Direct detection of coking and regeneration of single particles and fixed bed reactors by electrical sensors

Applied Catalysis A: General 382 (2010) 254–262

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Applied Catalysis A: General journal homepage: www.elsevier.com/locate/apcata

Direct detection of coking and regeneration of single particles and fixed bed reactors by electrical sensors N. Müller a,b , C. Kern b , R. Moos a , A. Jess b,∗ a b

Department of Functional Materials, University of Bayreuth, 95440 Bayreuth, Germany Department of Chemical Engineering, University of Bayreuth, 95440 Bayreuth, Germany

a r t i c l e

i n f o

Article history: Received 25 March 2010 Received in revised form 3 May 2010 Accepted 4 May 2010 Available online 11 May 2010 Keywords: Regeneration Coke burn-off Sensor Impedance spectroscopy

a b s t r a c t The activity of solid catalysts is often reduced by the formation of coke. Thus, regeneration by coke burn-off is needed from time to time. A new method to monitor in situ the coke load during coking and decoking by electrical sensors is presented, which could be used as a controlling instrument of high value. Single particles of an Al2 O3 catalyst were electrically contacted and characterised by impedance spectroscopy. A clear relationship between coke load and the impedance is observed. The sensor was tested by regeneration experiments both with single particles and in a coked fixed bed reactor. The results show that the coke burn-off within a single coked catalyst particle can be monitored and that it is possible to distinguish how strong the decoking of a single particle is influenced by pore diffusion. For a fixed bed, the axial coke profile can be monitored by means of axially distributed sensors, and the velocity of the reaction front and the length of the reaction zone are directly deduced by the local change of the coke profile with time. © 2010 Elsevier B.V. All rights reserved.

1. Introduction Fixed bed catalysts are used in refinery processes, in the petrochemical and fine chemical industry for a variety of processes to convert crude oil fractions and organic intermediates into required products [1]. In many processes, the catalysts deactivate by coke formation, e.g. in catalytic reforming of gasoline, catalytic cracking, desulfurisation or dehydrogenation of paraffins. In general, coke formation is a highly unwanted side reaction, which decreases the activity of the catalyst and often alters the product composition towards an unwanted direction [1–4]. To restore the activity of the catalyst, regeneration is necessary, which is normally conducted by burning off the coke with small amounts of oxygen in an inert gas stream. Depending on the specific process, the regeneration temperature ranges from 400 to 700 ◦ C. Lower temperatures lead to an excessive increase of the regeneration time as the reactivity of the coke is then too low. The maximum temperature is limited by the stability of the catalyst, e.g. gasoline reforming catalysts lose surface by sintering above temperatures of 550 ◦ C [5]. State-of-the-art to determine the coke load both during coke formation and decoking is to sample particles from time to time and to measure the coke load by thermogravimetry or other ex situ methods, e.g. by elementary analysis. In principle, it is possible

∗ Corresponding author. Tel.: +49 921 557430. E-mail address: [email protected] (A. Jess). 0926-860X/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.apcata.2010.05.001

to determine the coke load in situ, if the correlation between the decreasing activity and the coke load is well-known [6]. However, this indirect method is not accurate and does not allow to monitor the actual status of the coke load of a “working” catalyst in situ. In addition, only the average activity and average coke load of a fixed bed can be determined by such a correlation and note the local value that may change in axial direction. The regeneration involves both chemical reaction and transport processes, since oxygen must be transported by external mass transfer and by pore diffusion from the bulk phase to the internal coked surface. Pore diffusion strongly influences the effective rate of burn-off, at least for particle diameters and temperatures relevant for industrial (fixed bed) processes (>1 mm, > 400 ◦ C), so radial gradients of the O2 -concentration and with proceeding burnoff also of the carbon content in a catalyst particle are established (Fig. 1, left). For a strong limitation by pore diffusion, the particle may be divided into two distinct zones, a carbon-free outer shell and a core rich in carbon (shrinking core model). During decoking, the zone that divides these two regions moves towards the center of the particle (shrinking core model) [7–9]. On the macroscopic level of a fixed bed reactor, a moving reaction zone migrates through the reactor during decoking (Fig. 1, right). Within this zone, the oxygen concentration steeply decreases from the inlet value to zero, and the temperature increases from the inlet temperature to a certain much higher temperature. Thus, we have to consider time-dependent profiles of the oxygen concentration and the carbon load both within the particles (microscopic level) and within the fixed bed (macroscopic level), as

