Spray roasting of iron chloride FeCl2: laboratory scale experiments and a model for numerical simulation

Powder Technology 228 (2012) 301–308

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Spray roasting of iron chloride FeCl2: laboratory scale experiments and a model for numerical simulation Martin Schiemann a,⁎, Siegmar Wirtz a, Viktor Scherer a, Frank Bärhold b a b

Department of Energy Plant Technology (LEAT), Ruhr-University of Bochum, Germany Andritz AG, Vienna, Austria

a r t i c l e

i n f o

Article history: Received 9 January 2012 Received in revised form 17 April 2012 Accepted 12 May 2012 Available online 18 May 2012 Keywords: Iron Oxide Particle formation Modelling Spray roasting

a b s t r a c t Iron chloride solutions are a waste product in steel pickling plants. A technique to recover the spent solutions is the so-called spray roasting process, where the spent solution is sprayed into a hot reaction atmosphere and solid iron oxide particles are formed. The particle formation in spray roasting reactors has important influence on the efficiency of the recovery process and on the quality of the desired by-product Fe2O3. A laboratory reactor was designed to investigate the particle formation. Experiments were carried out covering the predominant conditions in spray roasting reactors. The results offer valuable insight into the particle formation process, providing data on the surface structure of the Fe2O3 particles formed and on the progress of chemical conversion. Based on these results, a simplified model applicable to CFD-modelling of spray roasting reactors has been developed. Simulations of particle trajectories in the laboratory reactor are presented to show the capabilities of the model. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Hydrochloric acid has been well established as pickling liquor for hot steel surfaces for more than 60 years. During the pickling process, iron chloride (FeCl2) is formed from hydrogen chloride reacting with iron oxides. This enrichment leads to a reduced pickling speed. After having reached a critical concentration of FeCl2, the spent pickling liquor has to be recovered. An established technology of recovery is the so-called Ruthner-type spray roasting reactor [1]. The heat for the roasting process is typically provided by natural gas fired burners which are located inside the Ruthner reactor. The liquid saturated with FeCl2 is injected into the reactor to undergo a thermal decomposition process leading to HCl, which is returned into the pickling process, and Fe2O3 (hematite) particles, which are a desirable by-product useful in different industrial processes like ferrite or pigment production [2]. The thermal decomposition process is described by the overall chemical reaction 4FeCl2 þ 4H2 O þ O2 →2Fe2 O3 þ 8HCl−55; 0 kJ=mol:

ð1Þ

The aqueous FeCl2-solution injected into the reactor contains roughly 70 w-% of water. The conversion of droplets to solid particles is affected by many factors like gas temperature, concentration of participating gas species and the flow field in the reactor. The complex gas phase conditions in Ruthner-type reactors make it difficult to ⁎ Corresponding author at: Ruhr-Universität Bochum, Universitätsstraße 150, 44801 Bochum. Tel.: + 49 234 32 27362; fax: + 49 234 32 14227. E-mail address: [email protected] (M. Schiemann). 0032-5910/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.powtec.2012.05.037

obtain details on the particle formation process and, hence, only information on how overall operating conditions influence the characteristics of Fe2O3 particles are available from Zaspalis et al. [7]. Laminar drop tube reactors (DTR) offer the possibility to investigate the particle formation process under well-defined conditions. Beck et al. carried out basic investigations on spray roasting of iron chlorides in a laminar DTR [3]. Those experiments showed the influence of the gas phase properties, but did not cover the predominant conditions present in spray roasting reactors. Furthermore no information on particle surface details like specific surface area and pore size distribution were published. The first is important for further processing of the iron oxide produced, and the latter possibly having distinct influence on the particle reactivity. Both parameters are of major interest and lead to a better understanding of the spray roasting process. The purpose of the work presented here is to develop a simplified model considering the basic phenomena of the complex process of particle formation and chemical reaction. This model helps to improve the understanding of the acid regeneration process and to optimize the efficiency of industrial scale reactors. To demonstrate the accuracy of the model developed, CFD-simulations of the laboratory reactor are presented. 2. Theoretical background Spent pickling liquor roughly consists of 70 w-% of water and 30 w-% of iron chloride. It is injected into the reactor via nozzles creating droplets with diameters ranging from 30–600 μm. Initially, the droplets behave like pure water droplets. After being heated up to the boiling point (373 K), water begins to evaporate. It is assumed that

