ARTICLE pubs.acs.org/EF
Evaluating the Combustion Reactivity of Drop Tube Furnace and Thermogravimetric Analysis Coal Chars with a Selection of Metal Additives Katherine Le Manquais,*,†,‡ Colin E. Snape,† Ian McRobbie,‡ and Jim Barker‡ †
Department of Chemical and Environmental Engineering, Faculty of Engineering, University of Nottingham, NG7 2RD, United Kingdom ‡ Innospec Limited, Oil Sites Road, Ellesmere Port, Cheshire, CH65 4EY, United Kingdom ABSTRACT: Opportunities exist for effective coal combustion additives that can reduce the carbon content of pulverized fuel ash (PFA) to below 6%, thereby making it saleable for filler/building material applications without the need for postcombustion treatment. However, with only limited combustion data currently available for the multitude of potential additives, catalytic performance under pulverized fuel (PF) boiler conditions has received relatively little attention. For the first time, this paper therefore compares the reactivity of catalyzed bituminous coal chars from thermogravimetric analysis (TGA) with those generated by devolatilization in a drop tube furnace (DTF). The principal aim was to explore the fundamental chemistry behind the chosen additives’ relative reactivities. Accordingly, all eight of the investigated additives increased the TGA burnout rate of the TGA and DTF chars, with most of the catalysts demonstrating consistent reactivity levels across chars from both devolatilization methods. Copper(I) chloride, silver chloride, and copper nitrate were thus identified as the most successful additives tested, but it proved difficult to establish a definitive reactivity ranking. This was largely due to the use of physical mixtures for catalyst dispersion, the relatively narrow selection of additives examined, and the inherent variability of the DTF chars. Nevertheless, one crucial exception to normal additive behavior was discovered, with copper(I) chloride perceptibly deactivating during devolatilization in the DTF, even though it remained the most effective catalyst tested. As a prolonged burnout at over 1000 °C was required to replicate this deactivation effect on the TGA, the phenomenon could not be detected by typical testing procedures. Subsequently, a comprehensive TGA study showed no obvious relationship between the catalyst-induced reductions in the reaction’s apparent activation energy and the samples’ recorded burnout rates. Although copper(I) chloride did generate a diffusion controlled reaction regime at a lower temperature than the other additives. Furthermore, only the thermally labile iron(III) chloride appeared capable of exerting a catalytic effect under mass transfer controlled combustion regimes, signifying that the physical state of the catalyst could be an important factor during PF combustion.
1. INTRODUCTION With the advent of low NOx burners and the high levels of inertinite in a number of internationally traded coals, nearly complete carbon burnout has become inherently more difficult to achieve during pulverized fuel (PF) combustion. Indeed, the increased unburnt carbon content in pulverized fuel ash (PFA) is creating considerably more problems worldwide than a decade ago, especially in terms of the ash’s suitability for use in byproducts and, hence, its ease of disposal.1 However, it has also provided the opportunity to develop effective coal combustion additives that can reduce the carbon content of PFA to below 6% (ASTM C618-08a), thus obviating the need for postcombustion treatment. Such treatment is often required to meet specifications for filler/building material applications and, thereby, to avoid superfluous landfilling. Although similar additives have previously been used to improve the efficiency of coal combustion systems,2 their implementation has normally been on an operational trial and error basis rather than from a detailed understanding of the complex reaction mechanisms involved. Historically, this was partly because of the assumption that inherent char reactivity is not a conversion limiting factor at the high temperatures experienced in a PF furnace, allowing diffusion processes to dominate (combustion regime III).3 But, r 2011 American Chemical Society
as small particle sizes increase the extent of boundary layer diffusion4 and since char deactivation can cause low intrinsic reactivity to occur after a relatively short heat treatment time,5 a combination of diffusion and chemical control now appears to be much more likely (regime II).6 This implies that the overall combustion rate will be the result of three interacting factors: the intrinsic reaction rate of the internal surface of the coal particles, the size of this surface, and the extent to which oxygen diffusion through the pores restricts the reaction.7 To compare the combustion activities of different coal and additive combinations, it can therefore seem preferable to decouple any mass and heat transfer effects from those of the chemical reaction.8 Unsurprisingly, this supposition has resulted in considerable recent research into suitable catalyst candidates, all of which has been focused on small-scale thermogravimetric analysis (TGA) based techniques.9-17 TGA provides a convenient and quantitative means of assessing the sample mass changes that occur during coal combustion. These instruments are relatively small, cheap, and fast to run—easily lending themselves to the Received: November 22, 2010 Revised: February 3, 2011 Published: March 02, 2011 981
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Table 1. Proximate, Ultimate, and Maceral Analyses of ATC PF proximate analysis
ultimate analysis
maceral analysis
fixed
ATC
semi-
moisture (wt %)
ash (wt %)
carbon (wt % daf)
volatiles (wt % daf)
C (% daf)
H (% daf)
N (% daf)
S (% daf)
O (% daf)
vitrinite (% daf)
liptinite (% daf)
fusinite (% daf)
fusinite (% daf)
5
13
69
31
85
5
2
1
7
45
4
43
8
assessment of a large number of doped coal samples. In addition, TGA burnout results have formerly been used in conjunction with chars produced on medium scale devices, such as drop tube furnaces (DTFs).18 DTFs are capable of creating an environment that simulates certain PF boiler conditions; in particular the short residence times, high temperatures, fast heating rates and dilute particle phases.19 These operating variables are known to have a significant influence on char morphology and can be critical factors in determining a coal’s carbon burnout propensity.20-22 However, DTFs are much larger than TGAs and, consequently, much more expensive and time-consuming to operate. Comparisons between TGA and DTF results have, furthermore, frequently led to conflicting reactivity trends being reported.21,23,24 No studies into additives have hitherto included any char production in a DTF or, instead, in any other system that closely replicates PF boiler conditions. By conducting TGA burnout analyses on catalyzed DTF chars and their TGA counterparts, this paper therefore comprehensively appraises the combustion enhancements associated with a broad selection of different inorganic compounds. These eight salts were nominally selected because they or similar compounds are recognized catalysts for the occurring reaction—either as established coal combustion, soot oxidation, or coal gasification treatments.25-27 In order to study the additives in their simplest forms, only the purest versions of the salts were investigated; since moving to economically favorable grades increases the likelihood of trace impurities influencing catalysis.28 Hence, the ability of TGA to reproduce the behavior of such additives in the DTF environment was established and the increase in burnout variability associated with the introduction of a physical mixture catalyst was also calculated. Ultimately, TGA was also used to replicate the medium-scale deactivation of one of the additives, in addition to exploring the additives’ influences on the encountered combustion regime, specifically in terms of more pronounced mass transfer control.