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Nomenclature Symbols and abbreviations Am external surface area (m2 /kg) cO2 concentration of oxygen (mol/m3 ) d diameter (m) D diffusion coefficient (m2 /s) EA activation energy (J/mol) EDX energy dispersive X-ray spectrometer IR infrared (analyser) km reaction rate constant of carbon combustion (m3 /(kg s)) km,0 pre-exponential factor of km (m3 /(kg s)) carbon load of catalyst, ratio of carbon mass to mass LC of fresh catalyst (kgC /kgcat ) LRF length of reaction front (m) m mass (kg) M molecular weight (kg/mol) NTP normal temperature and pressure (0 ◦ C, 1.013 bar) p pressure (Pa) rm reaction rate of coke burn-off (mol O2 /(kgcat s)) r radial coordinate within the particle (m) r0 radius of particle (m) R ideal gas law constant (8.314 J/(mol K)) Re particle Reynolds number, dp ue / (dimensionless) SEM scanning electron microscopy Sc Schmidt number, /Dmol (dimensionless) Sh Sherwood number (dimensionless) t time (s) T temperature (◦ C, K) ue superficial velocity (based on empty tube) (m/s) uHF velocity of heat front (m/s) velocity of reaction front (m/s) uRF Vm particle volume (m3 /kg) conversion of oxygen (dimensionless) XO2 z axial coordinate (m) Greek symbols ˇ mass transfer coefficient (m/s) ε voidage of fixed bed (0.4 for spheres) (dimensionless) εp porosity of particle (dimensionless)  effectiveness factor with respect to pore diffusion (dimensionless) b bulk density of fixed bed (kg/m3 ) gas density (mol/m3 ) g p particle density (kg/m3 )  kinematic viscosity (Pa s)  tortuosity (dimensionless)  Thiele modulus (dimensionless) Subscripts (if not already listed above) 0 initial b bulk C carbon eff effective cat catalyst g (bulk) gas phase in inlet of fixed bed Knu Knudsen m related to the mass mol molecular

Fig. 1. Coke burn-off during regeneration of a coked fixed bed catalyst on the level of a fixed bed reactor and a single particle. The arrows denote increasing time [10].

depicted schematically in Fig. 1. Details are given in the literature [11–13]. During the regeneration, the direct and in situ detection of coke formation in the particles would allow to measure the actual status of the catalyst and to respond instantaneously to irregularities. During regeneration, such a coke sensor (as investigated in this work) could not only detect the position of the regeneration front but could also monitor the remaining carbon load. This might help to improve the catalyst regeneration with respect to efficiency and safety. The basic idea of this work is to use selected catalytic particles (equipped with a respective sensing setup) that show the same coking behavior as all other catalyst particles (at least those near the “sensor particle”). These sensors can therefore directly represent the status of the coke level. Since the sensor should also detect the regeneration, one has to keep in mind that the coke may be burnedoff at conditions where mass transfer limitations may influence the process. Therefore, the sensor should have the same or at least a similar geometry like all other catalyst particles. In two previous publications, such a sensor for the in situ monitoring of the coke load of catalyst particles was presented for the first time [10,14]. The sensor consists of a representative single catalyst particle, which is electrically contacted and characterised by electrical impedance spectroscopy. The coke formation/burn-off and the impedance were simultaneously measured in a magnetic suspension balance [10]. A clear relationship between the coke loading and the electrical impedance signal could be observed, both during coke formation and during the regeneration by coke burn-off. In this work, these investigations are extended with respect to two aspects (Fig. 1), thereby mainly focusing on the regeneration (coke burn-off): ◦ The first aim was to monitor the coke burn-off within a single particle and to investigate the influence of pore diffusion on the sensorˇıs signal. Although first kinetic studies were already conducted, which indicate the influence of pore diffusion limitations on the impedance signal [10], comparative measurements of radial coke profiles as a function of decoking time and temperature have not yet been done.

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Fig. 2. Experimental setup for the coking and regeneration experiments in a fixed bed reactor (for details see [15]).

