NH 3 adsorption/desorption modeling in a fixed bed reactor

Transcription

1 NH 3 adsorption/desorption modeling in a fixed bed reactor Abstract Ana Rita Morgado Prates morgado.prates@gmail.com Instituto Superior Técnico, Lisbon, Portugal/ IFP Energies Nouvelles Supervisors: Prof.ª Maria Filipa Gomes Ribeiro (IST) Dr. David Berthout (IFPEN) September 2014 The Selective Catalytic Reduction of NO x with ammonia is one of the most promising deno x technologies for diesel vehicles. Metal exchanged zeolites are gaining increasing attention due to their high deno x performance over a broad range of operation conditions, namely narrow pore zeolites as ZMS-5 and others. The storage of NH 3 is a key step of the overall process, and compromises the SCR performance. The present work presents an improved model to describe NH 3 adsorption and desorption on H-ZMS-5. The objective is to find the most appropriate approach to describe diffusion and chemical kinetics phenomena within a catalyst, porous media. A model developed in IFP Energies nouvelles was used for simulate given NH 3 TPD experiments in fixed bed. The model results are compared with experimental data and moreover, some model improvements are suggested, concerning the analysis of the results. The experimental data evidence intraparticle mass transfer resistance due to certain parameter variation such as heating rate and inlet flow rate. It is already known from the literature the importance of this phenomenon on narrow sized pore zeolite. The linear driving force approximation is suggested as modeling approach to describe internal diffusion resistance within the zeolite. Experimental data also show a big influence of the amount of Al in the NH 3 storage capacity, as well as acid strength. Some mathematical relation between Si/Al ratio and storage capacity is suggested as model computation, but results are not accurate enough. To complement these conclusions and optimize the model, more experimental data are requested, and also a study of the zeolite s acidity. Keywords: NH 3 SCR, NH 3 TPD, Mass transfer, mathematical modeling, zeolites 1. Introduction Emissions from the combustion of the fossil fuel contain nitrogen oxides (NO x) responsible for acid rain, photochemical smog and intensification of ground-level ozone. An efficient way to reduce nitrogen oxides, is to apply selective catalytic reduction of these oxides with ammonia (NH 3 SCR) (1). There are several reactions that can occur during between NO x reduction with NH 3. Therefore, the basic reaction also known as standard SCR is described below :[] 4NH 3 + 4NO + O 2 4N 2 + 6H 2 O 1 The reaction between NH 3 and NO x occurs continuously on the surface of a catalyst, due to the adsorption of NH 3 on the catalyst acid sites. The system of NOx removal, typically is controlled by SCR in a called monolithic catalytic converter, which consists of a monolith encased in a metal can. Inside this structure there is a honeycomb type ceramic substrate in which the catalytic material is impregnated as a washcoat. The literature presents several modeling approaches for the SCR in a monolithic catalytic converter. One-dimensional (1D) simulations have become the de facto standard for modeling monolithic catalytic converters (2). Recent studies (3)present the expansion of the classical 1D model into a 1+1D model, allowing a better simulation of chemical reaction within the washcoat. In order to reduce packaging volume and costs, the combination of a NH 3 Selective Catalytic Reduction (SCR) on a diesel particulate filter (DPF), presents to be a promising alternative to the monolith catalytic converter, due its higher efficiency of emissions reduction (4). The available literature (4) presents a 1D model for this kind of device,which can be further used to explore a wide range of catalyst and system scenarios. There are several catalyst investigated for this application. Among SCR catalyst already proposed and explored, metal exchanged zeolites seem to be a promising alternative due to their high deno x performance in a wide range of operating conditions. Narrow pore zeolites such as MOR, FER, BEA and MFI exchanged with a transition metal as Fe, Cu, Cr and Ag have proven to be very suited for SCR (1). Fe-ZSM-5 was one of the first studied and presenting high stability and activity in NH 3 SCR, exceeding V 2O 5- WO 3-TiO 2. Cu exchanged zeolites also present high activity, although low hydrothermal stability and high NH 3 oxidation (1). Recently, it was proven that Cu-