devolatilization (premixed) or postdevolatilization but before TGA burnout (postmixed). In order to lessen any self-heating within the samples, coal and char portions of 5 mgs were used for the TGA work. 2.2. Additive Selection. Here, the primary aim was to explore the fundamental chemistry behind the catalytic reactivities of the chosen inorganic compounds. This is in contrast with many previous papers where a chemical’s cost, its availability, the assessment of a specific patented formulation or an additive’s environmental and other limitations have often appeared to be the determining factors when deciding which salts to investigate.9-17 The tested inorganic compounds were cesium chloride calcium nitrate, copper(I) chloride, copper nitrate, iron(II) chloride, iron(III) chloride, silver chloride, and sodium nitrate. All of these were added to the coal at a treat rate of 1 part catalyst to 99 parts coal by weight (a 1% mass loading). The samples were agitated using a flask stirrer to encourage an even dispersion of the catalyst in the physical mixture. 2.3. DTF. The DTF consists of a coal screw-feeder, water-cooled feeder, and collector probes, a controllable gas system, and a 1.5 m ceramic work tube, with an internal diameter of 50 mm and 5 mm thick walls. The DTF was heated to 1300 °C using three programmable heaters and, based on heating only occurring during the first half of a particle’s residence time, heating rates of the order of 104 °C s-1 can be assumed. An atmosphere of 1% oxygen in nitrogen (mol mol-1) was maintained, rather than true pyrolysis conditions, to allow for the combustion of any tars formed. A variety of furnace residence times were used when producing the chars—200, 400, and 600 ms—and these were achieved by correcting the inlet gas flows and lowering the DTF’s collector probe to set distances below the feeder probe. The three chosen residence times corresponded to probe separations of 22, 45, and 65 cm, respectively. 2.4. TGA. Chars were also produced using the TGA function of a TA SDT Q600 instrument, which heated the samples at 150 °C min-1 to 1100 °C under a nitrogen atmosphere, according to a previously optimized and reported devolatilization procedure.22 Once formed, the combustion activities of the different chars were measured using isothermal TGA burnouts at 525 °C. To do this, the DTF chars were heated at a rate of 50 °C min-1 to 525 °C under nitrogen, the furnace’s atmosphere was switched to air, and the samples were combusted for 80 min. For the TGA chars, the furnace was cooled to 525 °C after pyrolysis, and the samples were immediately burnt out. Earlier coal combustion work with the SDT Q600 has indicated that a diffusion based lag-time of at least 4 min should be expected at the start of this burnout period, while the furnace is filling with air.22 This can give the resultant burnout profiles a shape that is reminiscent of previously modeled self-acceleration behaviors,30 although no evidence has been collected to verify whether or not such an effect also occurs. Two carefully chosen measures of reactivity were therefore calculated. First, the time until 90% carbon conversion, and second, apparent first-order kinetics were applied between 5 and 95% carbon burnout to allow for the calculation of an average apparent rate constant (k) using
2. EXPERIMENTAL PROCEDURE 2.1. Coal Preparation. The coal used in this study was from the Arthur Taylor Colliery (ATC) in South Africa. Its proximate, ultimate, and maceral analyses are listed in Table 1. The ATC coal sample was ground using a ball mill before being sieved into a 38-53 μm fraction, from which any entrained fines were removed using an Alpine Jet Sieve. The 38-53 μm particle size range was chosen because fractions of cesium chloride > sodium nitrate > calcium nitrate ∼ iron(II) chloride ∼ iron(III) chloride > no catalyst. Commencing with, ostensibly, the two most successful TGA additives, the advantage of copper’s and silver’s readily changeable valence and their ability to exist in more than one oxidized
3.1. Additive Behavior with TGA Char. A previous publica-
tion has already established the combustion characteristics of TGA and DTF chars from the parent coal to be used in this study,22 indicating that ATC coal can be considered to be an ideal baseline from which to evaluate catalysts. But, before the combustion improvements associated with the individual additives were evaluated, it seemed prudent to characterize the effect of physical mixture catalyst dispersion on TGA char burnout repeatability and reproducibility. Especially as physical mixture dispersion is one of the most convenient and popular methods of introducing additives to coal.10-14 Table 2 thus shows the variability occurring in uncatalysed TGA char and TGA char with a moderately good additive, by using standard deviations in the two benchmark reactivity measures as indicators of data spread. The standard deviation for cesium chloride catalyzed TGA char was based on five discrete samples, all of which were analyzed five times, whereas the reactivity distribution for the uncatalysed char has been published previously.22 Hereby, Table 2 reveals that the burnout variability associated with the introduction of cesium chloride was considerable. The sample’s standard deviation, which was roughly (2% of the mean reactivity of the TGA char prior to additive addition, increased to somewhere in the region of (15-50% of the mean (depending on the reactivity criterion used). Although, given the unsophisticated method used for additive dispersion and the small mass of coal tested per TGA run, such substantial unpredictability was not, perhaps, very surprising. Furthermore, the error recorded in Table 2 will have been strongly dependent on the innate efficiency of the additive involved and/or its physical properties. As a result, the standard deviations associated with a more successful additive are likely to be much more significant. This advocates that a repeatability and reproducibility assessment should ideally be completed for every individual additive and weighting, even though time constraints 983
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Table 3. Additive Induced Reductions in the Time until 90% Carbon Conversion for TGA and DTF Chars DTF Char 200 ms TGA char (min)