◦ The second aim was to investigate whether the monitoring of the regeneration of a coked fixed bed is possible by several axially distributed sensor particles and to derive by this means directly important parameters such as the velocity of the reaction and heat front or the axial profile of the remaining coke load. 2. Experimental methods 2.1. Preparation and regeneration of coked catalysts The deactivation (preparation of coked catalyst) and regeneration was investigated in a practically isothermal tubular reactor with a diameter of 3 cm (Fig. 2, details in [15]) with Al2 O3 pellets as a model catalyst (Table 1). The fresh pellets (typically 180 g) were filled into the reactor, giving a bed height of about 25 cm. The temperature was maintained at typically 550 ◦ C. Propane served as a coking agent (50 vol% in N2 ). It was passed through the reactor at 1 bar with a flow rate of 20 l/h (NTP), adjusted by mass flow controllers (Brooks Instruments). The final content of coke (carbon) reached after about 2 days was 0.16 gC /gcat . The experiments on the regeneration of the coked fixed bed were carried out with a mixture of N2 and O2 (4 vol%) at 1 bar with a flow rate of 30 l/h (NTP). The CO- and the CO2 -content in the product gas was measured by IR-analysers (Fisher Rosemount), and the O2 -content was also continuously measured (paramagnetic susceptibility, Fisher Rosemount). The inlet content of O2 was adjusted by a mass flow controller (Brooks Instruments). The adiabatic temperature rise is about 500 ◦ C (for 4% O2 ), but the increase in temperature along the fixed bed of the lab-scale reactor was only

Table 1 Characteristic data of the fresh Al2 O3 catalyst (SN 380, Südchemie). Catalyst composition Geometry Diameter; length Catalyst density BET-surface area of fresh and regenerated catalyst BET-surface area of coked catalyst (15 wt% coke) Pore volumea Average pore diametera Porosity Tortuosity

>99% Al2 O3 Cylinder 4.5 mm; 4.5 mm 1450 kg/m3 178 m2 /g 170 m2 /g 0.3 cm3 /g 10 nm 0.37 2.7 [16]

a The pore volume and the average pore diameter almost remain during the coking/decoking process (<15 wt% coke).

around 15 K, because the volume-to-surface ratio and thus the heat losses were high. The experiments of this work were therefore done with an almost isothermal lab-scale fixed bed reactor. Two additional experimental methods were used in this work. The reaction rate of decoking was determined by thermogravimetrical measurements (thermobalance, Seiko Instruments, TG/DTA 6300), i.e. by the decrease of the carbon load with time (for details see [10,15]). The radial carbon distribution within single (coked and partly regenerated) particles was measured by SEM/EDX (JSM840A, Jeol/INCA, Oxford Scanning Microscope with Oxford EDX-Detector) at the Department of Materials Processing (University Bayreuth). Thereby, it has to be noted, that the initial radial carbon distribution was always homogeneous, which is a result of the very low reaction rate of coke formation [15].

2.2. Monitoring of carbon load by measuring the impedance of single particles A single catalyst particle was used as a coke sensor. The complex electrical impedance, Z, and the resistance R were measured with the setup as shown in Fig. 3. Five sensors were used to monitor the carbon content in axial direction in the fixed bed reactor (distance from inlet of catalytic fixed bed: 2.5, 7.5, 12.5, 17.5, and 22.5 cm). Each sensor particle was contacted with a gold paste on its opposite faces. After sintering, a wire was welded on the gold layer. To reduce the physical strain at the contacts and to protect the sensor, the particle was clamped into a steel bracket. Between the bracket and the sensor particle, alumina plates were fixed. The wires passed a ceramic tube, which served as a feedthrough and were connected to the impedance analyser (HP 4284A LCR-Meter). In addition to the experiments with five sensors (axially) distributed in the fixed bed, the impedance spectra (100 Hz to 1 MHz with an amplitude of 1 V) of a single sensor particle during coking and decoking were measured by a magnetic suspension balance (Rubotherm). Details on the measuring method and on initial electrical results can be found in previous reports [10,14]. In this work, for the sake of clarification only one selected result is again presented for the analysis of the coke burn-off in a single particle (Section 4.1). In case of the single particle measurements, the impedance Z was determined at different frequencies. In case of the fixed bed measurements with five sensors, this was not practicable, because then five impedance analysers would have been needed. Thus, only the resistance R of all sensors was measured simultaneously by a

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Fig. 4. Effective rate constant of coke burn-off versus 1/T.

