures, but the tar hydroconversion mechanism must be combined with an elementary reforming mechanism to depict the maximum in oils yields as a function of temperature. 3) Except for one small adjustment to one rate constant for one of the validation datasets, the same kinetic parameters accurately predicted oils yields for coal ranks through hv bituminous. Primary tar composition and, especially, their structural components determine the maximum oils yields from different coals.

The sample-to-sample variability in primary tar yields is

apparent in their associated oils yields. 4) Aliphatic tar components must be incorporated into oils along with their aromatic nuclei during monomer hydrogenation, and constitute half or more of the oils yield at the highest H2 pressures.


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5) Most of the assigned char hydrogasification reactivities vary by only a factor of four across the rank spectrum. However, the hydrogasification reactivity assignments for the hv bituminous coals tested by Tang et al. are five to twenty times greater than the all other coals in the validation database, including numerous other hv bituminous samples. Nomenclature A

Scaled aromatic nuclei in tar as a molar concentration in the gas phase

A0

Molar concentration of aromatic nuclei in coal, moles/cm3-coal

AGAS Molar concentration of aromatic nuclei per unit gas volume, moles/cm3 Ai

Pseudo-frequency factor in a reaction involving species i, s-1

B

Scaled labile bridges in tar as a molar concentration in the gas phase

B*

Scaled hydrogenated bridges in tar as a molar concentration in the gas phase

bi

Stoichiometric coefficient for product i for oil production via monomer decomposition weighted for the proportions of tar monomers with either one or two labile peripheral groups.

bi

Stoichiometric coefficient for product i for oil production via monomer hydrogenation weighted for the proportions of tar monomers with either one or two hydrogenated peripheral groups.

C

Scaled char links in tar as a molar concentration in the gas phase

CH2

Molar concentration of ambient H2

cij

Stoichiometric coefficient for gaseous product i during nucleation and addition of tj to soot

ci,O

Stoichiometric coefficient for product i during oils addition to soot

cRj,i

Stoichiometric coefficient for product i during soot nucleation

E

Fragment ends that lost labile peripheral groups as a molar concentration in the gas phase

(E/C)B Atomic ratio of element E = H, O to carbon in labile bridges in tar Ei

Activation energy in a reaction involving species i, kJ/mol

G

Scaled molar concentration of noncondensable gases from decomposition of labile bridges and peripheral groups


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Energy & Fuels

G*

Scaled molar concentration of noncondensable gases from decomposition of hydrogenated peripheral groups

I

Fragment ends that lost hydrated peripheral groups as a molar concentration in the gas phase

j

Index for the degree of polymerization in tar molecules

J*

Maximum extent of depolymerization for primary tar molecules

ki

Rate constant for a reaction involving species i, s-1

kk

Rate constant for reaction process k = HY, HC, or MH, atm-1-s-1

kOTD

Rate constant for oils production from monomer decomposition, s-1

LCOAL Coal loading, g/cm3 Mn

Number-average molecular weight of tar, g/mol

MWi Molecular weight of species or component i, g/mol nk

Reaction order for H2 in reaction k

e

Ni

Number of atoms of element e in structural component i

O

Scaled molar concentration of oils from both monomer hydrogenation and monomer decomposition

pT

Probability for any type of connection among nuclei in tar

ptj

Probability for any type of connection among nuclei in tj molecules

pTl

Probability for an intact labile bridge among nuclei in tar

ptjl

Probability for an intact labile bridge among nuclei in tj molecules

pTl*

Probability for an intact hydrogenated bridge among nuclei in tar

ptjl

Probability for an intact hydrogenated bridge among nuclei in tj molecules

pTS

Probability for an intact labile peripheral group on the end of tar fragments

pTS*

Probability for an intact hydrogenated peripheral group on the end of tar fragments

pTE

Probability for a fragment end that had previously held an intact labile peripheral group

pTI

Probability for a fragment end that had previously held an intact hydrogenated peripheral group

R

Scaled molar concentration of soot or, in Arrhenius rate constants, the universal gas constant


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S

Scaled labile peripheral groups in tar as a molar concentration in the gas phase

S*

Scaled hydrogenated peripheral groups in tar as a molar concentration in the gas phase

