Apparent kinetics derived from fluidized bed experiments for Norwegian ilmenite as oxygen carrier

Apparent kinetics derived from fluidized bed experiments for Norwegian ilmenite as oxygen carrier

Journal of Environmental Chemical Engineering 2 (2014) 1131–1141 Contents lists available at ScienceDirect Journal of Environmental Chemical Enginee...

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Journal of Environmental Chemical Engineering 2 (2014) 1131–1141

Contents lists available at ScienceDirect

Journal of Environmental Chemical Engineering journal homepage: www.elsevier.com/locate/jece

Apparent kinetics derived from fluidized bed experiments for Norwegian ilmenite as oxygen carrier Georg L. Schwebela , b , * , Sebastian Sundqvistc , Wolfgang Krummb , Henrik Leionc a

Department of Energy and Environment, Chalmers University of Technology, S-412 96 Go ¨teborg, Sweden Institut fu ¨ r Energietechnik, Universita ¨t Siegen, Paul-Bonatz-str. 9-11, D-57068 Siegen, Germany c Department of Environmental Inorganic Chemistry, Chalmers University of Technology, S-412 96 Go ¨teborg, Sweden b

a r t i c l e

i n f o

Article history: Received 16 September 2013 Accepted 15 April 2014 Keywords: Rock ilmenite Chemical-looping Reduction Apparent kinetics Fluidized bed

a b s t r a c t Chemical-looping combustion (CLC) is one of the most promising methods for CO2 -capture. Regarding the use of solid fuels in CLC, it is assumed that the lifetime of the oxygen carrier material will be lowered preferring low cost and environmental sound materials. In this work apparent kinetics for the reduction of a natural rock ilmenite from Norway are derived from experimental data while utilizing CO, H2 and CH4 as fuel gases. CO, H2 and CH4 are the main combustible gases in solid fuel CLC. The experiments were carried out in a laboratory batch fluidized bed reactor. The reactor was heated to bed temperatures varying from 850 to 950 ◦ C. Different fuel gas concentrations were achieved by diluting the fuel flow with nitrogen. For H2 , pulsed reduction experiments have been accomplished to allow the calculation of conversion dependent rates. The experimental conversion rates were fitted to different model approaches in order to derive the apparent kinetic parameters. Thereby the oxygen carrier conversion was represented by the mass based conversion ω. The results are compared to published data. The reaction order with respect to the gas phase is close to the reported values. Only the reaction order obtained for CH4 with the fitted power law deviated with about 40%, what could indicate a limitation of available surface for the heterogeneous decomposition of CH4 . Although the overall agreement between fitted power laws and experimental data was appropriate, their extrapolation outside the experimental data range has to be done with care.  c 2014 Elsevier Ltd. All rights reserved.

Introduction Chemical-looping combustion (CLC) is a promising method to accomplish CO2 capture when converting carbon based fuels [1]. Both economic as well as technical penalties have the potential to be lower than other capture concepts [2]. In general, the denotation “chemical-looping” can be connected to the use of solid oxygen carrier materials, e.g. metal oxides, which provide oxygen through their reduction for the thermochemical conversion of different fuels in the reduction step (Fig. 1). There the net supply of oxygen during reduction may follow different heterogeneous reaction pathways and does not necessarily include gas phase oxygen. For most of the oxygen carrier materials and reaction conditions investigated so far, the reaction pathway does not include gas phase oxygen. In contrast to that, the use of some materials allows the oxygen to be transported via the gas phase under certain conditions, i.e. if the partial pressure of oxygen over the specific oxide is high enough under the reaction conditions. In all cases the reduced oxygen carrier is recharged with oxygen from air in a separate reaction step, i.e. the oxidation. Both the reduction and the oxidation are

* Corresponding author. E-mail address: [email protected] (G.L. Schwebel).

c 2014 Elsevier Ltd. All rights reserved. 2213-3437/$ - see front matter  http://dx.doi.org/10.1016/j.jece.2014.04.013

Fig. 1. General principle of chemical-looping for thermochemical fuel conversion.

connected via a loop of reduced and oxidized oxygen carrier material. To carry out these two steps different reactor concepts are under investigation. In the case of conventional chemical-looping combustion, as of interest in the current publication, the reduction and oxidation are carried out in two separate reactors, the air reactor and the