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no or only a negligible amount of water evaporates during the heating phase, as the droplet surface is heated rapidly, thus, the boiling point on the surface is reached quickly. The evaporation of water leads to a concentration gradient in the droplet. The FeCl2 remaining in the droplet is enriched in the outer shell. When the concentration of FeCl2 reaches 63.6 w-% in this shell, all FeCl2 is bound in its hydrate form FeCl2 ⋅ 4H2O. This creates a solid layer of reduced permeability on the outer surface of the droplet. The water remaining inside causes swelling which changes the diameter of the solidified surface significantly. Finally, the particle ends as hollow sphere with a porous surface. When, after evaporation, only water bound in FeCl2 ⋅ 4H2O remains in the particle, the particle resumes heating up to T = 379 K. At this point the tetrahydrate is reduced to dihydrate. The remaining two molecules of water are then removed at T = 433 K, when monohydrate is formed, and at T = 538 K. This temperature marks the beginning of the chemical conversion process to iron oxide [4]. It can be expressed by two chemical reactions: 4FeCl2 þ 4H2 O→4FeO þ 8HCl þ 508 kJ=mol

ð2Þ

4FeO þ O2 →2Fe2 O3 −563 kJ=mol:

ð3Þ

The first reaction requires a certain amount of water vapour in the reaction atmosphere and is essential for the recovery of the HCl, while the second reaction is responsible for the formation of the desired by-product α-Fe2O3. The reaction step given in Eq. (3) summarizes two reaction steps. In detail, Fe3O4 is formed as an intermediate product from FeO and further reacts to Fe2O3 by the following steps: 6FeO þ O2 →2Fe3 O4

ð4Þ

4Fe3 O4 þ O2 →6Fe2 O3 :

ð5Þ

It should be noted here, that a well defined composition of the gas phase is necessary to assure the formation of Fe2O3, while deviant gas compositions lead to other (usually undesired) end products [5]. For example a lack of O2 would lead to Fe3O4, while high temperatures enforce the formation of γ-Fe2O3, which is undesired because of its magnetic properties. Usually the required conditions are met in

industrial reactors, so Eqs. (2) and (3) are sufficient for kinetic modelling.

3. Experimental setup A laminar drop tube reactor (Reynolds numbers, using the tube diameter, are in the order of 700) was designed to investigate the process of particle formation and chemical reaction under typical conditions and reduced to one dimensional particle trajectories. A methane fired burner supplied with preheated air of variable temperature provides a hot gas atmosphere in the temperature range of 900–1100 K, which is typical for spray roasting reactors [5,8]. Supplementary water vapour and oxygen are possible to modify the gas composition. A schematic sketch is shown in Fig. 1. In the combustion chamber flue gas, vapour and auxiliary gases are mixed. Before the gas enters the quartz glass tube, which acts as optical accessible drop tube, it is homogenized by a porous ceramics disc (silicon carbide, 80 ppi, thickness: 10 mm). The length of the glass tube (d = 65 mm) was varied between 1 and 1.5 m during the experiments to assure the formation of solid particles and a certain degree of chemical conversion of the iron chloride. Both are necessary to characterize the participating processes. The temperature was controlled by a type S thermo couple placed right below the porous ceramics disc approx. 1 cm from the drop tube entrance. All gas and vapour flows were controlled by mass flow controllers and pressure gauges to ensure defined conditions. A summary of the experimental conditions is given in Table 1. As the molar ratio of H2O/O2 should be higher than 4, in order to guaranty entirely roasted particles solely consisting of Hematite [4] in the final state, this ratio was varied between 1.85 (Exp. 2) and 5.7 (Exp. 4). In all experiments, monodisperse droplets of an iron chloride solution containing 30 w-% FeCl2 dissolved in demineralized water were created by a vibrating orifice droplet generator. The droplet generator is based on the principle of perturbated liquid jets [6], i.e. the liquid is pumped through an orifice (diameters used were 50 μm and 35 μm), which is periodically excited by a piezo ceramic. The setup is described by Beck et al. [3]. Droplets were created with a diameter of 89.4 ± 4.5 μm respective 66.3 ± 4.8 μm, respectively. The average droplet diameter was measured with a 2D PDA system (Dantec 60X).