premixed (min)
400 ms
postmixed (min)
premixed (min)
44.4
600 ms
postmixed (min)
premixed (min)
59.6
postmixed (min)
no catalyst
37.8
with iron(II) chloride
25.5
21.5
36.6
35.1
45.5
32.6
40.6
with iron(III) chloride
24.4
21.9
38.0
37.3
43.2
33.0
39.8
with calcium nitrate
23.4
20.4
45.9
28.9
33.1
31.3
52.0
with sodium nitrate with cesium chloride
20.4 18.2
23.8 19.6
45.1 42.8
28.4 26.1
27.5 29.2
29.4 30.9
50.2 51.1
with copper nitrate
16.6
17.0
34.0
23.5
24.3
18.1
41.9
with silver chloride
11.3
15.9
30.5
25.2
22.0
25.5
42.1
with copper(I) chloride
12.0
10.1
5.8
12.4
5.8
17.6
5.7
form becomes obvious if a reduction-oxidation (redox) combustion mechanism is presumed. Since, depending on the surrounding conditions, a transition metal cation might be able to acquire and then transfer multiple atoms of oxygen, whereas a group I or II element can only react in accordance with its set stoichiometry.33 This reaction scheme is akin to that proposed for the transition metal oxides12 and is also similar to the formation of a copper(I) oxide active phase during carbon black oxidation.32 Likewise, an equivalent cycle advocated for halide catalyzed soot prevention provides insight into the possible benefits associated with the chloride anion. In this reaction pathway, the dissociation and activation of oxygen is believed to occur on the metal ion of the halide compound and is followed by a shuttle mechanism that transfers it to the surface of the soot particle. This creates a carbon-oxygen complex, whose decomposition then yields carbon monoxide and carbon dioxide.34,35 Mobility of the catalyst particles prior to and during combustion is thus a major parameter in determining the amount of carbonoxygen contact, and it closely corresponds to the additive’s melting point and partial pressure. Consequently, halide anions are thought to possess improved migration capabilities from the in situ formation of intimate contact via wetting or gas phase transport.35 Given that the loose soot-catalyst contact therein portrayed is analogous to the physical mixture dispersion being employed here, a parallel mechanism seems highly plausible, although it should be noted that chlorine free radicals are also renowned oxidizing agents. Unfortunately, such a scheme did not seem to correspondingly promote the activities of iron(II) and iron(III) chloride, although their catalyzed combustion rates were considerably faster than that of the untreated coal. This is particularly remarkable because the iron chlorides have been a frequent additive choice in previous investigations—not only for coal combustion13 but also with soot oxidation.35 Nevertheless, as the anion remains unchanged from the above discussion, this reduction in catalytic reactivity was logically accredited to the presence of a different transition metal. No significant variations exist, however, between the ionization energies of the copper, silver and iron cations. Instead, this behavior could have originated from other properties, such as the compounds’ relative molecular weights or their melting points. For example, copper(I) chloride and silver chloride are presumably molten at the TGA burnout temperature of 525 °C, whereas iron(II) chloride might have resolidified (since it has a melting point of 677 °C) and iron(III) chloride will have already partially decomposed to form iron(II) chloride and
50.6
chlorine vapor. This implies that iron(II) chloride’s and iron(III) chloride’s comparative migration capabilities could have been reduced, decreasing the resultant catalyst-coal contact and, thus, the achieved rate of combustion during the subsequent burnout. Copper nitrate, in contrast, can be supposed to possess the copper cation’s multiple oxidation states but not the chloride anion’s augmented mobility, thus limiting its relative performance in Figure 1 and Table 3. Equally the advantage supplied by the chloride ion might have remained for the investigated group I additives, with cesium chloride outperforming sodium nitrate, but this result could also have been due to the propensity of the smaller alkali cations to react with the coal’s carbon matrix.36 Although all of the alkali cations have been shown to demonstrate some initial evidence of mobility, lithium and sodium possess the highest inclination to form bulk carbonate, which cannot participate in exchange reactions.37 Hence while cesium can migrate into and across the char, smaller elements like sodium tend to agglomerate on the particles’ surfaces. Fundamentally, as the group I elements’ propensity to disperse increases, so does their ability to form complexes, the assumed active sites of both gasification and combustion. Since hydrolysis experiments have indicated that all alkali metal complexes are probably equivalent,38 the creation of fewer of them will severely impede an additive’s catalytic prowess. Besides, the manifestation of all of these effects will have been at least partially mitigated by the wide ranging molecular masses of the compounds involved. For instance, almost twice as many sodium nitrate molecules (∼0.000 12 mol g-1) were present compared to cesium chloride ones (∼0.000 06 mol g-1). This signifies how additive reactivity might be better viewed on a molecular footing, where an equal number of catalyst particles can be compared. Such an effect could also explain why sodium nitrate was a more successful additive than calcium nitrate; substantiating a trend that has previously been identified during both pyrolysis39 and gasification.40 However, this behavior has generally been attributed to the metal ions’ first ionization energies (495.8 kJ mol-1 for sodium compared to 589.8 kJ mol-1 for calcium) and their different valences, which imply that there could be different types of bonding to the coal’s macromolecular structure.15 Thus, although the reactivity of a group II site is probably comparable to that of group I, it has been suggested that it can only form at the additive-carbon phase boundary.41 This suggests that the main problem could be one of catalyst dispersion, retention, or the resulting carbon to metal ion ratio, even though the more restrictive bonding might also make 984
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Figure 2. TGA burnout profiles for iron(II) chloride catalyzed TGA and DTF chars.