2 SSZ-13, a zeolite with the Chabazite structure and containing small radius (~3.8 A) eight-membered ring pores, is more active and selective for NH 3 SCR than other copper changed species (5). Several models can be found in literature applied to the different referred catalysts. Olsson t al presents several SCR NH 3 models over Cu-ZMS-5, as the one acid site approach (5), or the multi acid-site approach (6) between more complex developments (7). The storage and release of NH 3 is the key step of the SCR technology and compromises the efficiency of the whole process. Ammonia is adsorbed in the zeolite acid sites which are inside the pore network. The strength and nature of the acid sites are still a matter of discussion and study. Colombo et al (8)presents a model of NH 3 adsorption/desorption over Fe-zeolite suggesting two main acid sites: Bronsted acids sites, where ammonia is strongly adsorbed, and Lewis acid sites, where ammonia is weakly adsorbed. Moreover, diffusion phenomena inside the pore network control the local concentration of the reactants at the active sites, which will have a determinant role in catalyst activity. Studies (9) report the presence of significant intraparticle mass transfer resistance on H-ZMS- 5 for instance. Concerning the necessity to minimize NO x emissions and achieve the future legal requirements of transport emissions, post-combustion treatment technologies are extensively studied, in order to find the most efficient system. Models are developed in order to represent the actual behavior of a system, hence the use of models helps understanding and optimization of process efficiency. The use of small pore size zeolites in the NH 3 SCR process implies a deep knowledge of the diffusion phenomena to understand the possibilities and limitations of this process. This report describes the study and development of a given model for adsorption and desorption of NH 3 on H- ZMS-5 on a fixed bed reactor. ZMS zeolite is one of the most studied zeolites for SCR technology, allowing the study of diffusion phenomena over a small pore size zeolite. Pragmatically, modeling fixed bed reactors leads to a concrete study of the diffusion and kinetic process within the washcoat, which is the main challenge as a catalyst modeler and for SCR modeling. The main objective for an acceptable model is considered to be its ability to reasonably explain the observed qualitative characteristics of mass transport, temperature and pressure profile. To this end, several experiments were performed in fixed bed reactor and each different phenomenon was evidenced. An initial IFPEN model was adapted to case study and used for simulate given experimental data. The model results are compared with experimental data and moreover, some model improvements are suggested, concerning the analysis of the results. 2. Material and methods 2.1. Experimental Temperature programmed desorption is a wellknown technique for characterization of heterogeneous catalysts acidity. Basically, after the basis adsorption in the catalyst, the sample temperature increases constantly forcing desorption at continuously higher temperature (10). In this work, the NH 3 TPD experiments were conducted using a Micromeritics, Autochem II 2920 in a fixed bed reactor, with a zeolite bed of H-ZMS-5 (MFI), in order to study NH 3 adsorption/desorption process and diffusion The catalysts were prepared using H-ZMS-5 powder pelletized in grains, with different silica alumina ratios. Each type Si/Al ratio zeolite was pelletized into grains with different diameter (on order of µm). Bigger grains (on order of mm) of SiC were introduced to the fixed bed in order to normalize the pressure drop. SiC is an inert, hence does not interfere with NH 3 adsorption/desorption. For the actual experiments, the feed mixture contained 10%(v/v) of NH 3 in N 2 as a vector gas. The adsorption step occurs at 150 C and desorption step increases until 600 C. Highly sensitive linear thermal conductivity detector (TCD) reads conductivity variations of the outlet and inlet flow of the sample reactor, which allows calculating concentration. It assures the calibration volume remains constant over the full range of peak amplitudes so the area under the peak is directly proportional to the volume of gas reacted. Outlet temperature and pressure profiles were also available. There were performed two sets of experiments, study 1 and study 2. For the study 1, a series of experiments were conducted using H-ZMS-5 with silica alumina ratio of 15, with an average particle size of µm, while some operation conditions were changed. Study 1 aims to evaluate adsorption temperature, test 1, heating rate, test 2, and flow rate effects, test 3. Each test comprises one single parameter variation, as the other condition parameters remain approximately constant for a proper analysis, as shown in Table 1. For study 2 experiments were carried out to investigate the impact of Si/Al ratio of the zeolite. Six experiments were performed at different Si/Al ratio, (between 11.5 and 500) while all the other operation parameters were kept approximately constant, as shown in Table 2 Table 1 - operation condition for test 1, adsorption temperature effect, test 2, heting rate effect and test 3, flow rate effect Data File Zeolite sample(g) Flow rate (ml/min) Tad ( C) Desorption heating rate ( C/min) SiC (g) Bed depth (cm) Pression Max (Pa) T3 T1 E , ,50 1,92 E , ,50 2,15 E , ,50 2,00 E , ,50 2,31 E , ,50 2, , , , , ,1 T2