Sal

Scaled aliphatic sulphides in tar as a molar concentration in the gas phase

Sth

Scaled thiophene sulfur in tar as a molar concentration in the gas phase

T

Scaled molar concentration of tar fragments or temperature, K

t

Time, s

tj

Tar fragment with j linked aromatic nuclei

Yi

Scaled molar yield of product i

Page 46 of 57

Greek Symbols 

Average moles of nitrogen per aromatic nucleus

B

Scission selectivity coefficient for labile bridge conversion

C

Stoichiometric coefficient for gas production during spontaneous charring of labile bridges

B*

Twice the stoichiometric coefficient for gas production during elimination of hydrogenated peripheral groups

HY

Stoichiometric requirement for H2 in labile bridge hydrogenation

K,MH Stoichiometric coefficient for species K = O, H2O, H2S, NH3 from monomer hydrogenation MH

Stoichiometric requirement for H2 in monomer hydrogenation

O

Stoichiometric coefficient for oil production from monomer decomposition

S

OG* Stoichiometric coefficient for gas production from monomer decomposition for S=1 or 2 hydrogenated peripheral groups on the tar monomer

Rj

Stoichiometric coefficient for soot for nucleation and addition of tj into soot

R,O

Stoichiometric coefficient for soot in addition of oils to soot

0

Bulk coal density, g/cm3

i

Std. dev. about the mean energy for a reaction involving component i, kJ/mol

C

Residual moles of oxygen in a newly formed char link

Subscripts


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B

Labile bridges

B*

Hydrogenated bridges

C

Char links

FC

Pertains to quantities from FLASHCHAIN for primary hydropyrolysis

HC

Hydrocracking of labile and hydrogenated bridges and char links

HY

Hydrogenation of labile bridges and peripheral groups

MH

Monomer hydrogenation

N

Aromatic nuclei

R

Soot

S

Labile peripheral groups

S*

Hydrogenated peripheral groups

SN

Soot nucleation

SC

Soot addition

TD

Monomer decomposition

tj

Tar j-mer

References (1)

Niksa, S.

Flashchain theory for rapid coal devolatilization kinetics. 10. Extents of

conversion for hydropyrolysis and hydrogasification of any coal. Energy Fuels 2018, 32, 384-95. (2)

Guan, Q., Dapeng, B., Xuan, W., Zhang, J. Kinetic model of hydropyrolysis based on the CPD model, Fuel 2015, 152, 74-79.

(3)

Niksa, S. Interpreting coal conversion under elevated H2 pressures with FLASHCHAIN and CBK, Proc. 2011 Int. Conf. on Coal Science and Technol., IEA, Oviedo, Spain, 2011.


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Niksa, S. Flashchain theory for rapid coal devolatilization kinetics. 9. Decomposition mechanism for tars from various coals. Energy Fuels 2017, 31, 9080-93.

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Niksa, S., Kerstein, A. R. Flashchain theory for rapid coal devolatilization kinetics. 1. Formulation. Energy Fuels 1991, 5(5), 647-64.

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Xu, W.-C.; Tomita, A. Effect of coal type on the flash pyrolysis of various coals. Fuel 1987, 66(5), 627.

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Chen, J. C.; Castagnoli, C.; Niksa, S. Coal devolatilization during rapid transient heating. Part 2: Secondary pyrolysis. Energy Fuels 1992, 6, 265-71.

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Xu, W.-C.; Matsuoka, K.; Akiho, H.; Kumagai, M; Tomita, A. High temperature hydropyrolysis of coals by using a continuous free-fall reactor. Fuel 2003, 82, 677-85.

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Ikura, M.; Last, A. J. Flash hydropyrolysis of caking bituminous coal. Fuel Process. Technol. 1988, 20, 257-68.

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Tang, L.; Zhu, Z.; Gu, H.; Zhang, C. The effect of coal rank on flash hydropyrolysis of Chinese coal. Fuel Process. Technol. 1999, 60, 195-202.

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Finn, M. J.; Fynes, G.; Ladner, W. R.; Newman, J. O. H. Light aromatics from the hydropyrolysis of coal. Fuel 1980, 59, 397-404.

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Fallon, P. T.; Bhatt, B.; Steinberg, M. The flash hydropyrolysis of lignite and subbituminous coals to both liquid and gaseous hydrocarbon products. Fuel Process. Technol. 1980, 3, 155-68.


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Chen, W.-Y.; LaCava, A. I.; Graff, R. A. Flash hydrogenation of coal. 3. A sample of US coals. Fuel 1983, 62, 56-61.

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Steinberg, M. The flash hydropyrolysis and methanolysis of coal with hydrogen and methane. Int. J. Hydrogen Energy 1987, 12, 251-66.