Figure 3. TGA burnout profiles for copper(I) chloride catalyzed TGA and DTF chars.
the alkaline earth metal compound poorer at dissociating oxygen.37 An intention of future publications is therefore to examine multiple additive weightings. This should ultimately determine whether the results depicted here, and many of those from previous studies,9,11-13,16 provide an accurate insight into the behaviors of the tested additives or whether they have been influenced by the molecular masses of the compounds involved. 3.2. Additive Behavior with DTF Char. Before the additives’ performances in industrial scale char could be determined, the combustion characteristics of the unmodified DTF samples needed to be reaffirmed. Comparable data has already been published for ATC’s 53-75 μm coal fraction,22 and results from a selection of uncatalysed 38-53 μm DTF chars are displayed in Figure 1 and Table 3. Of these, the 200 ms DTF char seemed to be the most active. Burnout reactivity then appeared to decrease for the 400 ms char, since the longer residence time would have amplified thermal deactivation5 and reduced volatile matter retainment.42 Conversely, an increase in combustion reactivity was witnessed with the 600 ms sample. This implies that there could have been a change to the flow patterns within the DTF, because of the greater probe separation. Or that, over the longer residence time at high temperature, the 1% oxygen present might have provided an artificial activating side effect.43 However, these DTF chars also possessed substantial burnout variability from fluctuating devolatilization process variables and their effect on the evolved char structure. This gave the 400 ms DTF char from this particle size range a result standard deviation of up to (38% of the mean rate of carbon burnout.22 Such inconsistency obviously caused major difficulties when using these chars as the basis for investigation, particularly in terms of deriving a comprehensive additive ranking, and it is proposed that another experimental technique, like a wire mesh reactor, could be used to provide more reliable reactivity trends. Meanwhile, in order to minimize underlying char variability during the current study, the most unreactive chars from all three residence times were used to provide the uncatalysed benchmarks and for making up the postmixed samples. This accounted for the reactivity difference between the 400 ms DTF char and that from the TGA devolatilization procedure, which was originally optimized according to the average DTF char reactivity that was obtained under these conditions.22 Progressing to concentrate on the additives, the results shown in Figure 2 and Table 3 confirmed that iron(II) chloride boosted the rate of carbon burnout for all the investigated char types. The
reactivity pattern demonstrated was reminiscent of uncatalysed ATC—displaying a descending activity trend of 200 > 600 > 400 ms, although the premixed 200 ms DTF char was now of similar reactivity to its TGA counterpart. Interestingly, the greatest burnout enhancements seem to have occurred with the two 400 ms DTF chars, i.e. with the samples that possessed the lowest inherent reactivity. This agreed with other recently published results where an iron(III) oxide catalyst was found to be more effective during the combustion of higher rank, and hence, more unreactive coals.17 This bodes well for a positive performance with the unreactive carbon that is customarily found in the oxygen deprived zones of a PF furnace. Similarly, iron(II) chloride seemed to be most effective when it was premixed with the coal, again in accordance with the data collected from iron(III) oxide.17 This suggested that superior catalyst dispersion arose when devolatilization took place with the iron(II) chloride in situ, permitting the additive to be introduced into or onto the char’s structure during its formation.44,45 Other recent work has coincidentally suggested that iron(III) oxide might aid the production of free radicals during anthracite pyrolysis, hindering polymerization and the formation of graphitic nature carbon units.46 Although, conversely, it has also been reported to promote these types of behaviors in some blast furnace chars and cokes.47 This implies that, even if the produced additivecarbon contact was vital to ensuring a good combustion performance, iron(II) chloride’s presence might have been responsible for more than just facilitating future oxygen transfer.48 In contrast, copper(I) chloride presented rather different reactivity traits in Figure 3, where postmixing of the DTF char and additive was favored. This was most obvious in the three postmixed samples’ burnout profiles, which were much steeper than the ones that had embarked on a TGA or DTF devolatilization with the additive in attendance. In fact, the sheer gradients of the postmixed profiles in Figure 3 even implied that these combustions might have occurred under total mass transfer control (i.e., regime III). A logical deduction was that evaporation or some sort of catalyst deactivation was severely impeding copper(I) chloride in all other instances. This occurrence was moderate and therefore difficult to perceive in the TGA testing environment, but it was clearly evident in the burnout profiles of the chars from the harsher conditions of DTF devolatilization. Further proof was provided in the relative profiles of the premixed DTF chars, where the least reactive sample was the one with the longest residence time at high temperature. 985
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particularly surprising, given that ∼30% of the coal had already been lost from the postmixed samples prior to additive addition. Discounting any catalyst losses from volatilization, these samples therefore possessed effective additive-to-char ratios roughly one and a half times greater than those occurring in the equivalent premixed DTF and TGA chars. From the amount of catalyst alone, the postmixed samples should always have exhibited the fastest combustion rates. Greater variability also seemed to emerge in the reactivity trends produced by the postmixed chars’ burnout times, perhaps further highlighting the inferior dispersion or the larger catalyst losses that arose when the char’s structure was formed prior to additive addition. This was particularly apparent with the alkali and alkaline earth additives, possibly because of their inferior migration capabilities36 or from a change in the catalytic mechanism.10 One final complication in the data in Figure 1 and Table 3 was the aforementioned reactivity differences that existed between the underlying TGA and DTF chars. Hence, even though