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fuel reactor, respectively. Both reactors are connected by a circulating stream of solid oxygen carrier. While carrying out the reaction steps in two separate reactors, the off gases never mix. In the air reactor the oxygen carrier is oxidized exothermally by addition of air. The hot excess gas flow from this step can be utilized for power generation. The oxidized oxygen carrier is transferred to the fuel reactor where fuel is added. This principle was proposed in the 1940s [3] to reform methane and it has been patented as an envisaged process for CO2 production from carbonaceous sources [4]. A similar principle was proposed with the goal to lower the irreversibilities of combustion [5,6]. With increasing recognition of the climate change, “chemical-looping-combustion” was investigated to recover CO2 from the exhaust in high concentrations [7,8]. Since then, the capture of CO2 with low energy penalty is the main driving force for the research carried out in that field. There are two main mechanisms of oxygen transfer from the carrier to the fuel. (I) Gas phase oxygen release from the oxygen carrier and subsequent reaction with the fuel, referred to as CLOU (chemicallooping with oxygen uncoupling [9]) or (II) by heterogeneous reaction between reducing gases like CO and the oxygen carrier particles. If solid fuels are applied directly, the second mechanism requires the gasification of the fuel char which is known to be orders of magnitude slower than its combustion [10] under absence of an oxygen carrier. The rate of gasification increases within CLC due to the consumption of H2 known to inhibit the gasification [11]. However, in CLC the char gasification is still the rate limiting step while solid–solid reactions between oxygen carrier and fuel as found in dedicated experiments with copper based particles [12] are expected to be of low practical relevance. Depending on the oxygen carrier and fuel combination, the reduction step can either be endo- or exothermic [13]. A nitrogen free stream of conversion products, i.e. mainly CO2 and H2 O, are released from the fuel reactor. After condensation of the water, almost pure CO2 is ready for further storage. In recent years, the focus of the research has turned to the use of solid fuels. Thereby losses of active material due to possible side reactions of the oxygen carrier and ash as well as due to oxygen carrier material being withdrawn from the reactor with the ash may lead to high expected amounts of oxygen carrier make up [14]. This leads to a demand for abundant, low cost and environmental friendly oxygen carrier materials [15]. Possible materials are natural ores or residues from steel production. Finding promising oxygen carrier materials in extractive or steel industry, also offers the opportunity to insert CLC into the industrial process chain, as proposed, e.g. for hematite or ilmenite in a German patent [16]. Thereby these energy and emission intensive processes could achieve easy CO2 capture by available means. The oxygen carrier investigated in this study is a natural rock ilmenite from Norway. Ilmenite mainly serves as raw material for the pigment industry generating pig iron as by product. Other applications include the production of metallic titanium and to a minor extent the use for refractory maintenance in blast furnaces. A good overview on the production and use of ilmenite ores can be obtained from [17] or [18]. In CLC ilmenite is one of the most investigated oxygen carrier materials with focus on solid fuel application [14,19–32]. A review on the chemical-looping combustion technology can be found in [33,34] or in a more recent work [35]. During modeling, investigation, design and operation of CLC reactor systems, the description of the system requires the time resolved description of the ongoing reactions. The solids inventory per unit fuel power together with the solids circulation rate both presented in [36] are important constituents. The solids inventory is dependent on the integral reaction rate obtained either in the fuel or in the air reactor for chosen process parameters, e.g. temperature, fuel and stoichiometry. The solids circulation rate results from the oxygen carrier conversion achieved in one reactor and is therefore also dependent on a temporal and spatial resolved reaction rate. Thus, a description

of the reaction rate or reactivity of the oxygen carrier in dependence of the temperature and the concentration of reactants is crucial [37]. In general, the reactions for reduction and oxidation of the solid oxygen carrier in chemical-looping combustion are noncatalytic gas– solid reactions in the form of Eq. (1).

ν 1 A g + ν2 B s ↔ ν3 C g + ν4 D s

(1)

Herein ν i is the stoichiometric coefficient of the reactant i, s indicates the reactants in solid state and g indicates the reactants in gaseous state. The main difference to catalytic gas–solid reactions is that the solid particle changes throughout the reaction since it takes part in the reaction [38]. Another straight forward example is the combustion of coal. The conversion rates observed for reactions like this do not only results from the chemical reaction kinetics but also from other rate limiting effects, i.e. inner mass transfer. Since the mass transfer ability is dependent on the solids size, structure and composition, its characteristics change throughout the reaction as the solid reactant is converted. In order to account for the changes within the solid, structural models are used. A review on the different types of models available is found in [39]. During determination of the kinetic parameters from experimental data, the application of structural models helps to determine the effect of the chemical reaction. In CLC research, the application of structural models for kinetic analysis is common. A shrinking unreacted core model was used to interpret the experimental reaction rates obtained from TGA experiments for the oxidation and reduction of NiO/YSZ (yttria-stabilized zirconia) particles [40] and NiO/bentonite particles [41]. In both studies, the oxidation reaction was described including diffusional control. For modeling the reduction of Cu based particles produced by impregnation, a shrinking unreacted core model for plate like geometries with the chemical reaction considered as only resistance was used [42]. The reduction of Norwegian rock ilmenite, like the one used in this study, in a thermo gravimetric analyzer (TGA) was described with a changing grain size model [37]. In [43], the use of empirical models was investigated. A number of sixteen structural models including different resistances have been compared to seven empirical models. The authors fitted all models to the same experimental data taken from the literature. Although the performance of the empirical models was said to be good, the authors state that the use is limited to the area covered by the experimental data, since their structure is made from polynomial and exponential functions. Thus, the presented concept appears interesting since the models are highly flexible. In the present work reactivity data are gained from laboratory batch fluidized bed experiments. Previously, the solids inventory was derived from a general normalized rate calculated from experimental data obtained at one temperature and one inlet concentration [44]. Therefore, a first order reaction with respect to the fuel gas and negligible resistance between bubble and emulsion phase was assumed. The results obtained give good indications of the performance of different oxygen carriers, and account for the incomplete gas conversion found in the experiments. The validity of this description can be extended if data for different temperatures as well as for different gas concentrations would be included. Furthermore the influence of the solids conversion is not accounted for. Hence, the effective rate constant was found to vary with the conversion of the oxygen carrier [44]. This work aims at a description of the reduction rate depending on the oxygen carrier conversion, reactant gas concentration and temperature. CO, CH4 and H2 have been applied as fuel gases for the reduction of activated Norwegian ilmenite. The operational parameters are chosen close to those used in experiments for the characterization of oxygen carrier particles, i.e. high fuel gas concentration combined with low reduction times [25,32]. The apparent kinetic data were obtained by fitting the equation parameters to experimental values