3 Table 2- operation conditions in the experiments performed for study 2 Si/Al ratio Data File Zeolite sample(g) SiC Bed depth (g) (cm) pressure (Pa) Flow rate (g/s) 11.5 E ,20 1,50 1, , E ,20 1,50 1, , E ,19 1,50 2, , E ,19 1,50 1, , E ,21 1,50 1, , E ,20 1,50 1, , Model description The reactor model In the given model, the fixed bed reactor is described as heterogeneous CSTR model. The main assumptions made for the reactor model are: no gas phase accumulation and no diffusion resistance, which means all sites are immediately available and there is no radial concentration gradients inside the zeolite grains. Deviations from the ideal state were not considered. The model does not take into account the presence of impurities existing in the zeolite. For the thermal description of the system it was considered that there are no heat exchanges with external systems, so it is considered adiabatic. Temperatures in gas and solid phase (T g and T s respectively, in K) are deduced through respective 0D balances, presented in equation 2 and 3 respectively. dt g dt = m ih i + dq conv dv g P dt g dt m g dx i dt u i dm g dt C 2 vdt m g C v dt s dt = Q exchanged + Q wall FB mass CpCC Q exchanged = 2.89 k 6 V total V free (T D part D g part 4 T s ) The balance heat in the gas phase is based on the 1 st law of thermodynamics, of conservation of energy, where is considered convection between gas and solid phase (Q conv in J). Regarding the nomenclature shown, m i(kg), x i (fraction), h i and u i (J/kg) stand for the i th species mass, mass fraction, specific enthalpy and internal energy respectively. Moreover, m g (kg), V g (m 3 ) and P g (Pa) account for gas mixture mass, volume and pressure respectively. The heat balance in the solid phase, takes into consideration the exchanged heat between the gas and solid phase (Q exchanged ). Heat exchange between the reactor and the surroundings, (Q wall) which is neglected so Q wall 0. Further, reaction heat is neglected and the, fixed bed heat capacity, CpCC, is considered constant and FB mass stands for the fixed bed mass. Concerning the nomenclature shown in equation 4, k (W m -2 K -1 ), D part (m), V total (m 3 ) and V free (m 3 ) stand for thermal conductivity, particle diameter, total fixed bed volume and free volume respectively. 3 stands for flow rate for component I, and outlet and inlet flow rate respectively. Moreover, x iout and x iin correspond to the outlet and inlet mass fraction of the i th species, and w i the variation of i th species amount (kg s -1 ). df i dt = x iout F out + x iin F in + ω i 5 In the present study there is only formation and disappearing of NH 3, which corresponds to the adsorption and desorption of NH 3 in the catalyst, as it is defined in the following kinetic model. The gas velocity, v (m s -1 ) is computed according to laminar Ergun s equation 6, taking into account the pressure drop through the fixed bed, P g P out (Pa), the particle diameter D p (m), the fixed bed length L (m), the gas viscosity µ(n s m -2 ) and the fixed bed void fraction, ɛ. v = (P g P out )D p 2 L 150 µ ε 3 (1 ε) 2 6 In order to adequate the IFP given model to this study, there was added a D p computation to take into account the granulometry of the fixed bed of the performed experiments. Hence, two model parameters were included: the average inert grain diameter, D inert, and the average zeolite grain diameter, D zeolite. The average particle diameter D p is computed concerning the relative amount of SiC grains with D inert, and the relative amount of zeolite grains, with D zeolite. as shown in equation 7 D p = M cat FB mass D zeolite + FB mass M cat FB mass D inert Where M cat refers to the mass of zeolite used The kinetic model The double site approach is reported in several studies like, (6)and (9) where ammonia storage is modeled over two kinds of active sites, S1 for weak adsorption of ammonia on the zeolite and S2 for strong adsorption. The given kinetic model is a first-order non-activated adsorption and an activated desorption kinetics. Previous studies, (6), suggest desorption activation energy defined as a coverage dependent, α, by a Temkin approach. The rate constants are described by the Arrhenius expression, for each site (j), equation 8 k j = A j e E aj/rt 8 7 The mass balance for each gas component (i) is presented by the following equation 5, in which F i, F out, and F in (kg s -1 )

4 A j (m 3 mol -1 s -1 ) accounts for the adsorption or desorption pre-exponential factor, E aj (J mol -1 ) for the respective activation energy, R (J mol -1 K - 1)as the ideal gas constant, and T (K)the solid phase temperature. For activated desorption kinetics, activation energy E aj is dependent of the surface coverage, and is given by equation 9: E aj = E aj0 (1 α j θ j ) 9 E aj0 stands for the activation energy of desorption when the surface coverage equals to zero, and last, θ is the percentage of the occupied surface sites. The reaction rates of adsorption and desorption for each acid site S1 and S2 are listed in Table 3, where C NH3 is the NH 3 gaseous concentration in mol/m Simulation Taking into consideration the previous conditions and models, the following sketch was created in simulation environment LMS.Imagine.Lab AMESim using IFPEN-Exhaust Library.Figure 1 illustrates the used sketch. The inlet conditions are divided by the temperature subunits at the top, mass flow unit, and inlet flow rate composition. In the inlet conditions