the gap between the TGA and DTF char results appeared to become more prominent with the most proficient additives, this was could have been from the TGA char’s greater inherent reactivity, rather than being supplementary evidence of catalyst loss or deactivation. Essentially, a reduction in thermal annealing will have produced a less ordered carbon structure that was more susceptible to catalytic enrichment because of the amount and the accessibility of its active sites.53 Due to all of these interrelating concerns, it remained impossible to establish a definitive additive reactivity order. Particularly since most of the additives banded together at moderate reactivity levels which were difficult to distinguish between, because of the innate variability of the underlying DTF char.22 Besides, previous evaluations of DTF sample variability might have been underestimations, as they do not account for the unpredictability associated with the introduction of an additive via physical mixture dispersion (as was calculated for TGA char catalyzed by cesium chloride in Table 2). Once again, these errors remain wholly uncalculated because of processing time constraints, which make individual quantifications much less feasible than with TGA char. Thus, for most additives, the burnout of catalyst containing TGA chars could be the most conclusive way of comparing compounds. This is because no extra insight was gained by devolatilising on the DTF and poorer repeatability and reproducibility was encountered. However, the above discussion of Figure 1 and Table 3 did not emphasize the results of copper(I) chloride—the most successful catalyst for all types of DTF char and the second most effective with TGA char. Crucially, results from a combination of DTF residence times and/or comparable pre- and postmixed samples were required to identify its loss or deactivation. If TGA alone is going to be used to assess future additives, an alternative recognition technique needs to be developed. 3.3. Replicating DTF Additive Deactivation on the TGA. Having identified a catalytic phenomenon that was not evident in the TGA char investigations, methodology modifications were required to detect this behavior on the small scale. A high temperature burnout step was deemed logical—as Figure 1 and Table 3 had already shown that the existing high temperature TGA devolatilization did not appreciably impede copper(I) chloride’s burnout reactivity. Figure 5 therefore displays profiles from 1100 °C burnout runs with a selection of catalyzed TGA chars. These confirmed that the additive was indeed deactivating, by showing the opposite reactivity trend to that witnessed at
Figure 4. TGA burnout profiles for copper nitrate catalyzed TGA and DTF chars.
Copper(I) chloride’s inhibition was thus time dependent, but it must also have also been influenced by temperature and/or heating rate, otherwise the catalyzed TGA char would have been the least reactive of those assessed. Potential explanations behind the deactivation of the additive could include catalyst-mineral matter synergisms49 or the intensification of copper(I) chloride based thermal annealing.50 Equivalent behavior was not detected for the copper nitrate containing chars examined in Figure 4. Instead, the burnout profiles of the TGA and DTF chars were more reminiscent of those from iron(II) chloride. This indicated that the phenomenon did not affect all the transition metal chlorides and, meaningfully, all the copper compounds. Furthermore, it has not been commented on in any past combustion studies with other copper salts.51,52 This occurrence is therefore likely to be very restricted, either isolated to this specific compound or to a small number of similar ones—like the copper halides. Even so this event still warrants further examination because, hitherto, it has not been possible to uncover its exact origin. The importance of identifying such a cause depends on both the severity of the problem in a more realistic oxidizing environment, like that of DTF burnout, and on the potential usefulness of a copper(I) chloride additive or any others that are likewise inhibited. To this end, the above figures were placed in context by comparing the burnout performances of all eight additives across specific char types. This is the case in Figure 1, where the catalyzed TGA chars are ranked from left to right by their apparent first-order burnout rate constants and the results for the premixed and postmixed 400 ms DTF chars are also displayed. Here, the rate constants of the catalyzed DTF chars predominantly correlated with the additive grading that was formerly established for the TGA char—demonstrating a gradual increase in combustion rate toward the right-hand side of the graph. Table 3 shows the additive dependent alterations in the time until 90% carbon conversion for all of the investigated char types, where the premixed 200 and 600 ms DTF char samples’ results again approximately agreed with both of the above reactivity trends. Copper nitrate, copper(I) chloride, and silver chloride were revealed to be the most successful additives on all but one of the investigated char types. The data displayed in Figure 1 and Table 3 additionally implies that premixing of the additive and the coal prior to devolatilization was only occasionally beneficial and rarely as influential as was witnessed for iron(II) chloride. However, this was not 986
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Table 4. Apparent Activation Energies and Pre-exponential Factors from the Combustion of TGA Chars Containing Selected Catalysts apparent activation
apparent
energy (kJ mol-1)
pre-exponential factor
no catalyst
84.9
5.14
with iron(III) chloride
81.8
5.10
with iron(II) chloride
78.0
4.91
with copper(I) chloride
77.9
5.23