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using a linear least squares method. Different approaches are used to derive apparent kinetic parameters from the experimental data. For the ilmenite tested in the current contribution already a thoroughly conducted kinetic study is available from the literature [37] giving the chance for a comparison with the apparent kinetic parameters from the actual study. Therefore, the experimental data is also fitted to the changing grain size model. Experimental Oxygen carrier used In this work a concentrate from a rock ilmenite mineral from Norway is used as oxygen carrier. The same material has already been the subject of numerous investigations related to chemical-looping, e.g. [14,19–32,37,45]. With ilmenite, the fuel conversion increases during the first reduction oxidation cycles, and so does the apparent reaction rate. This behavior is known as activation and has been reported in the literature not only for Norwegian rock ilmenite [19,23] but also for other natural occurring ilmenites [32]. Hence, in order to get stable conversion the ilmenite has to be activated before the experiment. The activation of the sample used here is carried out conducting five reduction oxidation cycles at 850 ◦ C followed by a number of cycles at 950 ◦ C until stable performance is reached. Syngas (50 vol.% H2 in CO) was the fuel for all cycles during the activation. The results from the activation of the sample being the basis for this work can be found in [32]. XRD analysis on the fresh particles used in the current study indicated ilmenite (FeTiO3 ) and hematite (Fe2 O3 ) as the main phases. During oxidation above 800 ◦ C, ilmenite (FeTiO3 ) is converted to pseudobrookite (Fe2 TiO5 ) and additional rutile (TiO2 ) [46] according to Eq. (2). 2 F eT i O 3 + 1/2 O2 ↔ F e2 T i O5 + T i O2

(2)

This corresponds to a transition from FeII oxide to FeIII oxide. During reduction the pseudobrookite is converted back towards the ilmenite state, whereas the oxygen is not released in the gas phase and has to be consumed by a fuel gas. However, after several oxidation reduction cycles particles with an iron oxide rich shell were found [20,25] indicating that the iron separates from the titanium, and that Eq. (2) is not totally reversible. Similar results were observed during the reduction of ilmenite by Zhao et al. [47] and den Hoed and Luckos [48] also discussed that tendency based on phase equilibria calculations and experimental findings. Hallberg et al. [28] investigated the heat of reaction for the same natural ilmenite used in the current study. They obtained a value of 469 kJ/mol O2 laying between the heat of reaction of ilmenite oxidation to pseudobrookite together with rutile and oxidation of magnetite (Fe3 O4 ) to hematite (Fe2 O3 ), being 445 kJ/mol O2 and 480 kJ/mol O2 , respectively both values obtained from the literature [28]. The authors concluded that this finding could also be assigned to a possible phase separation. Here it is worth noting, that the natural ilmenite used contains already free iron oxides from the beginning. However, no signs of phase separation have been observed during experiments with coal, where the extent of reduction achieved within one cycle was limited [30]. The reduced particles after the activation in this study incorporated ilmenite, rutile and pseudobrookite. One advantage of the Fe−Ti−O system compared to the Fe−O system is the better thermodynamics. For iron oxides only the transition from Fe2 O3 (FeIII ) to magnetite (Fe3 O4 , FeII,III ) gives full conversion ¨ of CH4 to H2 O and CO2 . The transition from Fe3 O4 to the wustite state (FeO, FeII ) allows approximately 65% of the carbon to be converted into CO2 at about 900 ◦ C. The transition from pseudobrookite

Fig. 2. Experimental set-up.

to ilmenite allows almost complete fuel conversion considering the chemical equilibrium [20]. Hence the amount of oxygen available for full fuel conversion is higher in ilmenite than in pure iron oxides. A characteristic value is the oxygen transport capacity or oxygen ratio R0 (Eq. (3)). R0 =

mox − mred mox

(3)

Here mox denotes the mass of the completely oxidized and mred the mass of the completely reduced oxygen carrier. R0 is dependent on the oxygen carrier material and the assumed conversion. Experimentally Leion et al. [19] could achieve values close to 0.05 using the same carrier material as in the present work. A somewhat lower ´ value, i.e. 0.048 is presented Adanez et al. [23] who also investigate Norwegian ilmenite. For activated Norwegian ilmenite the oxygen ratio is reported to be 0.033 [37]. Taking a raw Canadian rock ilmenite with 20 wt% inert impurities as basis, a R0 value of 0.04 was given [21]. Compared to the pure iron oxide system, ilmenite gives a less endothermic overall reduction in the fuel reactor [19]. This leads to a lower circulation flow of oxygen carrier required for providing this heat. Laboratory equipment and experimental procedure All experiments were carried out in a batch fluidized bed quartz glass reactor with an inner diameter of 22 mm and an overall length of 870 mm (Fig. 2). A porous quartz plate in the reactor is used as gas distributor. The temperature is measured by CrAl/NiAl thermocouples located below the distributor and in the bed. The fluidizing gas enters the reactor from the bottom. The gas composition is controlled by mass flow regulators and magnetic valves. The water content in the off gas is condensed in a cooler before the concentrations of CO, CO2 , CH4 , H2 and O2 are measured online downstream in a gas analyzer (Rosemount NGA 2000). The oxygen carrier sample is mixed with quartz sand and placed on the distributor plate at ambient temperature. The reactor is heated up by an external electric furnace to the desired target temperature. During oxidation a gas consisting of 10 vol.% O2 diluted with nitrogen (N2 ) is fed into the reactor. This low oxygen concentration is chosen in order to prevent an excessive increase of the temperature during the exothermic oxidation. At the same time 10 vol.-% is enough to oxidize the carrier within reasonable time scales. Since the experiments are conducted in a semi batch wise manner, the oxidation and reduction steps are separated by inert periods where only N2 is fed into the system for 180 s. With all investigated fuel gases, that is H2 , CO or CH4 , continuous reduction periods of 18 s have been accomplished. Additionally, one experimental campaign using H2 was carried out, where