The effective diffusivity of oxygen in the porous catalyst is defined as εP DO2 ,pore (4) Deff,O2 = P DO2 ,pore is the combined diffusivity of the molecular diffusivity (O2 in N2 ) and the Knudsen diffusivity:



DO2 ,pore =

Fig. 3. Design of coke sensor (for details see [10,14,15]).

1 DO2 ,mol

+

1

−1

DO2 ,Knu

(5)

The Knudsen diffusivity is calculated by digital multimeter (Keithley 2700 in combination with a differential multiplexer 7700).

3. Data evaluation and modelling methodology 3.1. Effective kinetics of coke burn-off The intrinsic reaction rate of coke burn-off (in mol O2 per mass of catalyst and unit time) was measured by thermogravimetry [10,15] and is given by: rm = km LC cO2

with km = km,0 e−EA /RT

and LC =

mC mcat

(1)

Former experiments with varied O2 -content showed that the rate is first order with respect to O2 [11]. In case of the regeneration of the coked catalyst used here (cylinders with dp and L of 4.5 mm), the influence of the pore diffusion resistance cannot be neglected. The effectiveness factor  is the ratio of the rate constant with pore diffusion resistance to the intrinsic rate constant (dp → 0) and is given for a first-order irreversible reaction by: =

km,eff tanh  1 = ≈ km  

for  ≥ 2

(2)

The Thiele modulus (for a coked catalyst with a uniform carbon load LC ) is given by: Vm = Am



km LC p Deff,O2

(Vm /Am : ratio of particle volume to external surface)

(3)

DO2 ,Knu

dpore = 3



8RT  MO2

(6)

For the given catalyst with a mean pore diameter of 10 nm, Knudsen diffusion dominates, i.e. DO2 ,pore ≈ DO2 ,Knu , because DO2 ,Knu is 0.024 cm2 s−1 compared to DO2 ,mol with 1.2 cm2 s−1 (550 ◦ C, 1 bar). The overall effective rate (based on the mass of the C-free catalyst) is given by rm,eff = km,eff LC CO2 ,g with km,eff =

 1  km

+

LC ˇ Am

(7)

−1 (8)

The mass transfer coefficient ˇ was calculated by the Sherwood number for flow around a spherical particle [17]: Sh =

ˇdp = 2 + 0.664 Re0.5 Sc 0.33 DO2 ,mol

(9)

Fig. 4 depicts the result of the thermogravimetrical measurement of km,eff versus 1/T and shows that the agreement with the calculation is good. For temperatures of more than 440 ◦ C, pore diffusion has an influence of the decoking process. It should be noted that  in Eq. (3) depends on the carbon load LC , which changes gradually during burn-off with time and in case of a resistance of pore diffusion also with the radial position in the particle. The Thiele approach – Eqs. (2) and (3) – can then not be applied anymore, and numerical simulations are needed (see Section 3.3). For the thermogravimetrical measurements, the coke conversion was very low, and thus the Eqs. (3), (6) and (7) could be used for the kinetic data analysis (Fig. 4).

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3.2. Modelling of the regeneration (coke burn-off) within a single particle The radial profiles of the oxygen and carbon load within a single catalyst particle were simulated by the commercial computer program Presto (solver for differential equations, CiT GmbH, Rastede, Germany). The cylindrical Al2 O3 -catalyst has a diameter and length of 4.5 mm. For the numerical simulations, the particles were considered as spheres with the same ratio of volume to external surface area (6 Vm /Am ). External and internal temperature gradients can be neglected – as proven in [3], and only the mass balances of the gas and solid phase have to be taken into account: εp

∂cO2 ∂t

=

1 ∂ r 2 ∂r



Deff,O2 r

∂cO2 2 ∂r



− rm p

∂LC − = rm MC ∂t

(10)

r=0: r = r0 :

= 0; ∂r cO2 = cO2 ,g

(ue cO2,in ) t =

 L b C,0 MC

+ ε cO2,in



z (15)

(11)

LC = LC,0 ∂cO2

3.3.1. Velocity of the reaction front During coke burn-off in a fixed bed, a reaction front with a constant velocity develops after a short induction period. This velocity can be deduced by a mass balance: within a time interval t, the reaction front moves in axial direction by z. The oxygen, which enters the volume element with the length z within the time interval t, is converted by reaction with the coke and thereafter needed to “fill up” the void of the bed:

(with ue as superficial velocity = uG ε)

The velocity of the reaction front uRF (= z/ t) is then given by:

The initial and boundary conditions are t=0:

front, the length of the reaction zone, and the adiabatic temperature rise in case of adiabatic operation. Some more insights how to derive the following equations are given e.g. in [11,12,18–20].