illustrated in Figure 6, where Arrhenius plots for a narrow selection of catalyzed TGA chars are shown—although the standard x-axis of the Arrhenius graph, the reciprocal of temperature, has been replaced with temperature for ease of comprehension. In Figure 6, each of the profiles can be subdivided into two distinct regimes for the average first-order combustion rate constant. First, a linear ascending region where some level of kinetic control can be assumed, and second, a horizontal section where the combustion rate is stable because of complete mass transfer control. Thus, while most of these results reaffirmed that the upper temperature limit for some kinetic influence during the combustion was 575 °C,22 when the reaction was assisted by copper(I) chloride mass transfer control materialized at the lower temperature of 500 °C. A parallel reduction has already been noticed during the copper catalyzed gasification of coal,55 where the superior reaction rate again allowed mass transfer to become the rate determining step at a cooler temperature than was otherwise feasible. Now that these boundaries had been firmly established, apparent activation energies could be calculated from the gradients of the ascending sections of the Arrhenius plots. These values were not true activation energies however, since some diffusion-based rate limitations would have been present. As expected,11 Figure 6 and Table 4 show that all the additives reduced the observed average activation energy from the previously determined 85 kJ mol-1,22 even though there was no obvious relationship between these reductions and the already recorded burnout improvements. For example, the apparent activation energies of the copper(I) chloride and iron(II) chloride chars were both 78 kJ mol-1 but, in Figure 1, copper(I) chloride provided a combustion rate constant that was twice as fast. This lack of association might be due to the additives limiting mass transfer, for example by blocking the char’s pore structure to differing extents,56 or it could be taken as evidence of a multifaceted catalytic mechanism.25 Either way, catalyzed coal combustion is highly complex, which alludes to why—as with soot oxidation57—activation energy data has not been universally reported. Instead, additives have usually been ranked according to qualified temperatures,12,13 conversions or combustion rates (as was done above).12-14,17 Finally, the mass transfer controlled rate constants displayed in Figure 6 were also of interest. Here a definite reduction in burnout speed was observed for the copper(I) chloride and iron(II) chloride samples, whereas a rate increase occurred with iron(III) chloride. Since this was not evidence of evaporation or deactivation—as iron(II) chloride seemed uninhibited under the higher temperatures of DTF devolatilization—different reasoning was required to explain these results. It was realized that copper(I) chloride and iron(II) chloride were either solid or molten at all of the temperatures used in Figure 6. Iron(III) chloride, conversely, has a decomposition temperature of 315 °C,
Figure 5. Reproducing catalyst deactivation by conducting TGA char burnouts at 1100 °C.
Figure 6. Influence of TGA burnout temperature on the control regimes of a selection of the catalyzed coal combustions.
525 °C (iron(II) chloride > copper(I) chloride) and because the copper(I) chloride catalyzed sample was now less reactive than the untreated base coal. This represented a more pronounced inhibition than that experienced on the DTF, which can be accredited to the much longer residence time of the catalyst at high temperature and/or to the presence of higher oxygen concentrations.54 An 1100 °C burnout temperature would, unfortunately, be an unsuitable choice for ordinary TGA additive testing, since the encountered combustions were almost completely mass transfer controlled. For example, the iron(II) chloride catalyzed profile presented in Figure 5 was in or adjacent to the diffusion controlled reaction regime (III). As such, any improvement in the sample’s intrinsic reactivity did not cause an observable increase in the rate of carbon burnout. This would clearly make it very difficult to distinguish between the most effective additives at this burnout temperature. Furthermore, since only one of the eight additives tested deactivated, typical deactivating compounds might be identifiable from their inferred chemical characteristics—without the need to permanently amend the standard TGA heating procedure. 3.4. TGA Combustion Regime Study. The high temperatures required for the deactivation of copper(I) chloride also created problems for quantifying this phenomenon in terms of its influence on the reaction’s apparent activation energy. Specifically because the combustion of copper nitrate > cesium chloride > sodium nitrate > calcium nitrate ∼ iron(II) chloride ∼ iron(III) chloride > no catalyst. However, sample repeatability and reproducibility was very poor, with a moderately catalyzed TGA char demonstrating a result standard deviation of (50% of the mean rate of carbon combustion. This was attributed to the physical mixture catalyst dispersion being employed. As such, it was difficult to accurately differentiate beyond exceptional catalysts (copper(I) chloride, copper nitrate, and silver chloride) and effective additives (all of the other compounds tested), meaning that it was almost impossible to make assumptions about the underlying chemistry behind these results. Especially given the restricted number of inorganic compounds tested and the mass-based catalyst weighting used. Despite this, most of the additives conformed to a similar reactivity grading when premixed and postmixed into DTF devolatilization chars from three different residence times. Mixing the additive and the coal prior to devolatilization was found to be occasionally beneficial, with the postmixed chars’ burnout times producing more erratic reactivity rankings. This emphasized that inferior dispersion or increased loss of catalyst can occur when the char structure is formed prior to additive addition. Nevertheless copper nitrate, copper(I) chloride, and silver chloride were found to be the most successful additives on all but one of the investigated char types. Thus, for most additives, the burnout of catalyst containing TGA chars was thought to be the most conclusive way of comparing compounds; since no extra insight was gained by devolatilising on the DTF and poorer reproducibility was encountered. This unpredictability was due, at least in part, to the innate variability of the underlying DTF char. There was one significant exception to normal additive behavior. Copper(I) chloride substantially deactivated during DTF devolatilization, even though it remained the most successful catalyst on all types of char. This behavior was only moderate and therefore difficult to perceive in the TGA testing environment, but it was clearly evident in the burnout profiles of the chars produced during DTF devolatilisation. The severity of the deactivation was both time and temperature dependent. Hence, when only TGA was used to assess the additives, a prolonged burnout period at over 1000 °C was needed to detect the catalytic inhibitions. This type of temperature was not suitable for ordinary TGA additive testing, however, as combustion was occurring in or close to the mass transfer controlled reaction regime. Deactivation fortunately seemed to be a fairly restricted behavior, possibly limited to just this compound or the copper halides.