Fig. 1. Schematic sketch of the burner head with all components and the quartz glass drop tube.

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Table 1 Summary of the resulting gas mixtures for all experiments, given are the volume flow, the molar concentration and the gas temperature downstream of the porous ceramics disc. Exp. 1–6: dorifice = 50 μm, Exp. 7: dorifice = 35 μm. Exp. #

V_ ½ln = min

N2

CO2

O2

H2O

T [K]

lDT[m]

1 2 3 4 5 6 7

78.0 63.0 63.0 73.3 78.0 73.3 73.3

73.0 65.0 58.9 50.6 73.0 50.6 50.6

7.7 9.5 9.5 8.2 7.7 8.2 8.2

4.0 6.0 12.5 5.3 4.0 5.3 5.3

15.4 19.0 19.0 30.4 15.4 30.4 30.4

883 893 910 933 938 928 920

1.0

1.5

In all experiments, solid samples were taken at the drop tube outlet. The particles were collected in ceramics bowls, which were kept at room temperature to stop the reaction process immediately. 3.1. Analysis of formed particles Static nitrogen physisorption experiments were performed in an Autosorb 1 C setup (Quantachrome). All samples were pre-treated at 100 °C for 4 h. This is below the typical temperature of 200 °C, but was necessary as there were residues of chemically bound water in the samples, which would have been removed by higher pre-treatment temperatures, leading to falsified results concerning the surface parameters. Data were analyzed according to the BET equation, assuming that the area covered by a nitrogen molecule equals 0.162 nm 2. The pore size distribution was obtained using the BJH method. The accuracy of the measurements was ±1 m 2g − 1. The production of iron oxides in spray roasting reactors usually targets a certain mineral composition of the produced powder. For example, the production of α-Fe2O3 is preferred to γ-Fe2O3 due to different magnetic properties. Therefore, the analysis of the produced samples by XRF or titration, both of them leading to very accurate elemental compositions, was not considered. Instead, X-ray diffractometry was applied to measure the mineral phase composition of the samples semi-quantitatively. This technique is standard in the characterization process of spray roasted iron oxides, when the phase composition is considered [7–10]. This information is important, as it leads to better understanding of the reaction kinetics, which is necessary for accurate modelling of the chemical reactions. Measurements were carried out in a PANalytical X'Pert Pro diffractometer. Scanning electron microscopy (SEM) was applied as imaging analysis technique to gain knowledge of the particle shapes and diameters. For SEM imaging a Zeiss/LEO 1530 Gemini was used. 4. Experimental results SEM images were used to identify the particle structure formed during the spray roasting process in the laboratory. A representative particle, shaped like the hollow sphere expected, is depicted in Fig. 2a. The diameter of this particle was measured to be d ≈ 195 μm. In Fig. 2b, surface details of a particle are presented in a higher magnification. It is clearly shown that the particle surface exhibits various cracks and fissures creating a porous structure and increasing the particles' active surface. Both images show particles from experiment 1. For experiments 1–6, i.e. an initial droplet diameter of 89 μm, and an average particle diameter of 195.3 ± 22.1 μm were measured from 64 particles in total. For experiment 7, where the initial diameter was 66 μm, the particles showed a final diameter of 169.2 ± 13.0 μm (22 particles in total). These data indicate that the particles undergo a significant swelling before ending in a solid hollow sphere. This state was reached by nearly half of the particles, while others ended in irregular shaped or collapsed particles. All the final states are described as possible results of drying processes of particles [9], where different factors take influence on the actual