subunits, k subunits are used for constant parameters, such as mass flow, the conversion of C to K, and the mass fraction of the different components 1, 3, 4, 5, 6, 7, 8, 9, 10 and 12, which is zero All the other subunits are used for non-constant parameters, such as temperature and inlet NH 3 and N 2 mass fraction, which depends in of the TPD stage. The reactor subunit receives all the reactor, kinetic and heat transfer parameters. The analyzers subunits, before and after the reactor, give information about the properties of the respective flow. Although in the present work it is only studied NH 3 adsorption and desorption, the inlet conditions are ready to simulate a complete exhaust gas flow rate, for possible future studies. The model input parameters are inserted in each subunit respectively. The inlet conditions as for the reactor parameters are given from the experimental procedure. The heat transfer was found by varying and choosing the value that most fitted to the experimental temperature profile results. Finally, for the kinetic parameters required for the calibration of the kinetic model were extracted from available literature on sorption and diffusion of NH 3 in H- ZMS-5 (6). 3. Results For each simulation, mass, heat and pressure profiles were obtained and compared to the experimental data. In order to achieve the best fitting, kinetic and heat parameters were manipulated taking into account available kinetic parameters in the literature. For all simulations, pressure and temperature profiles present coherent results For each simulation, mass, heat and pressure profiles were obtained and compared to the experimental data. In order to achieve the best fitting, kinetic and heat parameters were manipulated taking into account available kinetic parameters in the literature. For all simulations, pressure and temperature profiles present coherent results comparing to the experimental data. Moreover, double site approach seems to well describe the experimental TPD curves. Figure 1- AMESim sketck Table 3- rate expressions for NH3 adsorption and desorption on S1 and S2 Adsorption Rate of S1 mol/(mol sites1.s) r ad1 = A ad1 C NH3 (1 θ 1 ) Desorption Rate of S1 Mol/(mol sites2.s) r des1 = A 0des1 exp ( E a01des R T (1 α 1θ 1 )) θ 1 Adsorption Rate of S2 mol/(mol sites1.s) r ad2 = A ad2 C NH3 (1 θ 2 ) Desorption Rate of S2 mol/(mol sites2.s) r des2 = A 0des2 exp ( E a02des R T (1 α 2θ 2 )) θ Study 1

5 Figure 2- test1: NH3 mol fraction vs temperature during desorption Figure 3-test2: NH3 mol fraction vs temperature during desorption Figure 4 - test3: NH3 mol fraction vs temperature during desorption For test 1, Figure 2 the adsorption was conducted at either 100 C (E11-092) and 250 C (E11-093). As expected, adsorption temperature of 250 C provides enough energy to cause NH 3 immediate desorption on the weakly bounded sites. As a result, adsorption at 250 C (E11-093) show only the strong bounded Bronsted site peak. Simulated results present a similar response, Simulated results still present a small weak adsorption peak, probably because the input E ades1 parameter is higher than the real one. A more rigorous fitting would allow finding better values. Concerning heating rate effects, Figure 3 for higher heating rate, 10 C/min, the amount of desorbed NH 3 increases comparing to 5 C/min, since the system receives more energy allowing a more effective desorption as expected. Moreover, at higher heating rates the desorption maximum is slighted shift to a higher temperature, especially for the weak acid site, in which the maximum temperature adsorption difference is 20 ºC, as shown in Table 4. This behavior is often attributed to intraparticle mass transfer limitations, (9), although the difference is not very predominant. The model seems to well describe experimental data, though intraparticle mass transfer limitations are not assumed by the model. the maximum adsorption temperatures are quite similar. Table 4 - test2:temperature of max. desorption for exp. data and simulated resutls Exp data Simulated results Peak Max Temp (K) Max Temp (K) E11-89 S1 525, , S2 732, , E11-90 S1 505, , S2 726, , Regarding flow rate effects, Figure 4, although the NH 3 storage capacity is the same for both E and E11-089, it is expected that the corresponding TPD do not show the same coverage area, once the flow rates are bigger the NH 3 molar fraction is smaller. However, experimental results show that the desorbed amount of NH 3 at 50L/min is substantially smaller for simulated results. The model presents a difference of maximum mol fraction of 0,0046 (NH 3 mol fraction) for S1 and 0,0033 for