Next, a TGA regime study showed that the additives were able to lower the combustion’s apparent activation energy, but there was no association between these additive-induced reductions and the recorded TGA burnout rate improvements. Although the presence of copper(I) chloride did induce a diffusion controlled reaction regime at a lower temperature than otherwise feasible. These TGA results also implied that the physical state of the catalyst might become important during PF combustion. Specifically only a decomposed additive, iron(III) chloride, appeared capable of exerting a catalytic influence under a mass transfer controlled combustion regime. It was consequently postulated that iron(III) chloride’s decomposition permitted its constituents to reassociate themselves with the carbon surface.
’ AUTHOR INFORMATION Corresponding Author
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[email protected]. Phone number: þ44-115-9514166. Fax number: þ44-115-9514115.
’ ACKNOWLEDGMENT The authors are grateful to Innospec Inc. for their financial support of the Ph.D. studentship of K.LeM. ’ REFERENCES (1) Hurt, R. H.; Gibbins, J. R. Fuel 1995, 74 (4), 471–480. (2) Ritscher, J. S. Combustion catalyst and process for using the same. U.S. Patent 4,331,644, May 25, 1982. (3) Backreedy, R. I.; Habib, R.; Jones, J. M.; Pourkashanian, M.; Williams, A. Fuel 1999, 78 (14), 1745–1754. (4) Lu, L.; Kong, C.; Sahajwalla, V.; Harris, D. Fuel 2002, 81 (9), 1215–1225. (5) Beeley, T.; Crelling, J.; Gibbins, J.; Hurt, R.; Lunden, M.; Man, C.; Williamson, J.; Yang, N. Symp. (Int.) Combust. 1996, 26 (2), 3103–3110. (6) Essenhigh, R. H.; Klimesh, H. E.; Fortsch, D. Energy Fuels 1999, 13 (4), 826–831. (7) Smith, I. W. Proc. Combust. Inst. 1982, 19, 1045–1065. (8) Valix, M. G.; Trimm, D. L. Chem. Eng. Sci. 1992, 47 (7), 1607–1617. (9) Pranda, P.; Prandova, K.; Hlavacek, V. Fuel Process. Technol. 1999, 61 (3), 211–221. (10) Li, L.; Tan, Z. C.; Meng, S. H.; Wang, S. D.; Wu, D. Y. J. Therm. Anal. Calorim. 2000, 62 (3), 681–685. (11) Li, X. G.; Ma, B. G.; Xu, L.; Luo, Z. T.; Wang, K. Energy Fuels 2007, 21, 2669–2672. (12) Ma, B.-G.; Li, X. G.; Xu, L.; Wang, K.; Wang, X. G. Thermochim. Acta 2006, 445 (1), 19–22. (13) Xu, D.-Y.; Huang, M.; Wang, Y.-B.; Wu, H. X.; Zhang, B. J. China Univ. Mining Technol. 2006, 16 (2), 216–219. (14) Zhang, L. M.; Tan, Z. C.; Wang, S.-D.; Wu, D. Y. Thermochim. Acta 1997, 299 (1-2), 13–17. (15) Wu, Z.; Xu, L.; Wang, Z.; Zhang, Z. Fuel 1998, 77 (8), 891–893. (16) Murakami, K.; Shirato, H.; Ozaki, J. I.; Nishiyama, Y. Fuel Process. Technol. 1996, 46 (3), 183–194. (17) Gong, X.; Guo, Z.; Wang, Z. Combust. Flame 2010, 157 (2), 351–356. (18) Biswas, S.; Choudhury, N.; Sarkar, P.; Mukherjee, A.; Sahu, S. G.; Boral, P.; Choudhury, A. Fuel Process. Technol. 2006, 87, 191–199. (19) Ulloa, C.; Borrego, A. G.; Helle, S.; Gordon, A. L.; Garcia, X. Fuel 2005, 84 (2-3), 247–257. (20) Yu, J.; Lucas, J. A.; Wall, T. F. Prog. Energy Combust. Sci. 2007, 33 (2), 135–170. 988
dx.doi.org/10.1021/ef101577z |Energy Fuels 2011, 25, 981–989
Energy & Fuels
ARTICLE
(57) Dernaika, B.; Uner, D. Appl. Catal. B: Environ. 2003, 40 (3), 219–229. (58) Quyn, D. M.; Wu, H.; Hayashi, J. I.; Li, C. Z. Fuel 2003, 82 (5), 587–593.