Fig. 2. SEM images of a representative hollow particle (a), and surface details (b), showing the porous structure of the particle surface.

final state, like drying rate, permeability, stability of the outer shell and further more. The results of the physisorption measurements are summarized in Table 2. The particle samples from experiments carried out in the shorter drop tube (1–4) show specific surface areas between 12.34 and 22.41 m 2g − 1. As the drop tube length and thus the residence time of the particles are increased, the specific surface area is enlarged to 31.43–36.19 m 2g − 1. Also sample 7 generated from droplets with 66 μm initial diameter shows a specific surface of 35.58 m 2g − 1. These values are close to the upper limit discussed in literature, where data published is ranging from 2.4–50 m 2g − 1 ([2,5,7]). The estimated pore diameters were calculated using the relation dpore ¼

4V p : Ap

ð6Þ

Table 2 Specific surface As and mean pore diameter dpore for all measurements and averaged for experiments with different drop tube lengths. Exp. #

As [m2/g]

dpore [nm]

1 2 3 4 5 6 7

15.73 12.34 16.82 22.41 31.43 36.19 35.58

10.10 9.77 7.56 9.88 5.56 3.77 3.77

d pore ≅9:3nm

d pore ≅4:5nm

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to calculate the droplets/particles density depending on the chemical composition throughout the whole process:

Table 3 Results of the X-diff measurements in mole-%. Exp. #

FeCl2 ⋅ 4H2O

FeCl2 ⋅ 2H2O

FeO

Fe3O4

Fe2O3

1 2 3 4 5 6 7

77.1 77.8 73.4 53.1 71.5 71.9 90.3

11.2 6.6 14.2 37.2 0 0 0

10.1 14.8 12.4 9.7 25.6 23.7 0

1.6 0.8 0 0 2.9 4.4 0

0 0 0 0 0 0 9.7

ρp ¼

In Table 2, mean pore diameters d pore are given, grouping the experiments by drop tube length. In the short drop tube, particle formation led to a mean pore diameter of 9.3 nm, while the proceeding reaction altered the surface to a mean pore diameter of 4.5 nm. X-ray diffraction measurements were carried out to quantify the mineral components in all samples. The results are summarized in Table 3. All samples contained a significant amount of FeCl2 ⋅ 4H2O. In the first four samples, FeCl2 ⋅ 2H2O was found as well, while all samples produced in the 1.5 m drop tube did not show contents of dihydrate. Wustite (FeO) was found in samples 1–6, which were created with a 50 μm orifice or 89 μm initial droplet diameter. While the concentration of FeO was found to range from 10 to 15 mol-% in all samples generated in the shorter drop tube, longer residence times led to roughly 25% of FeO (samples 5 and 6). Those samples also contained 3 to 4% of magnetite (Fe3O4), while there was half or less than half of this amount detected in samples 1 to 4 and 7. Sample 7 was the only one with a significant content of hematite. The results of the X-Ray diffraction measurements show, that the roasting process is in a very early stage, as the particles still contain large amounts of FeCl2. Although the conversion process is not finished, these partially reacted particles allow to estimate the reaction rate. The results do not show a strong dependency of the reaction rate on the gas phase composition. 5. Numerical modelling The goal is to develop a model for numerical modelling of large scale reactors. As the modelling of the gas phase was carried out using FLUENT, 1 a user defined function (udf) was developed which considers the major phenomena of the particle formation and chemical reaction process. When a droplet is heated to the boiling point of water (T = 373 K), the unbound water evaporates from the particle, leading to a reduction in droplet size and an increase of the density. The evaporation process is controlled by convective heat transfer, so the shrinking rate of the droplet is described by [11]:  3 0 2 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi T g −T p d 4λ @ 4 5: d ¼ 1 þ 0:23 Rep Þ1n 1 þ dt p P p cp;g dp hf