(12) ∂LC =0 ∂r

(13) (14)

Eq. (14) expresses that there is no concentration gradient between the bulk phase and the outer surface of the particle. As shown by Fig. 4, this assumption is justified, at least for temperatures below about 700 ◦ C and dp < 5 mm. 3.3. Parameters to characterise the regeneration of a coked fixed bed reactor Four main parameters characterise the regeneration of a coked fixed bed: the velocity of the reaction front, the velocity of the heat

uRF =

ue cO2,in (b LC,0 /MC ) + εcO2,in

≈

ue cO2,in MC b LC,0

(16)

3.3.2. Velocity of the heat front Not only a reaction front, but also a heat front moves through the bed, which heats up the reactor zone ahead of the moving reaction front from the initial temperature T0 to the maximum temperature Tmax . The velocity of the heat front is higher compared to the reaction front and can be deduced from a respective heat balance: uHF =

ue g cp,g ue g cp,g ≈ g cp,g + b cS b cs

(17)

3.3.3. Length of the reaction zone Depending on the gas velocity and the kinetics of coke burn-off, a certain length of the bed is needed to convert the oxygen. This

Fig. 5. Radial distribution of carbon load at different regeneration temperatures for a constant burn-off degree of 50%.

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Fig. 6. Coke load versus absolute value of impedance at two regeneration temperatures.

length is called the length of the reaction zone LRF . For a plug flow reactor LRF is given by (using XO2 = 0.99 as reference):

degree of 50%. The calculated and measured values are in good agreement. Fig. 5 indicates that the radial gradient of the carbon load is ue 9.2ue LRF = − ln(1 − XO2 ) ≈ for XO2 = 0.99(18) relatively small at a low temperature (400 ◦ C), since the chemical km,eff LC,0 b km,eff (LC,0 /2)b reaction is the rate controlling step. This is in agreement with Fig. 4 as the effective reaction rate constant then still almost equals the In Eq. (18), only the half of the value of the initial coke load is used rate constant of the chemical reaction. For a temperature of more to account for the fact that the load decreases in the reaction zone than 450 ◦ C, distinct radial profiles of the carbon load are already from the inital value to zero. established, and the interplay of pore diffusion and reaction determines the rate. In case of a burn-off temperature of more than 3.3.4. Temperature rise in case of adiabatic operation 550 ◦ C, a sharp carbon profile is established and an outer C-free The adiabatic temperature increase (for a steady state process) shell is formed. is given by: The pronounced development of a carbon-free outer shell for cO2,in R H temperatures of more than 500 ◦ C is also reflected by photographs

Tad = (19) g cp,g of the cross-section of the partly regenerated Al2 O3 particles (Fig. 5). The “white” shell indicates the outer carbon-free zone, which is clearly not established in the case of relative low tem4. Results and discussion peratures of 400 and 450 ◦ C. Again note that in all samples 50% of the coke was burned-off. 4.1. Coke burn-off within a single particle The measured correlations of the coke load and the impedance for regeneration temperatures of 390 ◦ C and 520 ◦ C are shown The radial profiles of the carbon load within a particle durin Fig. 6, i.e. for the case of almost no and strong limitation by ing burn-off calculated by the numerical simulation and the pore diffusion. In both cases, the disruption of continuous convalues measured by SEM/EDX are shown in Fig. 5 for differductive coke paths by the oxidation process rapidly increases the ent regeneration temperatures and the example of a burn-off

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Fig. 7. Absolute value of impedance |Z| versus electrical resistance R (left) and carbon load LC versus R (right).