6 S2, while that for experimental results this differences are about 0,0056 and 0,0023 respectively,table 5. Table 5- test3: difference between the maximum mol fraction of NH 3 desorbed of exp. Data and simulated results, for each peak S1 and S2 S1 (max NH 3 molfraction) S2 (max NH 3 mol fraction) exp results Simul. resutls 0,0056 0,0046 0,0030 0,0033 This incoherency is a clearly evidence of intraparticle mass transfer, once at higher flow rates the amount of NH 3 per unit of time is higher and consequently the internal diffusion resistance is bigger, as the concentration at the surface. Hence the amount of NH 3 is lower, and the TPD area is smaller. Besides the curves area, both experimental and simulated TPD curves present a similar behavior 3.2. Study 2 As mentioned before, for this study, seven experiments were carried out with the same operational parameters. However, each experiment used a zeolite H- ZMS-5 with a different Si/Al ratio. obtained TPD curves show not only a decrease of storage capacity, as the curve area decrease, but also a slightly shift of the desorption maximum to a lower or higher temperature, as shown in Table 7. This phenomena clearly shows a variation of acid strength, which may be related. It is well known that Si/Al ratio effects strength of protonic sites of zeolites, in such a way that the presence of neighbors (protonic sites in the surroundings) decreases acid strength. Hence, the higher Si/Al, the stronger acid site, since the chances of having an alumina on the surroundings are lower. (1) This effect increases the acid strength, which can be reported between E11-99 (Si/AL 11.5) and E (Si/Al 15) for example. However, extraframework aluminum species (low Si/Al) increase acidity by interaction of bridging hydroxyl groups (Bronsted) and Lewis sites. Hence, low Si/Al, increase acid strength, which can be reported for E and E Moreover, it should be noted that each zeolite sample has a different average grain diameter as shown in Table 6. If internal diffusion resistance is significant, the respective TPD curves may be being delayed if the grain diameter is higher than the other. For instance, TPD curve for E11-099, presents the highest maximum desorption temperatures, and also coincides with the zeolite sample with higher mean grain diameter ( 1.29µm). There is no available information to clearly understand each effect contribution in each sample. Table 6- Average grain diameter for different samples of H- ZMS-5 Si/Al D zeolite (µm) Si/Al ratio 1,29 11,5 0, , ,19 25 Figure 5 - study 2: experimental desorption curves, NH3 mol fraction vs time The Si/Al ratio drastically influences the amount of available acid sites. As stated above, zeolite s protonic acidity comes essentially from hydroxyl groups bridging alumina and silica leading to Bronsted acid sites. Moreover, Lewis acid sites come from extraframework aluminum species, or defects in the crystal lattice, so it will depend on the amount of Al species available. Hence, the higher Si/Al the fewer available Bronsted and Lewis sites for NH 3 adsorption, decreasing NH 3 storage. The impact of this ammonia storage Ω1 and Ω2 decreasing can be clearly seen in Figure 5 andtable 9 and Table 10. It should be stressed out that the weak adsorption peak has a prevalent decrease as Si/AL ratio increases, comparing to the strong adsorption peak. The behavior suggests that Bronsted sites are rather formed than Lewis sites having a low amount of available Al. As the Si/Al ratio decreases, (low Si/Al ratios) there is more available Al to form Lewis acid sites. For more conclusive answers, it would be useful to subject the different zeolite sample to some analysis, in order to have more accurate information about the type and accessibility of the acid sites. At higher Si/Al ratio, TPD curves present some noise, such as for Si/Al ratio of 140 and 500. At this high ratios the adsorbed and desorbed amount of NH 3 is very low and probably near the sensor sensibility limit. The For simulate the experimental data presented above, firstly, the simulated results were fitted to E experimental data, which zeolite sample has the smallest Si/Al ratio (11.5). The suitable model parameters found for E were used for the rest of the experimental data fitting, except from the storage capacity of each site, Ω 1 and Ω 2. As expected, the model cannot predict the Si/Al effect on acid sites strength, although the difference is not very significant. As a result, TPD curves are slighted shifted from the simulated ones, since desorption activation energy has decreased. However, manipulating these four parameters, storage capacity, Ω 1, Ω 2 and desorption activation energy E ades1, E ades2, the model presents a satisfactory response. 4. Model Improvements The results obtained in the previous chapters provide some information about the accuracy of the model concerning the case study. From study 1, the model seems to well predict the experimental results. However, the small discrepancy regarded in test 3 evidences how the model deviations in case of internal diffusion resistance. Concerning study 2, the model well predicts the experimental data with an appropriate parameter fitting. Nevertheless, the experimental data show an evident relation between Si/Al ratio and NH 3 storage and E ades parameters. If this relation is found to be accurate enough, there might be a possibility to the given model predict NH 3 storage and E ades itself. To understand this kind of relation, it is essential to understand the type and relative amount of