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the fuel gas was inserted in four distinct pulses of 2 s each during one reduction period. This gives the opportunity to discretize the reduction interval in order to investigate the rate evolution with respect to the oxygen carrier conversion. An overview on all experimental parameters conducted is given in Table 1. During the experiments the temperature is varied from 850 over 900–950 ◦ C. Three different inlet fuel gas compositions were used for every sample. In the continuous reduction experiments 6 g of oxygen carrier was reduced by 50, 75 and 100 vol.% fuel gas mixed with nitrogen. For the pulsed reduction experiments, the fuel gas consisted of 6.25, 9.4 and 12.5 vol.% hydrogen in nitrogen. Hence the amount of fuel flow per unit oxygen carrier mass was increased to overcome the outer transport limitation. The experiments for every case with different fuel gas composition or temperature combination was repeated at least twice. In order to characterize the fluidization, the minimum fluidization velocities for the various gases have been calculated using Eq. (4), taken from [49].   1 − mf · νg umf = 42.9 · · ϕS · dp ⎛ ⎞  3 ·g· ϕ ·d 3· ρ −ρ  3.1 × 10−4 · mf ( S p) ( P g) ⎜ ⎟ − 1⎠ (4) ⎝ 1 +  2 2 1 − mf · νg · ρg A particle density of ρ P = 4200 kg/m3 is considered for ilmenite and ρ P = 2300 kg/m3 for sand. According to [50] the sphericity of a heat treated Canadian rock ilmenite is ϕ S = 0.799 for particles sieved to 125–180 μ m. The ilmenite investigated here is a rock ilmenite concentrate. Hence it appears appropriate to choose the same sphericity, 0.799, which was also used for sand. The voidage at minimum fluidization was chosen to ε mf = 0.45. From the calculation the lowest fluidization number u/umf was 5.18 for 100 vol.% H2 at 850 ◦ C for 180 μ m ilmenite. At 950 ◦ C the highest u/umf ratio was obtained for 50 vol.% CH4 in N2 for 125 μ m ilmenite with a value of 16.59. It has to be noted, that a large portion of the bed consist of quartz sand which therefore dominates the fluidization. Sand shows higher fluidization numbers due to its lower density. Optically, no differences in fluidization could be detected between the studied cases. Data evaluation Experimental reduction rates The mass based conversion of the oxygen carrier ω is calculated from the actual mass m and the oxidized mass mox , according to Eq. (5).

ω=

m mox

(5)

The oxygen carrier mass in its oxidized state mox was assumed to be equal to the raw mass of activated oxygen carrier. The experimental reduction rate with respect to ω is calculated from the experimental data using CO as fuel according to Eq. (6).

 MO dω · n˙ C O 2 ,out (t) r ω (t ) = = (6) dt mox MO is the molar mass of oxygen and n˙ C O 2 ,out denotes the outgoing molar flow of CO2 . In the case of H2 as fuel, the time dependent reduction rate cannot be obtained since the actual flow of H2 O is not measured. Therefore the rate is calculated using the total hydrogen balance and the reduction time (Eq. (7)). rω =

(mox · (t1 − t0)) ·



MO   t1 t1 t0 n˙ H 2 ,in (t) dt − t0 n˙ H 2 ,out (t) dt

(7)

Fig. 3. Reduction rate rω as a function of the mass based conversion ω (a) at 850, 900 and 950 ◦ C using 75 vol.% CO as fuel and (b) at 950 ◦ C using 50, 75 and 100 vol.% CO as fuel.

t1−t0 is the time interval of the reduction phase and for a single pulse in the continuous reduction and the pulsed reduction, respectively. n˙ H 2 ,in and n˙ H 2 ,out denote the ingoing and outgoing molar flows of H2 . In the case of CH4 for the calculation of the reduction rate also the actual hydrogen value is required. Due to malfunction of the cross interference correction of the hydrogen measurement, the actual hydrogen value was calculated, assuming that the water gas shift reaction is in equilibrium. Therefore the reduction rate results from Eq. 8. MO r ω (t ) = · mox ⎞ ⎛ 3 · n˙ C O ,out (t) + 4 · n˙ C O2 ,out (t)   ⎜ ⎟

 ⎜ n˙ C O,out (t) 4577.8 ⎟ ⎝ −2 · n˙ ⎠ + 1 · exp −4.33 + C O ,out (t) · n˙ C O2 ,out (t) T

(8)

According to Moe [51] (cited in [52]) the equilibrium constant of the water gas shift reaction is represented by Eq. (9).