ð7Þ

The quantities included are the droplets density ρp, its diameter dp and temperature Tp, the heat capacity of the surrounding gas phase cp,g and the latent heat of water hf. Note, that during the evaporation of unbound water, the particle temperature is assumed to be constant. A temperature gradient in the particle, which is possible for larger particles, is neglected. The density as a function of the iron chloride concentration is given in [4]. As the density changes significantly between the initial iron chloride solution and the final state Fe2O3, a mass weighted approach was chosen

1

Ansys, Canonsburg, Pensylvania, USA.

  1 ∑ mi ρi : mp i

ð8Þ

Here, mp is the particle mass, mi is the mass of the i-th component and ρi is its density. Note that the model only differentiates between unbound water, water bound to tetrahydrate, iron chloride, wustite and hematite, as these components are included in the chemical conversion process. During the evaporation process, FeCl2 is enriched in the outer shell of the droplet. An analytical expression to calculate the concentration gradient was developed by Brenn [12], who described the mass fraction Y(τ, ξ) of the remaining substance (FeCl2) by the following equation: −λj

Y ðτ; ξÞ ¼ ∑ C j ð1 þ ατ Þ j

  3 α 2 ξ : :M K λj; ; − 2 4G

ð9Þ

The mass fraction is calculated on a basis of dimensionless parameters, as there are time τ, diameter ξ, shrinking rate α, diffusion coefficient G and the specific eigenvalues of the problem λj. The Kummer function Mk is discussed in [13], it is also needed to calculate the coefficients Cj. Further input parameters are the droplet diameter at the beginning of the process and the initial mass fraction of FeCl2 in the droplet, which have to be defined as starting values. The shrinking rate α can be estimated by simulation of a water droplet in hot gas of given temperature. The diffusion coefficient of iron chloride in water can be calculated by the Wilke–Chang correlation [14], and is approx. 5⋅10 − 9 m²/s. When the concentration gradient Y(τ, ξ) reaches a value of 0.64 in the outer layer of the droplet, i.e. the droplet shell consists of pure FeCl2 ⋅ 4H2O, the shell becomes impermeable for water vapour escaping from the inner region of the droplet. From this point on, the droplet is treated like a solid particle. The increasing pressure in the particle core causes a particle swelling process. The swelling is calculated during the evaporation process of unbound water by the formula " #   df mp;0 −mp 1 dp mp ¼ d0 1 þ : d0 1−Y FeCl2 mp;0

ð10Þ

The parameters included are the diameter d0 as the starting point for the swelling process, the final diameter df which is reached when all unbound water has left the particle, thus the particle only consists of pure FeCl2 ⋅ 4H2O, the average mass fraction Y FeCl2 when the swelling process starts (this can be calculated from the concentration gradient described in Eq. (9)), the particle mass at this time mp,0 and the current mass of the particle mp, which indicates the particle mass at any given time. The final diameter experimentally determined for two droplet/particle sizes was reported in chapter 2.1. In the next step, when all free water has been removed from the particle, the outer diameter of the particle remains constant. Now, all water which is bound to iron chloride hydrate is split of and evaporates, leaving pure iron chloride in the particle. Fig. 3 shows the temperature steps in the conversion process depending on the energy input per mass unit of iron. At 373 K, more than 3 kJ/g droplet mass is necessary to evaporate all unbound water in a particle containing 30 w‐% of iron chloride. In the next step, the now solidified particle is heated to 379 K, where the tetrahydrate is converted to dihydrate. After further energy input by convective heat transfer, the particle reaches 433 K and looses one more water molecule per iron chloride molecule, resulting in purified monohydrate. The last water bound to the molecule is split of at 538 K. After losing the last water, the chemical reaction of iron oxide formation starts.