7 acid sites and quantify the zeolite s acidity. Regarding the model specified in the previous chapters, various improvements could be made in order to expand and improve its use, and concerns mainly these three subjects: Diffusional resistance, Influence of Si/Al, Zeolite s Acidity Table 7- desorption maximum temperatures (K) peak A) Diffusional resistance E11-99 Si/Al 11.5 E Si/Al 15 E Si/Al 25 E Si/Al 40 E Si/Al 140 S1 511,92 525,6 507,6 512,2 481,4 S2 719,09 725,4 716,3 719,7 677,6 For the actual model, gas accumulation is neglected so df i/dt 0. The surface balances are given by equations 12,13 and 14. It Is assumed that there is no accumulation at the catalyst surface, so dc s/dt 0 The analysis of the previous results shows a considerable impact of diffusional resistance in kinetics and mass transfer. Moreover, previous studies reveal significant internal diffusion resistance in the ammonia-tpd system, playing an essential role in the construction of a kinetic model (9) As a matter of fact, H-ZMS-5 is a medium-small pore sized zeolite, which is a known factor for increasing diffusional resistance within the zeolite. Based on the previous arguments, it is reasonable to propose the introduction intraparticule mass transfer resistance. Including intraparticle mass transfer resistance in the given model, would be the first step of the modeling procedure. The second step will be to prove the models efficiency with some experimental data. Further experiments evidencing diffusion resistance should be performed in order to make a proper comparison: -Experiments testing zeolite diameters effect: internal diffusion limitations increase with the zeolite diameter. Experiments should try a wide range of grain diameter, concerning the range of grain diameters used in SCR technologies; -Experiments testing desorption heating rate for constant particle size: at higher heating rates, the TPD curve is slightly deviated to higher temperatures due to intraparticle diffusion limitations. Diffusional resistance may be computed in the model as it is presented below. As first approach, one may use the film model to describe the mass-transfer from the gas to the catalyst surface as it is described in (7). The mass transfer coefficient, k g (ms -1 ) can be calculated using the Sherwood, Sh, number according to: Sh = k gd p D eff 10 where D v(m) stands for the characteristic length. The effective diffusion coefficient D eff can be obtained from available literature (11) or correlations, as Fuller correlation for instance, as described in (7). Sherwood number is function of Reynolds and Schmitt number, and may be given by some empiric correlations for fixed bed reactors (12). As for the mass balance, it is presented by equation 11. Replacing equation 5 df i dt = x iout F out + x iin F in k g A(C C s ) 11 k g A(C C s ) + (N cat1 dθ 1 + N cat2 dθ 2 )m zeol = 0 12 N cat1 dθ 1 = r ad1 r des1 13 N cat2 dθ 2 = r ad2 r des2 14 The intraparticle mass transfer can be described by an effective diffusion model with the driving force being concentration gradient in the radial direction of a spherical particle (9) leading to a set of partial differential equations which may assume some complexity. As reported in (13)the first and widely used approximation for spherical sorbents, proposed by Glueckauf and Coates (1947), is the linear driving force (LDF) approximation. For adsorption of a spherical particle subject to a step change in the surface concentration, the LDF describes the adsorption rate being proportional to the difference between the surface concentration and the average concentration within the particle. The specific LDF expressions can be derived using Fickian diffusion model, Fickian diffusion/convection model or the dusty-gas model, the adsorption isotherm is linear or nonlinear and the intraparticle partial pressure profiles can be assumed parabolic or polynomials. In general, these expressions have the form of a system of ordinary differential equations for the vector of the average concentrations of the species and the vector of some other average concentrations (auxiliary variables) as it is described in (14). The right-hand side of the system has the compact form of the product of an LDF matrix and a vector of driving forces (differences) involving the average concentration in the pellet and the concentrations at the external surface. Generally, LDF approximations are based on the Fickian diffusion model, which is the simplest of all mass transport models. This may be first option for including the LDF approximation in the model developed in the current work. Afterwards, the model should be tested in order to evaluate its accuracy due experimental data. In the presence of intraparticle total pressure gradients, using the Fickian diffusion model may produce inaccurate results because Knudsen flow is underestimated and viscous flow is not taken into account. In that case, LDF approximation should approach Fickian diffusion/convection model, which uses Darcy s law to account for the viscous fluxes of the components or even dusty-gas model. The effective transport coefficients used in LDF approximation may be computed from the following equations, as suggested by (13). More correlations are available in the literature (15).