impedance, but this effect is much more pronounced for the lower regeneration temperature. As shown by the respective phase diagram (see also [14]), the change of the impedance signal can be explained as follows. As long as several continuous carbonaceous paths are still present, ohmic behavior dominates. When a value of the impedance |Z| of 105  is reached, more and more of the remaining conductive paths are disrupted, and the phase signal starts to shift strongly from ohmic (phase ϕ = 0◦ ) to a capacitive behavior (ϕ → −90◦ , Figs. 6 and 7). Finally, the particle almost behaves like a capacitor. At the lower regeneration temperature, where the carbon is evenly distributed throughout the pellet during the burn-off process, the impedance signal is higher for a given degree of coke burnoff. For instance at a residual coke load of 7 wt%, a value of |Z| = 105  is reached at 390 ◦ C whereas for 520 ◦ C the corresponding value is only 102 . In other words, ohmic behavior is still dominant for 520 ◦ C, whereas at a low temperature the particle already starts to behave like a capacitor. Vice versa, for a constant value of |Z| of 105 , which represents the crossing from ohmic to capacitive behavior, a residual coke load of 7 wt% is reached at 390 ◦ C whereas for 520 ◦ C the corresponding value is only about 4 wt%. This behavior can be explained by a simplified equivalent circuit diagram. As shown in Fig. 5, (internal) diffusion limitations strongly influence the effective reaction rate at 520 ◦ C, whereas the reaction is still kinetically controlled at about 390 ◦ C. In the latter case, the coke load is locally still almost constant and decreases uniformly during the regeneration. In the case of a strong influence of pore diffusion (520 ◦ C), an outer shell free of coke and a core region still rich in carbon are established. If we consider the conductive coke paths as resistors, we have a parallel circuit of many resistors. For illustration, this is indicated in Fig. 6 for simplification by just two parallel resistors. At 420 ◦ C, these two resistors have the same relatively high resistance as the coke load decreases with time but not with the local (radial) position (case A in Fig. 6). Thus, the total resistance is still high (Rtot = R1,A /2 = R2,A /2). For 520 ◦ C (case B in Fig. 6), we get a parallel circuit of a resistor with a very high resistance (carbon-free shell, R1,B ) and a second with a very low resistance (R2,B ) representing the core region which is still rich in carbon. Thus the total resistance now equals R2,B which is much lower than the total resistance of case A. This simple model may explain the influence of the regeneration temperature on the impedance. Two main conclusions may be drawn from the experiments with the sensor with regard to monitor the coke burn-off within a single coked catalyst particle: It is possible to monitor the change of the residual coke load and (at least qualitatively) also to distinguish how strong the decoking of a single particle is influenced by pore diffusion.

In addition to the experiments with the Al2 O3 catalyst presented in this work, similar studies were done with a metal catalyst (Cr2 O3 /Al2 O3 ). The results (sensor signals versus coke load) are similar and indicate that the presented method is also suitable to monitor the coking/decoking behavior of other catalysts (details in [14]). 4.2. Regeneration of a coked fixed bed (coke burn-off) Fig. 8 depicts the courses of the temperature increase T, the concentrations (CO, CO2 , O2 ) and of the signal of all five sensors (resistance) with time during coking and decoking in the lab-scale fixed bed reactor. The conditions are given in Table 2.

Fig. 8. Courses of resistance R, increase of temperature T, and of the content of CO, CO2 , O2 during coking (0 < t < 49 h) and decoking (t > 49 h) (TReg = 550 ◦ C, Tcoking = 600 ◦ C, coke precursor propane (50% in N2 ), for other conditions see Table 2). Table 2 Reaction conditions and data on chemical media of the fixed bed decoking experiment (all values are given for 550 ◦ C and 1 bar). Mean temperature Initial carbon load, LC,0 Superficial gas velocity, ue Inlet oxygen concentration, cO2,in Effective rate constant, km,eff Reaction enthalpy of coke burn-off, R H Porosity of fixed bed, ε Heat capacity of gas, cp,g Heat capacity of solid catalyst, cS Bulk density of catalyst bed, b Density of gas, G

550 ◦ C 0.16 kgC kgcat −1 0.028 m s−1 0.58 mol m−3 (4 vol%) 0.03 m3 kg−1 s−1 (Fig. 4) 393 kJ mol−1 0.4 30 J mol−1 K−1 1000 J kg−1 K−1 770 kg m−3 14.5 mol m−3

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Fig. 9. Details of Fig. 8: course of the resistance detected by sensor 4 (left) and of the temperature difference detected by the sensors 4 and 5 during regeneration (right).