(21) Cloke, M.; Lester, E.; Thompson, A. W. Fuel 2002, 81 (6), 727–735. (22) Le Manquais, K.; Snape, C.; McRobbie, I.; Barker, J.; Pellegrini, V. Energy Fuels 2009, 23, 4269–4277. (23) Biswas, S.; Choudhury, N.; Ghosal, S.; Mitra, T.; Mukherjee, A.; Sahu, S. G.; Kumar, M. Energy Fuels 2007, 21 (6), 3130–3133. (24) Barranco, R.; Cloke, M.; Lester, E. Fuel 2003, 82 (15-17), 1893–1899. (25) Moulijn, J. A.; Kapteijn, F. Carbon 1995, 33 (8), 1155–1165. (26) Quyn, D. M.; Wu, H.; Bhattacharya, S. P.; Li, C. Z. Fuel 2002, 81 (2), 151–158. (27) Lopez-Peinado, A. J.; Rivera-Utrilla, J.; Lopez-Garzon, F. J.; Fernandez-Morales, I.; Moreno-Castilla, C. Fuel 1986, 65 (10), 1419–1422. (28) Buchwald, S. L.; Bolm, C. Angew. Chem. Int. Ed 2009, 48, 5586–5587. (29) Carpenter, A. M.; Skorupska, N. M. Coal Combustion Analysis and Testing, IEACR/64. IEA Coal Res. 1993, 52–67. (30) Varhegyi, G.; Szabo, P.; Jakab, E.; Till, F. Energy Fuels 1996, 10 (6), 1208–1214. (31) Sima-Ella, E.; Yuan, G.; Mays, T. Fuel 2005, 84 (14-15), 1920–1925. (32) Bokova, M. N.; Decarne, C.; Abi-Aad, E.; Pryakhin, A. N.; Lunin, V. V.; Aboukais, A. Thermochim. Acta 2005, 428 (1-2), 165–171. (33) Setzer, C.; Schutz, W.; Schuth, F. Transition Metal Compound Oxide Catalysts for Lowering the Light-Off Temperature of Particles from Diesel Exhaust. 10th International Congress on Catalysis, Budapest, Hungary, 19-24th July 1992, pp 2629-2632. (34) Ciambelli, P.; D’Amore, M.; Palma, V.; Vaccaro, S. Combust. Flame 1994, 99 (2), 413–421. (35) Mul, G.; Kapteijn, F.; Moulijn, J. A. Appl. Catal. B: Environ. 1997, 12 (1), 33–47. (36) Lang, R. J. Fuel 1986, 65, 1324–1329. (37) Cerfontain, M. B.; Kapteijn, F.; Moulijn, J. A. Carbon 1988, 26 (1), 41–48. (38) Mims, C. A.; Pabst, J. K. ASC. Div. Fuel Chem. Prep. 1980, 263–268. (39) Oztas, N. A.; Yurum, Y. Energy Fuels 2000, 14 (4), 820–827. (40) Chen, S. G.; Yang, R. T. Energy Fuels 1997, 11 (2), 421–427. (41) Floess, J. K.; Longwell, J. P.; Sarofim, A. F. Energy Fuels 1988, 2, 756–764. (42) Naredi, P.; Pisupati, S. V. Energy Fuels 2008, 22 (1), 317–320. (43) Senneca, O.; Salatino, P.; Masi, S. Exp. Thermal Fluid Sci. 2004, 28 (7), 735–741. (44) Jelles, S. J.; van Setten, B. A. A. L.; Makkee, M.; Moulijn, J. A. Appl. Catal. B: Environ. 1999, 21 (1), 35–49. (45) Serra, V.; Saracco, G.; Badini, C.; Specchia, V. Appl. Catal. B: Environ. 1997, 11 (3-4), 329–346. (46) Gong, X.; Guo, Z.; Wang, Z. Energy Fuels 2009, 23 (9), 4547–4552. (47) Wang, W.; Thomas, K. M.; Poultney, R. M.; Willmers, R. R. Carbon 1995, 33 (11), 1525–1535. (48) Lee, W. J.; Kim, S. D. Fuel 1995, 74 (9), 1387–1393. (49) K€uhn, L.; Plogmann, H. Fuel 1983, 62 (2), 205–208. (50) Radovic, L. R.; Walker, P. L.; Jenkins, R. G. J. Catal. 1983, 82 (2), 382–394. (51) McKee, D. W. Carbon 1970, 8 (2), 131–9. (52) Patrick, J. W.; Walker, A. Carbon 1974, 12, 507–515. (53) Gale, T. K.; Bartholomew, C. H.; Fletcher, T. H. Energy Fuels 1996, 10, 766–775. (54) Radovic, L. R.; Walker, P. L.; Jenkins, R. G. Fuel 1983, 62 (2), 209–212. (55) Moreno-Castilla, C.; Lopez-Peinado, A.; Rivera-Utrilla, J.; Fernandez-Morales, I.; Lopez-Garzon, F. J. Fuel 1987, 66 (1), 113–118. (56) Pohl, J. H. Influence of Mineral Matter on the Rate of Coal Char Combustion. In Mineral Matter and Ash in Coal; Vorres, K. S., Ed.; American Chemical Society: Washington, DC, 1986; Vol. 301, pp 430436. 989
dx.doi.org/10.1021/ef101577z |Energy Fuels 2011, 25, 981–989