49

Energy & Fuels

25

20

Primary Tar, daf wt.%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 50 of 57

15

10

5

0 0

10

20

30

40

50

Measured Tar + Oils, daf wt.%

Figure 1. Predicted primary tar yields from hydropyrolysis vs. sums of reported yields of tar plus oils. Open symbols below the parity line are from () Fallon et al.12 and () Chen et al.13


Page 51 of 57

35

25

30

Primary Tar

25

Primary Tar 20

15

Oils


20


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

15

Oils 10

10

Secondary Tar 5

5

Secondary Tar 0 0

1

2

3

4

5

0 600

650

H2 Pressure, MPa

700

750

800

850

Temperature, C

Figure 2. (Left) Evaluation of yields of () oils and () secondary tar from a subbituminous coal for heating at 2000 C/s to 800 C under various H2 pressures; and (Right) Evaluation for different temperatures under 3 MPa H2. Predicted primary tar yields appear as the dashed curves. Both test series imposed 1.8 s coal contact time and 3 s gas contact time in a FFR.8


900

Energy & Fuels

15.0 70

12.5

Primary Tar

10.0



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Oils

7.5

5.0

2.5

Secondary Tar

Wt. Loss 60

50


40

Predicted Volatiles Yield

30

0.0 650

700

750

800

650

675

Temperature, C

700

725

750

775

800

Temperature, C

Figure 3. (Left) Evaluation of yields of () oils and () secondary tar from a high volatile (hv) bituminous coal blend for heating at 8000 C/s to different temperatures under 12.9 MPa H2 with coal contact times from 3.7 to 6.5 s and gas contact times from 14 to 23 s.9 Predicted primary tar yields appear as the dashed curve. (Right) () Measured and ( connected by line segments) predicted total weight loss and ( connected by dashed line segments) predicted volatiles yields for the same test conditions.


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20

15


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Primary Tar 10

Oils

5

Secondary Tar 0 70

75

80

85

90

95


Figure 4. Evaluation of yields of () oils and () secondary tar from diverse coals for heating at 5 C/s to 600 C for 900 s under 15 MPa H2 with hydroconversion is a second reactor stage at 850 C with 4 s gas contact time.11 Predicted products appear as corresponding open symbols connected by solid line segments. Predicted primary tar yields appear as () connected by dashed segments.


Energy & Fuels

15.0

25

12.5

20

Oil Mixture 10.0

Tar Yields, daf wt.%

Oils Yield, daf wt.%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 54 of 57

7.5

5.0

Adjustment to C6H6

15

Primary Tar

10

5

2.5

0.0 70

75

80

85

90

Secondary Tar

0 70


75

80

85

90


Figure 5. Evaluation of yields of () oils and () secondary tar from diverse coals for heating at 7000 C/s to 750 C for 2 s under 4 MPa H2 in a FFR with 42 s gas contact time.10,15 Predicted products appear as corresponding open symbols connected by solid line segments. The left panel also shows the predicted oils mixtures of substituted BTX + PCX as () connected by dotted line segments. Predicted primary tar yields appear in the right panel as () connected by dashed segments.


Page 55 of 57

60


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

50

Measured Wt. Loss


40

30

Predicted Volatiles Yield 20

10

0 70

75

80

85

90


Figure 6. () Measured total weight loss and ( connected by dashed line segments) predicted volatiles yields for the test conditions in Figure 5.10


Energy & Fuels

100000 80000 60000

-0.5 -1

40000

AHG atm s

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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20000

8000 6000 4000 2000 0 65

70

75

80

85

90

95


Figure 7. Assigned pseudo-frequency factors for char hydrogasification to interpret datasets on () 14 diverse coals from Tang et al.10; () 3 coals from Xu et al.8; () 1 coal blend from Ikura and Last9; and () for the 21 coals in the validations with coal conversions reported previously.1


Page 57 of 57

5

4

3

YOils/ATar

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

2

1

0 70

75

80

85

90

95

Carbon Content, daf wt. %

Figure 8. Ratio of predicted oils yields to the amounts of aromatic nuclei in primary tar vs. coalC contents for () 14 coals from Tang et al.10 where YOILS are the predicted BTX/PCX mixtures rather than the benzene-only values; () 3 coals from Xu et al.8; () 1 coal blend from Ikura and Last9 and () 8 coals from Finn et al.11


FLASHCHAIN Theory for Rapid Coal Devolatilization Kinetics. 11. Tar

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