The resistance of the sensors, which were axially evenly distributed along the fixed bed, is a measure for the carbon load. At first, the catalyst was loaded with coke by passing a mixture of nitrogen and propane over the bed (0 < t < 49 h). During this period, the resistance R of all sensors strongly decreases until a final value of about 10  is reached. Thereafter the regeneration was started by passing a mixture of oxygen (4%) in nitrogen over the bed (t > 49 h). After an initial period of about 10 h, a reaction zone is formed that moves through the bed. Table 3 (middle column) summarises the values of the velocities of the reaction and heat front and of the length of the reaction zone as determined by the Eqs. (16)–(18). The heat losses of the lab-scale reactor were large and so the reactor was almost isothermal and by far not adiabatic (Fig. 8 and Table 3). Based on the values of the electrical resistance and temperature, which were measured at five different axial positions along the fixed bed (distance of 5 cm between each sensor), the three main parameters that determine and characterise the regeneration process is derived by the electrical sensors as follows (see Fig. 9). The velocity of the reaction front is derived by the time elapsed until two consecutive sensors ( tsensor, ) located in a distance

Lsensor detect the same resistance (e.g. 104 ) and thus the same residual coke load: uRF =

Lsensor

tsensor,

(20)

According to Fig. 8, tsensor, is about 9 h (sensors 3–5, i.e. after the initial period of the regeneration) and the distance between two sensors is 5 cm. Thus, Eq. (20) leads uRF = 0.6 cm/h. The velocity of the heat front is derived by the time elapsed until the temperature detected by the sensors in the rear part of the bed to circumvent the initial phase of regeneration (here no. 4 or 5), which is located in a distance of Lsensor in axial direction (22.5 cm for no. 5 and 17.5 cm for no. 4), starts to increase ( tsensor ): uHF =

Lsensor

tsensor

(21)

As shown in Fig. 9 (right), tsensor is 5 h for sensor 5 and 17.5 h for sensor 4, and in both cases Eq. (21) leads uHF = 4.5 cm/h. The length of the reaction zone is derived by the velocity of the reaction front (Eq. (20)) and the time elapsed until the resistance measured by the sensor (e.g. no. 4) has increased from the initial to the final value (see Fig. 9, right). For a resistance of less than about 10  and of more than 100 k, which corresponds to carbon loads of 10% and 4%, respectively, the accuracy of the DC measurement and of the derived resistance is limited. Thus, the time elapsed between 10  and 100 k is used and the ratio of the initial load to the difference in the detectable difference in carbon load is used as the weighting factor: LRF =

uRF (t100 k − t10



 ) LC,0

LC,10  − LC,100 k



= 2.7 uRF (t100 k − t10  )

(for LC = 0.16 wt-%)

(22)

According to Fig. 9 (left) t100 k − t100  is about 6.5 h and with uRF = 0.6 cm h−1 and LC,0 = 0.16 Eq. (22) leads LRF = 10 cm. Table 3 shows that the agreement of the calculated values of uRF , uHF , and LRZ with those deduced from the measurements with the electrical sensors is very satisfying. Based on the course of temperature and electrical resistance with regeneration time, which was measured by the sensors at five different axial positions, the axial profile of the electrical resistance in the fixed bed reactor (and thus of the local carbon load) at different fixed regeneration times were estimated (Fig. 10). By this figure, the length of the reaction zone as well as the velocity of the reaction front is directly deduced (and much easier and more evident than from the R versus time diagrams shown in the Figs. 8 and 9). The length of the reaction zone (about 10 cm) can be derived from the curve at a regeneration time of for example 10 h, and the velocity of the reaction front by the reactor length that is passed by the carbon load profile in a certain time, e.g. between 20 and 30 h (see Fig. 10). It should be finally noted that one may argue that the regeneration experiment in the lab-scale fixed bed reactor substantially

Table 3 Parameters of the fixed bed decoking experiment: comparison of calculation and measurement with the electrical sensors. Parameter

Calculation (Eqs. (16)–(19))

Value derived by electrical sensors (Eqs. (20)–(22))

Unit

Velocity of reaction front Velocity of heat front Length of reaction zone Adiabatic rise in temperature

0.6 5.8 7 524

0.6a 4.5 10 13b (see Figs. 8 and 9)

cm h−1 cm h−1 cm K

a b

Mean value of sensor 2–5. The lab-scale reactor was by far not adiabatic, but almost isothermal.