 4577.8 K = exp −4.33 + (9) T

Results and discussion Experimental reduction rates From the experiments carried out according to the description in section `Laboratory equipment and experimental procedure” the experimental rates with respect to ω during reduction have been calculated. In Fig. 3 the reduction rates obtained while using CO as fuel are presented. In Fig. 3(a), the influence of the reactor temperature is indicated through the rates resulting from the experiments with 75 vol.-% CO at 850 ◦ C, 900 ◦ C and 950 ◦ C, respectively. It is evident that the rate increases with increasing temperature. Also, it is obvious that an increase in temperature from 850 to 900 ◦ C leads to a lower rate improvement compared to rising the temperature from 900 to 950 ◦ C. In addition Fig. 3(b) shows the experimental rates obtained from varying inlet gas compositions at 950 ◦ C. Increasing inlet concentrations act positive on the acquired reduction rate. It can be seen that qualitatively the inlet fuel gas concentration correlates to the rate. Similar results were obtained from the experiments with varying gas composition at 850 ◦ C and 900 ◦ C. Fig. 4(a) shows the experimental reduction rates obtained at three different temperatures with 75 vol.% CH4 in the gas sent to the reactor. The general trend of the rates is comparable to what is observed for CO hence increased temperatures lead to increased rates. In contrast to the experiments with CO, a change of the temperature from 850 to 900 ◦ C resulted in a higher rate increase than the change from 900 to 950 ◦ C. During the reduction of iron ore with methane, the maximum rate is said to be limited at temperatures above 830 ◦ C due to decreasing reaction surface for methane decomposition by the formation of metallic iron [53]. This effect could play also a role for the use of the ilmenite in this study since it might contain free

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Table 1 Experimental parameters. Gas comp.

a. 50 vol.% in N2 , 75 vol.% in N2 and 100 vol.%. b. 6.25 vol.% in N2 , 9.4 vol.% in N2 and 12.5 vol.% in N2

Bed comp.

Fuel gas CO

H2

CH4

6 g ilmenite in 9 g sand 0.5 g ilmenite in 0.75 g sand

CR, a) −

CR, a) PR, b)

CR, a) −

CR: continuous reduction (18 s); PR: pulsed reduction (4 × 2 s).

Fig. 4. Reduction rate rω as a function of the mass based conversion ω (a) at 850, 900 and 950 ◦ C using 75 vol.% CH4 as fuel and (b) at 950 ◦ C using 50, 75 and 100 vol.% CH4 as fuel.

Fig. 5. Reduction rate rω as a function of the mass based conversion ω (a) at 850, 900 and 950 ◦ C using 75 vol.% H2 as fuel and (b) at 950 ◦ C using 50, 75 and 100 vol.% H2 as fuel obtained from the continuous reduction experiments.

iron oxide. The rates from the experiments conducted at 950 ◦ C with different fuel gas compositions are presented in Fig. 4b). An increase of the calculated rates with increasing inlet fuel gas concentration is evident. The highest rate is observed at 950 ◦ C with 100 vol.% CH4 . The actual values are about 10% lower than the rate values obtained under the same conditions with CO. In the stable area, the rates observed are increasing with decreasing ω values. In the case of H2 only one rate value is obtained for the entire reduction phase according to Eq. (7). This value is assumed to be valid throughout the reduction period; hence the rate does not change with changing ω values (Fig. 5). The maximum rates observed for H2 are almost twice that high than the ones seen for CO and CH4 at 950 ◦ C and 100 vol.% fuel. Therefore the oxygen carrier particles are also more reduced during the reduction with hydrogen. However, it is obvious from Fig. 5a, that the influence of temperature for the investigated cases with hydrogen appears to be negligible. In contrast, the gas phase fuel composition has major influence (Fig. 5b). This indicates that the rates achieved for the reduction with hydrogen are dependent on the hydrogen flow provided during reduction. The aim of the experiments was to derive data for the calculation of apparent kinetics in dependence not only of the gas composition but also of the mass based conversion and the temperature. It is not possible to resolve the dependence of the reduction rate on the mass based conversion with the first adapted approach. In order to improve the data basis for hydrogen, pulsed reduction experiments have been carried out aiming at a discretization of the reduction period with

Fig. 6. H2 vol.% curve indicating the pattern of a pulsed reduction with 12.5 vol.% H2 in N2 .

hydrogen. The oxygen carrier mass was lowered to 0.5 g in sand in order to lower the total amount of hydrogen consumed in the reactor to exclude a limitation of the reaction from fuel supply. To achieve a comparable range obtained for the oxygen carrier conversion, also the gas phase concentration of the fuel was lowered. The H2 curve during a cycle with a pulsed reduction is given in Fig. 6. In Fig. 7 the rates calculated after Eq. (7) for the pulsed reduction periods are illustrated. Hereby one rate value is obtained for every single reduction pulse. The level of the rates obtained from pulses of 9.4 vol.% H2 in N2 increases with raising temperatures as evident from Fig. 7a. This behavior confirms improvement of the data base by lowering the mass of the active oxygen carrier. The rates obtained for different fuel gas inlet compositions at a reactor temperature of 950 ◦ C are presented in Fig. 7b. As expected, the influence of the fuel gas composition stays evident. Increasing the H2 inlet fractions raise the rates obtained. The absolute numbers for the rates from the pulsed reduction experiments are at the same level as for the continuous experiments where the rate was obviously limited. Thus, the conversion in ω achieved throughout one reduction sequence is comparable to the previous H2 experiments. This effect is due to the lower gas phase concentration of H2 during the pulsed reduction experiments.

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T is the mean temperature in the bed during the corresponding reduction period in K. For CH4 as reductant the concentration of H2 O in the exit of the bed is calculated from a balance assuming the water gas shift reaction to be in equilibrium. The task is to obtain the unknown coefficients in Eqs. (11) and (12) by fitting the parameters to the experimental data. After including Eq. (12) into Eq. (11) and taking the logarithm of the result we obtain a linear function with respect to the parameters (Eq. (13)).   EA ln (rω ) = ln (k0 ) − + w · ln (ω) + n · ln C g (13) R· T Fig. 7. Reduction rate rω as a function of the mass based conversion ω (a) at 850, 900 and 950 ◦ C using 75 vol.% H2 as fuel and (b) at 950 ◦ C using 50, 75 and 100 vol.% H2 as fuel obtained from the pulsed reduction experiments.