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The gas transport depending on diffusion through the porous shell of the particle was calculated by kpor ¼

As it is illustrated in Fig. 3, the different species exhibit different heat capacities and evaporation enthalpies. For the former, the equation

ð11Þ

was used, where the energy consumed was divided by the temperature difference while the particle mass was constant, i.e. during particle heating between two steps of hydrate water evaporation. The enthalpy required for evaporation was calculated by

hf ¼ Δ

Q ðT ¼ const:Þ m

ð12Þ

in the phases of constant particle temperature. The values determined for cp and hf are summarized in Table 4. The chemical reaction, which has been described in Eqs. (2) and (3), is controlled by three processes, the chemical reaction rate, pore diffusion and boundary layer diffusion of the components H2O and O2. These processes are combined to one effective reaction rate.

keff ¼

1 kkin

1 þ k1 þ K diff

ð13Þ

De ¼

! ε 1 1 þ ; τ DKn Ddiff

Under assumption of an ideal reaction, the first step requires water vapour, which reacts with FeCl2 forming FeO and gaseous HCl. Arrhenius parameters for this reaction are given by Vilcu [15], who carried out experiments at temperatures between 853 K and 893 K, leading to a pre-exponential factor k = 2080.0 mol(m³s kg) − 1 and an activation energy Ea = 121.0 kJ mol − 1. For the second reaction, in which FeO reacts with O2 to Fe2O3, the following Arrhenius parameters k = 1.427⋅10 8 m³ (mol s) − 1 and Ea = 3780 J mol − 1 were used [16].

T [K]

cp [kJ/(kg K)]

b 373 373 b T b 379 379 b T b 433 433 b T b 538 T [K] 373 379 433 538

2.918 1.838 2.164 3.395 hf [MJ/kgH2O] 2.26 2.82 3.30 3.29

ð15Þ

where the Knudsen diffusion coefficient DKn ¼

dpore 3

rffiffiffiffiffiffiffiffiffi 8RT πM

ð16Þ

describes the gas transport due to molecule-wall interactions, which is controlled by the pore diameter dpore. For all calculations, dpore was set to 4 nm, according to Table 1. Further parameters in Eq. (15) are the porosity ε (set to 0.05 in the following), the tortuosity τ of the pores (set to 5), both taken from [18], and Ddiff, the gas diffusion coefficient used to calculate the effect of molecule-molecule interactions, as it is presented by Reid [17]. The same coefficient is used to calculate the transport of the reacting species to the particle and thus to calculate kdiff ¼

2MA Ddiff ; dp RT

ð17Þ

where MA denotes the molar mass of component A diffusing in the gas mixture. The combination of the chemical and diffusive reactivities leads to the total mass flow rate d 2 m ¼ πd keff nB P dt A

por

Table 4 cp and hf for all characteristic steps of hydrate conversion.

ð14Þ

where dp denotes the particle diameter and di stands for the inner diameter of the shell. Further parameters contributing to Eq. (14) are the universal gas constant R and the particle temperature Tp. The inner diameter di has been calculated from the measured particle diameters under the assumptions that a particle consists of pure FeCl2 and that all FeCl2 remains in the particle during the drying process. The pore diffusion coefficient De is calculated using the Bosanquet relation

Fig. 3. Particle temperature plotted against energy input per mass unit.

  1 Q 1 −Q 2 cp ¼ m T 1 −T 2

2d D  p e ; di dp −di RT

ð18Þ

of substance A, which is FeCl2 for reaction (2) and FeO for reaction (3). nB is the mole fraction of the gaseous reactant contributing to the respective reaction. Hence the chemical reaction affects the gas phase as well, and, therefore, source terms have to be calculated. For the components H2O and O2, which are dissipated at the particle surface, the mass consumption can be determined from Eq. (18): ΔmB ðΔt Þ ¼ ν AB mA

MB f Δt MA

ð19Þ

i.e. the mass flow rate of substance A is multiplied by the particle flow rate f_ (which acts as a scaling factor, as the mass of a single particle multiplied by the number of particle trajectories in the simulation may differ from the total particle mass considered in the simulation) and the calculation time step Δt. The ratio MA/MB corrects Eq. (19) for the different molar masses of the reactants involved. As the reaction of FeCl2 with water causes two moles of HCl per mole H2O, the stoichiometric coefficient νAB is −1 for the mass flow of water and 2 for the release of HCl. As the reaction rate for the oxidation reaction of FeO is given in terms of mass change of FeO, the stoichiometric coefficient νAB is −0.25 when ΔmO2 is calculated.