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The coke burn-off within a single coked catalyst particle can be monitored, and it is also possible to distinguish whether and how strong the decoking is influenced by pore diffusion. For a fixed bed, the axial coke profile can be easily monitored by means of axially distributed sensors, and the velocity of the reaction front and the length of the reaction zone are directly deduced by the local change of the coke profile, which corresponds to the sensor resistance, with time. If the sensors are also equipped with thermocouples, the velocity of the heat front is also detected. Fig. 10. Resistance R versus length of fixed bed reactor.

differs from the regeneration of a technical fixed bed reactor: (1) adiabatic operation was not reached (substantial heat losses), (2) the velocity of the gas was by a factor of at least 10 lower compared to industrial operation [11], (3) the length and diameter are by at least one order of magnitude smaller, and bypass effects may not be excluded in the lab-scale reactor, because the ratio of the reactor diameter to the particle diameter was small (about 7). All of these objections are true, but the aim of this work was not to come to general conclusions how a technical regeneration process can be optimised or to deduce the exact values of the velocity of the reaction front or of the length of reaction zone. The aim of this work was to present a new technique to measure these parameters in situ. And if this is possible in a lab-scale reactor – as shown in this paper – there is no indication that this is not possible in any (technical) reactor. 5. Conclusions The electrical single particle sensor presented in this work is suitable to monitor the coke load of catalyst particles during and decoking (burn-off), as demonstrated by experiments with an Al2 O3 catalyst. This sensor could be used as a controlling instrument of high value, and consists of a single catalyst particle, which is electrically contacted and characterised by impedance spectroscopy. A clear relationship between coke load and the impedance is observed. The sensor was tested by regeneration experiments with single particles and in a coked lab-scale fixed bed reactor, which show a good agreement of measured and calculated values.

Acknowledgements Financial support by the Deutsche Forschungsgemeinschaft (MO 1060/5 and JE 257/12) is gratefully acknowledged. The authors also wish to thank SÜD-CHEMIE for supplying the Al2 O3 catalyst, an Ingrid Otto from the Chair of Materials Processing of the University Bayreuth (Prof. M. Willert-Porada) for the SEM/EDXmeasurements. References [1] J. Hagen, Industrial Catalysis, first ed., Wiley-VCH, Weinheim, 1999. [2] G. Ertl, H. Knözinger, J. Weitkamp, Handbook of Heterogeneous Catalysis, vol. 4, first ed., Wiley-VCH, Weinheim, 1997. [3] C. Kern, PhD Thesis, University of Bayreuth, 2003. [4] G. Ertl, H. Knözinger, J. Weitkamp, Handbook of Heterogeneous Catalysis, vol. 3, first ed., Wiley-VCH, Weinheim, 1997. [5] J.F. Le Page, Applied Heterogeneous Catalysis: Design, Manufacture, Use of Solid Catalysts, Éd. Technip, Paris, 1978. [6] J.A. Moulijn, Chemical Process Technology, Wiley-VCH, Weinheim, 2001. [7] G.F. Froment, K.B. Bischoff, Chemical Reactor Analysis and Design, second ed., Wiley-VCH, New York, 1990. [8] M. Ishida, C.Y. Wen, AIChE J. 14 (1968) 311. [9] Y.C. Wen, Ind. Eng. Chem. 60 (1968) 34. [10] N. Müller, R. Moos, A. Jess, Chem. Eng. Technol. 33 (2010) 103–112. [11] C. Kern, A. Jess, Chem. Eng. Sci. 60 (2005) 4249–4264. [12] K.R. Westerterp, H.J. Fontein, F.P.H. van Beckum, Chem. Eng. Technol. 11 (1988) 367–375. [13] D. Tang, C. Kern, A. Jess, Appl. Catal. A: Gen. 272 (2004) 187–199. [14] N. Müller, A. Jess, R. Moos, Sens. Actuators B 144 (2010) 437–442. [15] N. Müller, PhD Thesis (in preparation), University of Bayreuth, 2010. [16] D. Tang, PhD Thesis, RWTH Aachen, 2004. [17] E.-U. Schlünder, Einführung in die Wärmeübertragung, F. Vieweg & Sohn, Braunschweig/Wiesbaden, 1986. [18] G. Eigenberger, Dynamik und Stabilität verfahrenstechnischer Prozesse, Chem. Ing. Technol. 55 (1983) 503–515. [19] G. Emig, H. Hofmann, U. Hoffmann, U. Fiand, Chem. Eng. Sci. 35 (1980) 249–257. [20] E. Wicke, D. Vortmeyer, Ber. Bunsenges. Phys. Chem. 63 (1959) 145–152.