Kinetic modeling of apparent kinetic parameters In order to derive a basic design for a chemical reactor, the rate has to be expressed as function of temperature, gas phase concentration C g and oxygen carrier conversion ω. According to a general phenomenological expression, the rate is written in the following form (adapted from Hossain et al. [54]) (Eq. 10).   r ω = f ( T ) · f (ω ) · f C g (10) This expression means that the rate obtained can be expressed as the product of functions being dependent on the temperature f(T), the oxygen carrier conversion f(ω), and the concentration of the gas phase reactant f (C g ), respectively. But it is important to point out that the experimental reaction rates in this work are only apparent rates. As shown above, for the experiments with CO, CH4 and with pulses of H2 , dependencies of temperature, fuel gas composition and oxygen carrier conversion are evident. However, it is not ensured that the rates are only limited by chemical reaction. The transient areas in the beginning and the end of the reduction periods seen for CO and CH4 are most likely due to back mixing mechanisms in the system and are therefore not used. This does not apply for the rates obtained from the H2 fueled experiments because the transient areas cannot be resolved from the calculated rates. Hence, the experimental rates for H2 are conservative. Considering f(T) to be the apparent rate constant k and applying a simple power law to represent the influence of ω and C g , Eq. (10) can be rewritten to result in Eq. (11). rω = k · ω

w

· C gn

(11)

This formulation incorporates the so called apparent kinetic parameters, namely k, w and n. It is assumed that the influence of the oxygen carrier conversion ω can be included in the same way as the effect of the fuel gas concentration C g . Hence, w and n are the exponents related to the actual oxygen carrier conversion and fuel gas concentration respectively. n and w are referred to as reaction order. k includes the temperature dependence and is calculated by an Arrhenius expression (Eq. 12).

 −E A (12) k = k0 · exp R· T k0 is the frequency factor and EA the activation energy.  is the universal gas constant (8.314472 J/(mol K)) and T the absolute temperature. The fuel gas concentration in mol/m3 is calculated is calculated taking into account the mean temperature in the bed and the average molar fraction of the fuel in the gas obtained as the mean value between the molar fractions at the inlet and outlet. The particles are considered to be well mixed throughout the fluidized bed. The mean value is therefore assumed to be a good representation of the gas composition relevant for the particle conversion.

The parameters ln(k0 ), EA , w and n are calculated using the experimental data points as input for a linear least squares fit. To account for a possible temperature dependence of the exponent w, Eq. (11) is rewritten including a linear temperature function instead of the exponent w given by Eq. (14). rω = k · ωm·T +b · C gn

(14)

The linear function used as basis for the data fitting is then given by Eq. (15). ln (rω ) = ln (k0 ) −

EA R· T

  +m · T · ln (ω) + b · ln (ω) + n · ln C g

(15)

Here m is the slope and b the intercept of the linear function representing the reaction order n in dependence of the temperature. In the same way, it is also possible to make the reaction order n dependent on the temperature. Thus, Eq. (11) is rewritten including a linear temperature function instead of n. rω = k · ωw · C gm·T +b

(16)

The linear function used as basis for the data fitting is then given by Eq. (17). EA R· T     +w · ln (ω) + m · T · ln C g + b · ln C g ln (rω ) = ln (k0 ) −

(17)

Again m is the slope and b the intercept of the linear function representing the reaction order n in dependence of the temperature. The linear temperature function in the exponents of Eqs. (14) and (16) are included to make the function more flexible towards changes of the exponents with temperature while keeping the linear character of the equation to be fitted. Also the parameters of Eqs. (15) and (17) are obtained by the linear least squares method. In addition to the presented approaches the experimental data is also included in the changing grain size model as used for the same material by [37]. The model equations are given in Eqs. (18) and (19). t

τ

= 1 − (1 − X )1/3

(18)

With τ being the time for complete conversion of the solid is

τ=

ρm · rg

(19)

b · k · C gn

Therein ρ m is the molar density, b is the stoichiometric ratio and rg is the radius of the grain. The values for these parameters have been taken from Abad et al. [37] for reasons of consistency. In the context of the experimental results obtained, the formulation for the changing grain size model is adopted. rω =

2/3

R 0 · 3 · (1 − (1 − ω ) / R 0 ) ρm · rg

·b

· k · C gn

(20)

G.L. Schwebel et al. / Journal of Environmental Chemical Engineering 2 (2014) 1131–1141

Fig. 8. Calculated and experimental rates rω as a function of the mass based conversion ω found for the reduction with CO at (a) 850 ◦ C, (b) 900 ◦ C and (c) 950 ◦ C.

Fig. 9. Calculated and experimental rates rω as a function of the mass based conversion ω found for the reduction with H2 at (a) 850 ◦ C, (b) 900 ◦ C and (c) 950 ◦ C.

Fig. 10. Calculated and experimental rates rω as a function of the mass based conversion ω found for the reduction with CH4 at (a) 850 ◦ C, (b) 900 ◦ C and (c) 950 ◦ C.