8 B)Influence of Si/Al B1) Influence of Si/Al on ammonia storage effect As it is known, and also based on the preliminary experimental results, it is evident that Si/Al has a significant effect on storage and acid site strength. Zeolite s protonic acidity comes essentially from hydroxyl groups bridging alumina and silica. The strong interaction of O with Al weaks OH bond, increasing the acid strength (Bronsted sites). Moreover, extraframework aluminum species also increase catalytic activity of zeolites (Lewis acid species) showing enhanced acidity through interaction of bridging hydroxyl groups. Therefore, the higher alumina amount the higher number of acid sites, hence higher storage. In fact, it is well noticeable the decrease of S1 and S2 storage with the increase of Si/Al, as it is shown in Figure 5. The variation of acid site storage with Si/Al ratio seams to reveal a consistent tendency. Using some of the available data of Ω1 and Ω2 of Si/Al of 11, 15 and 140, a tendency line was built to find a mathematical description of this behavior, with R squared of approximately and respectively Table 8. Table 8- expressions correlating Ω1 and Ω2 with Si/Al ratio, obtained from experimental data Ω1=f(Si/Al) Ω2=f(Si/Al) Y=-2E-04ln(x)+0,0009 R 2 =0,8357 Y=0,0075x -0,905 R 2 =0,8357 In order to evaluate the prediction these mathematical relations, the values of Ω1 and Ω2 were obtained for all the experiments (Si/Al ratios) and compared with the experimental ones.. Concerning Ω1, the expression results are far different from the experimental ones, which conclude that the expression is not trustful for an accurate prediction of Ω1 with Si/Al, as shown in Table 9. The achieved expression for Ω2, presents accurate results for low Si/Al, (11, 15 and 25) and high Si/Al of 14, as listed on Table 10. The previous results suggest that a descriptive model may be able to predict each site storage from the input parameter of Si/Al for the present case study. However, this prediction would be only reliable for low Si/Al and only for storage capacity of the Bronsted acid sites. In either case, in order to have an accurate mathematical expression for describe this behavior, more experimental data from different Si/Al ratios will be needed. If the predicted results well correspond to the experimental ones, the expression can be implemented in the model that from the new parameter Si/Al will compute Ω1, Ω2 or both. B2) Influence of Si/Al on acid strength Si/Al ratio has effects on the acid strength. regarding the variation of the maximum adsorption temperatures. However, and as it is referred before, the variation of E ades does not have a preferential tendency with SI/Al ratio, since as the ratio increases, the respective maximum desorption temperature increases or decreases almost randomly, as listed in Table 7. In fact, there are three main effects that explain this variation: (i) the presence of neighbors (protonic sites in the surroundings) decreases acid strength, which means that a higher Si/Al ratios, increases acid strength, (ii) extraframework aluminum species (low Si/Al) increase acidity by interaction of bridging hydroxyl groups (Bronsted) and neighboring small extra-framework aluminum species (Lewis sites), so high Si/Al ratio, decreases the acid strength. (ii) internal diffusion limitations, which play a bigger rule for higher grain diameter zeolites. The available data results do not give enough information to know which type of acid site is predominant in each peak, or which effect is predominant is each case. Firstly, it should be noted that each MFI Si/Al has a different average grain diameter. In order to have a proper comparison between the different Si/Al the zeolite grain diameter should be approximately the same. It has already been proven that internal diffusional are a significant phenomenon in MFI zeolite, which compromises the maximum desorption temperature (TPD curves are delayed). Moreover, further experiments and analysis should be done to help understand the predominant acidity in different Si/Al ratio (16). It should be noted that determining quantitatively acid sites strength is still a challenge and in fact, no satisfactory acidity scale for solids has been stablished. -Experiments with different Si/Al ratio, constant particle size: for truly compare Si/Al effects without zeolite size influence -Calorimetric studies of the adsorption of NH 3 : measuring the heat of adsorption and desorption heat -Ammonia TPD allows the determination of the number of acid sites, and its relative strength, moreover provides quantitative information on the distribution of acid sited strength in zeolites. -Temperature-programed desorption of probe molecules such as pyridine: study the type and accessibility and amount of acid sites -Infrared Spectroscopy: allowing the measurement of relative acidity of Bronsted sites -Infrared Spectroscopy measuring bands by the adsorption of basic probe molecules: giving information about the nature, amount, strength, density, microenvironment location and accessibility of acid sites -Solid-State Al MAS NMR: determination of the structure or the localization of alumina. Aluminum spectrum presents two distinct peaks corresponding to tetrahedral and octahedral structures, which corresponds to Bronsted and Lewis sites respectively.