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Fig. 4. Comparison of reaction rate constants of the three processes affecting the reaction rate.

Fig. 6. Particle temperature and density, initial diameter 90 μm, gas phase conditions from Exp. 5 (Table 1).

Droplets of 89 μm and 65 μm were simulated with an injection velocity of 8 m/s. The mass flow rate was set to 1.3⋅10 − 5 kg/s. The reaction rate constants kkin, kpor and kdiff for the formation of HCl (Eq. (2)) are compared for a particle injected with 90 μm initial diameter into the reactor with boundary conditions of Exp. 5 in Fig. 4. This experiment represents typical conditions for spray roasting reactors. Along the whole trajectory, the pore diffusion rate constant kpor is two orders in magnitude smaller compared to the other reaction rate constants, according to Eq. (13). This clearly indicates the dominating influence of pore diffusion on the reaction rate. Figs. 5 to 7 show the development of several characteristic parameters of particle evolution for a 90 μm droplet in the laboratory reactor under the conditions of Exp. 5 (Table 1). In Fig. 5, the particle diameter and the diameter di of the void leading to a hollow sphere are depicted for the first 0.3 s of particle residence time in the reactor. During the first 0.1 s, the particle size is decreasing due to evaporating water. After this period, formation of the inner void starts, forming a hollow particle. This is the point when the particle swelling process is initiated, thus the outer diameter dp starts to increase as well. The swelling process is interrupted twice after 0.15 s.

In these periods, the particle undergoes inert heating until the next conversion of the iron chloride takes place in terms of dehydration. In Fig. 6, the evolution of the particle temperature and density is plotted against the residence time in the combustion chamber. After rapid heating to 373 K, the temperature stays constant for 0.1 s, at this temperature level, the unbound water evaporates from the droplet. The steps of dehydration are visible as times of constant particle temperature. After 0.175 s, the particle temperature rapidly increases. This is the point, where all water is evaporated, the swelling process is finished and the chemical reaction starts. The particle density shows a permanent increase, beginning at 1400 kg/m 3, which is the density of an aqueous solution containing 30 w‐% of iron chloride and rising up to a value of 3300 kg/m 3 at the reactor outlet. The final density reached by the given particle indicates an incomplete chemical reaction, as the density of FeCl2 is 3165 kg/m 3, while the iron oxides considered have densities of 5900 kg/m 3 (FeO) respective 5240 kg/m 3 (Fe2O3) [4]. Fig. 7 shows the evolution of the particle mass and the mass of the species considered, e.g. FeCl2, FeO and Fe2O3. The rapid mass loss at the beginning of the particle trajectory represents the evaporation of water. Here, the interruptions caused by inert heating until the next step of hydrate water evaporation become visible as well. After 0.15 s, when the chemical reaction starts in the now dry particle, the particle mass shows a very slow decrease. The conversion process causes a decrease in the FeCl2 mass, while the mass fractions of FeO and Fe2O3 increase. Note, that the mass values of the iron oxides are scaled by a factor of ten. The particle consists of roughly 1.5⋅10 − 10 kg FeCl2 and 5⋅10− 11 kg of each FeO and Fe2O3 at the end of the reaction tube. As the prediction of the chemical conversion and the chlorine content in particular is one of the major purposes of the current work, simulations of all seven experiments were carried out to compare the numerical and experimental results. The concentrations in the simulations were determined from 20 particles, which were tracked with the random walk model included in

Fig. 5. Particle diameter dp and diameter of the inner void di, initial diameter 90 μm, gas phase conditions from Exp. 5 (Table 1).