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Therein R0 is chosen to be 0.033 being the value for activated ilmenite given in Abad et al. [37]. The apparent kinetic parameters as well as the reaction order with respect to the fuel gas concentration are obtained from a linear least squares fit after including the Arrhenius expression and taking the logarithm. Parameters from least squares fit In Table 2 the results from the data fitting are summarized. Furthermore, the kinetic data from the study [37] performed with the same Norwegian ilmenite in its activated state are listed, giving the best possibilities for general comparison. Only the activation energies and the reaction orders with respect to the gas allow a comparison. The values calculated for the pre-exponential factor change with the general shape of the model equation used. In [37] there is no reaction order with respect to the oxygen carrier conversion included since the authors used a structural model to represent the conversion of the oxygen carrier. For CO, the obtained reaction orders with respect to the gas concentration as well as the activation energies are in good agreement with the values presented by Abad et al. [37] for all four expressions considered in this work. For CH4 the exponent n is about 40% lower and the activation energies are roughly 10–35% higher than the literature values. This may be connected to the influence of the heterogeneous decomposition of CH4 . The heterogeneous decomposition has been proven to play an important role in the reaction with a rock ilmenite [55]. A low value for n indicates a low influence of the methane concentration. This would stimulate the assumption, that the decomposition as intermediate step is the limiting factor, as confirmed for the reduction of iron ore in fixed and fluidized bed experiments with methane [53]. The time consuming step could be the surface reaction itself, e.g. due to limited reaction surface or the gasification of carbon formed to CO. The differences found between the kinetic parameters for CH4 resulting from the current study and the literature values by Abad et al. [37] lead to the assumption that the time consuming steps are stressed differently in the TGA compared to the laboratory scale fluidized bed. The low activation energies obtained for the continuous reduction experiments with H2 confirm a possible influence of transport phenomena for H2 in the used set up. It is assumed that diffusion processes are negligible in the experimental system. Hence, it is likely that the conversion is limited by the H2 flow into the reactor. In contrast to that, the fit of the data stemming from the pulsed reduction experiments with H2 leads to up to 33% higher activation energies than given in Abad et al. [37] with respect to Eq. (11). However, Eq. (14) is in the same range as the literature value. The high values indicate, that the transport problems during the continuous reduction with H2 could be solved with a lower mass of active carrier. Only the pulsed reduction experiments with H2 will be used for further evaluation in this paper. In general the apparent kinetic data derived with the power law expressions appear to be appropriate in comparison with the values obtained with the grain size model applied in the current study as well as in the literature. With respect to the reaction order w, it is obvious that the influence of the oxygen carrier conversion decreases from H2 over CO towards CH4 . Comparison of calculated and experimental rates Mean root square relative error The quality of the overall fit is justified calculating a mean root square relative error according to Eq. (21).  2 0 . 5 z 1 (rω,exp,i − rω,calc,i ) E rr = (21) z rω,exp,i i=1

This corresponds to the mean value of the root quadratic difference between the experimental rate rω,exp,i and the calculated rate rω,calc,i using either Eqs. (11), (14), (16) or (20) with the corresponding parameters, normalized to the experimental rate rω,exp,i . The resulting errors are listed for relevant model equations and reducing gases in Table 3. The sum of the mean errors for one of the three model equations considering all gases gives an indication of the performance of the single equation to represent all data. The lower the sum, the better is the overall representation. The sum of the mean errors obtained with the expression in Eq. (14) including a temperature dependent reaction order with respect to the oxygen carrier conversion is the lowest with 0.12, compared to 0.269 and 0.304 obtained with the expressions in Eq. (16) and Eq. (11), respectively. Also the grain size model (Eq. (20)) yields a low error sum of 0.168. Thus, the linear function in temperature for the exponent w leads to an improved representation of the experimental data. The mean errors calculated with the rates from Eq. (14) also result in the lowest values among the errors found for each single gas. From this, Eq. (14) appears as the equation to prefer among the power law approaches, although, e.g. the activation energies found with Eq. (11) for CO and CH4 match better with literature values. The errors calculated for CH4 as reducing gas represent the largest differences among the equations used. For the pulsed reduction with H2 the relatively high error obtained even using Eq. (14) can be attributed to the step like appearance of the experimental data resulting from the integral calculation procedure. In the end, based on the mean root square error, Eq. (14) is selected as the best alternative. At this stage it has to be noted that the calculated error only allows a comparison in the area covered by the experimental data, 850–950 ◦ C, moderate change in the oxygen carrier conversion and the chosen fuel concentrations. A more general view on the results obtained for each gaseous fuel is given in the next section. CO as fuel gas Fig. 8 shows the experimental rates from the reductions with CO and the corresponding calculated rates as a function of the oxygen carrier conversion. The data for different reactor temperatures, i.e. 850, 900 and 950 ◦ C can be found in Fig. 8a-c, respectively. The single plots of the rates calculated from the experimental data (filled markers) are indicated by the mean value of the actual temperature as well as by the mean value of the actual mean concentration calculated according to Eq. (13). The same mean temperatures and concentrations have been used as parameters in the model equations giving Eqs. (11)-(20). The levels of the experimental rates are qualitatively represented by all models confirming the low errors found. Thereby the rates predicted with the fitted equations generally tend to underestimate the experimental rates making the calculated rates conservative. The only exception is seen at 900 ◦ C for a calculated mean concentration value of 3.9892 mol/m3 . Comparing the plots obtained from the different model equations, the lines for Eqs. (11) and (16) are almost parallel to the x-axis. In contrast to that, the line obtained from Eq. (14) changes its slope drastically with varying temperature to result in a better prediction of the trend of the experimental data especially at lower temperatures. Thus, Eq. (14) is able to represent the downward trend of the rates with decreasing ω values at 850 ◦ C and 900 ◦ C whereas at 950 ◦ C Eq. (14) tends towards increasing rates with decreasing ω while the data is decreasing. However, in Fig. 8c, the rates predicted at lower oxygen carrier conversions tend to be over predicted. Hence, although low error values are achieved due to the flexibility of the power law models (Eqs. (11), (14) and (16)) the use of the equations outside the range of the experimental data has to be done with care. The rates calculated with Eq. (20) always tend to decrease with increasing oxygen carrier conversion. Since Eq. (20) is less flexible its application is justified outside the area where experimental data are available.

G.L. Schwebel et al. / Journal of Environmental Chemical Engineering 2 (2014) 1131–1141

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Table 2 Results from data fitting for CO, CH4 and H2 and the corresponding values obtained from [37].

Eq. (11)

Eq. (14)

Eq. (16)

Grain size model this study Eq. (20)

CO n w k0 EA in kJ/mol

0.74 0.22 0.83 84.25

0.75 −0.238 × T + 282.836 0.23 71.59

−2.709E−04 × T + 1.063 0.10 1.40 89.35

0.83 − 0.14 95.19

0.80 − 0.10 80.7 ± 2.4

CH4 n w k0 EA in kJ/mol

0.57 –17.82 476.84 146.90

0.56 1.072 × T − 1.303E + 03 27,563.78 186.75

−1.647E−03 × T + 2.501 –19.41 13,452.56 179.51

0.68 − 388.93 172.96

1.00

H2 cont. n w k0 EA in kJ/mol

1.15 0.02 0.00 17.52

1.15 −4.640E−04 × T + 0.567 0.00 17.46

6.543E−05 × T + 1.078 0.02 0.00 16.02

1.95 − 0.00 30.80

Pulsed H2 n w k0 EA in kJ/mol

0.93 43.68 6.61 87.56

0.96 −0.274 × T + 369.455 1.00 69.09

0.958 × T − 0.764 43.63 4.85 84.49

0.83 − 0.14 79.27

Table 3 Mean errors calculated according to Eq. (19) and their sum for the different model equations.

Eq. (11) Eq. (14) Eq. (16) Eq. (20)

CO

CH4

H2 (pulsed)

Σ

0.026 0.022 0.026 0.030

0.177 0.036 0.149 0.058

0.101 0.062 0.094 0.080

0.304 0.12 0.269 0.168

H2 as fuel gas For H2 as fuel only the data obtained from the pulsed reduction experiments are plotted together with the corresponding calculated values. In Fig. 9 the experimental rates from the pulsed reductions with H2 (filled markers) and the corresponding calculated rates both as a function of ω at different temperatures are presented. The results from the model equations in Fig. 9 follow the same trend. The representation of the experimental data at all temperatures is straight forward. At 850 ◦ C (Fig. 9a) all models tend to underestimate the data resulting in conservative values obtained from the equations, especially at high values for ω. The grain size model represented by Eq. (20) delivers the lowest rates in that area. As evident from Fig. 9c except from the rates calculated with Eq. (20) the experimental data is always overestimated in the beginning of the conversion at 950 ◦ C. It has to be noted, that the transient areas could not be removed from the experimental data, leading to, that the actual rates found in the beginning of a reduction are higher than expected from the experimental data presented here. CH4 as fuel gas Fig. 10 shows the experimental rates from the reductions with CH4 (filled markers) and the corresponding calculated rates both as a function of ω. Fig. 10 represents the data for the different temperatures investigated. In general, the rate levels are qualitatively represented by all model equations in the investigated ω area. However, at 900 ◦ C the experimental data is underestimated, especially by the rates calculated with Eqs. (11), (16) and (20). The data calculated for a mean concentration

Grain size model [37]

9.80 135.2 ± 6.6

1.00 0.06 65.0 ± 2.7

of 8.2259 mol/m3 with Eqs. (11) and (16) corresponds to the experimental data for a calculated mean concentration of 5.9733 mol/ m3 . The rates calculated based on Eq. (14) can better adapt to the experimental data at 850 ◦ C and 900 ◦ C. However, the calculated rates increase with a steep slope with decreasing ω values leading to overestimated rates outside the range where experimental data is existent. As evident from Fig. 10c, Eqs. (11), (16) and (20) lead to highly overestimated rates already for medium ω values at 950 ◦ C. Conclusions In the present study fluidized bed experiments have been performed to obtain reactivity data for the oxygen carrier reduction. An activated concentrate from a natural rock ilmenite has been used as oxygen carrier for chemical-looping combustion of CO, CH4 and H2 . Both temperature and fuel gas inlet concentration have been varied leading also to variations of the oxygen carrier conversion. In order to gain sufficient data from the experiments with H2 , pulsed reductions with low oxygen carrier mass were conducted. The experimental conversion rates were fitted to different modified power law models as well as to the changing grain size model in order to derive the apparent kinetic parameters. Thereby the oxygen carrier conversion was represented by the mass based conversion ω. A comparison with published parameters reported for the same material obtained from experiments in a TGA apparatus was performed. The activation energies obtained from the fitted power law expressions tended to higher values than the literature values. The reaction orders for the different fuels are close to the reported literature values. Only the reaction order obtained for CH4 with the fitted power law is about 40% lower. This likely indicates a limitation of available surface for the heterogeneous decomposition of CH4 . The activation energies as well as the reaction orders with respect to the mean fuel gas concentration obtained from the experimental data in this study appear to be in the same order of magnitude independent of the model used. Comparing the experimental and calculated rates for the fuel gases investigated, a power law equation with a temperature dependent reaction order regarding the oxygen carrier conversion (Eq. (14)) gives the lowest errors in the observed parameter area.

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