Fig. 7. Overall particle mass mp, masses of iron chloride (mFeCl2), wustite (mFeO) and hematite (mFe2O3), gas phase conditions from Exp. 5 (Table 1).

The geometry of the laboratory reactor, simplified to the glass tube from the injection point of the particles downstream, was used to verify the particle formation model in FLUENT. A mesh with 50 000 hexagonal cells was generated. The gas phase chemistry was modelled by the methane-4step-Lindsted model [19] and the eddy-dissipation concept (EDC, [20]). On top of the glass tube, gas mixtures corresponding to the experimental conditions given in Table 1. were supplied. This leads to gas velocities and temperatures comparable to those during the experiments.

6. Numerical results

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Fig. 8. Experimentally and numerically determined mole fractions of FeCl2.

Fig. 10. Experimentally and numerically determined mole fractions of Fe2O3.

FLUENT, which is a stochastic method to track particles while considering flow turbulence along their trajectories. This leads to statistical scattering of the particle trajectories and results in scattered final states of particles. From those results the mean value and the standard deviation were computed. Figs. 8 to 10 show the numerical results compared to the experimental results. For the latter ones, an uncertainty of 5 mole% in total was assumed, as this is the uncertainty of the X-Ray diffractometer. The content of iron chloride is compared in Fig. 8. For five of seven experimental conditions, the simulated content of iron chloride matches the experimentally determined value. Only the results from the experiments 4 and 7 do not show an agreement within the tolerance range. A bigger difference was found for the FeO concentrations. Only the experiments 1, 2 and 6 could be reproduced in range by the numerical simulation within the tolerance. A better agreement between simulation and experiment is achieved for the hematite concentration, as shown in Fig. 10. The experiments 1, 5 and 6 are well reproduced by the numerical simulation. The experiments 2 and 4 are still in the tolerance range. In summary, the numerical results show a stronger dependency on the gas phase composition than the experimentally determined values do. For 13 out of 21 data pairs, the results of the numerical results are in agreement in respect to the numerical and experimental tolerances. The data pairs (sample 5, FeO) and (sample 3, Fe2O3) are close to agreement, while further 6 of 21 data pairs are not in good agreement. A possible reason is the neglected kinetics of the decomposition of the iron chloride hydrates. As kinetic data for this process is given in literature [21], it is foreseen to implement this further detail into the model of particle formation and reaction.

sensitive with respect to the gas phase composition. Nitrogen physisorption experiments were carried out to gain knowledge on the specific surface and the pore size distribution of the created particles. While the former was found to be high, between 12 and 36 m 2/g, but in agreement to literature values, the latter was used to be implemented into a model, which can be used to numerically simulate the spray roasting process in CFD simulations. This model includes the particle swelling and the chemical reaction, which was found to be dominated by pore diffusion. The evolution of the specific surface is not included in the current model. The experimental results concerning the mineral phase composition were used to verify the model derived in FLUENT simulations of the laboratory reactor. The simulations agreed with the experiments within the tolerance range by trend, but showed a stronger dependence on the gas phase concentrations applied. Here, additional effort is required. The global reaction rate could be deduced from the experiments. The reaction rate was found to be controlled by pore diffusion. The new model can be used for numerical simulations of large scale industrial plants, work which is currently underway. Here, the particle formation and reaction model can help to gain knowledge on the reaction conditions, i.e. temperature fields and gas phase compositions in order to improve the reactor design and thus the quality of the iron oxide produced in those large scale facilities.

7. Conclusions Experiments were carried out to examine the formation of iron oxide particles from aqueous iron chloride solutions in a laboratory scale spray roast reactor. Monodisperse particles were investigated to examine the particle swelling, mineral phase composition and the surface properties of the iron oxide under typical conditions of industrial plants. X-Ray diffraction measurements were used to quantify the phase composition of the particles, which was found to be little

Fig. 9. Experimentally and numerically determined mole fractions of FeO.

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