9 Table 9 - Storage capacity for S1, comparison between the experimental and calculated value, for each Si/Al ratio sample Si/Al Ω1 model (µmol/g) 594, Ω1 exp (µmol/g) 510, ,51 126,73 126,73 %error 16, ,16 84,22 389,23 Table 10 - Storage capacity for S2, comparison between the experimental and calculated value, for each Si/Al ratio sample Si/Al Ω2 model (µmol/g) 856,25 573,43 368,25 244,99 82,69 -H MAS NMR technique can also provide information about the acidity of the zeolite, using H chemical shifts as the basis of an acidity scale. This parameter can be correlated with the proton donor ability of the corresponding site, in a way that higher acid strength indicates a proton more positively charged, and less shielded, which means higher chemical shifts. So far it has been possible to identify six distinct types of proton from the chemical shift value, refereeing to different types of acid sites, in different types of cavities. (17) The previous analysis would give information about the amount and type of each acid sites, Bronsted and Lewis, which would be very useful for understanding Si/Al consequences, relative storage capacity, etc. Moreover, the porosity repartition of a given zeolite is a important information concerning the accessibility of the acid sites and the available internal catalyst area. Commonly, textural characterization of porous solids is carried out by physical adsorption of gases. For instance, typical N 2 adsorption isotherm on H-ZMZ-5 leads to a Langmuir type isotherm, suggesting a predominant micro porosity and an internal surface area relatively small. Some studies (17) report the use of NH 3 TPD and 1 H MAS NMR to characterize the acid strength of H-ZMS-5. In this case, acid strength distributions of Bronsted sites have been determined by deconvolution of both spectra. The 1 H MAS NMR spectra is deconvoluted into Gaussian components using Fit2003 software of Massiot et al., from which results the chemical shift, identification and relative amount. It should be stressed out that the observations made may not hold for other H-MFI with different Si/Al. The TPD profile is deconvoluted into several components characterized by the number and strength of the acid sites. It is assumed that the desorption form the acid sites is irreversible and kinetically first-order, and that there is no interaction between two acid sites. Each individual components obtained correspond to a family of sites characterized by the same acid strength, from which it is possible to derive number os acid sites, desorption rate constant and the activation energy, E ades. In this case, for TPD acidity is defined by the E ades, while for 1 H MAS NMR acidity scale is based on the proton chemical shift. The authors (17) recall a relationship between the acidity and the H chemical shift, proposing a correlation between NH 3 TPD and 1 H MAS NMR results as the basis of an acidity scale for Bronsted acidic sites, namely a linear relationship between the activation energy for ammonia desorption, E ades and the 1 H NMR chemical shift. As expected, the equations predict that the heat of adsorption of ammonia and the chemical shift of the acidic proton increase with an increase of the hydroxyl hydrogen positive charge, i.e., acid strength. This correlations may open a Ω2 exp (µmol/g) 878,61 554,00 366,33 310,96 0 %error 2,55 3,51 0,52 21,21 0,0083 door for an acidity scale for zeolites, helping to predict their catalytic activity. Using the available TPD curves of this work and performing an 1 H MAS NMR, one would be able to predict the acid strength of a given zeolite, for a given Si/Al, as it is suggested in (17), and define a correlation between, E ades and H chemical shift. Improving the model requires not only a good approach, but also using the most convenient parameters. When developing kinetic models, the precision of used parameters is very important for the model reliability. In this case, one can use micro calorimetric results not only determining the adsorption heat, but also the coverage dependent activation energy parameter, α. In the available literature (18) it is presented a strategy to calculate the coverage dependent activation energy on H-ZSM-5, conducting an ammonia stepwise experience. This study describes all the experimental procedure and data treatment to determine this parameter. This procedure would confirm the kinetic assumptions assumed in the present model, and introduce also more accurate parameters. 5. Conclusion and Perspectives A fixed bed reactor model of ammonia adsorption and desorption has been analyzed and compared to experimental data. It has been shown that the model well describes the experimental data although it presents some limitations due to internal diffusional phenomena. The importance of this phenomena must not be neglected in this kind of technology and in this kind of zeolite, H-ZSM-5 (9). In fact, the experimental results evidence this kind of limitations (test 2 and test3 from study one), which is in accordance with previous studies of NH 3 adsorption/desorption on H-ZMS-5, noting the significant effect of the phenomenon. It is known that internal diffusion limitations are more prevalent in small pore zeolites. Moreover, as previously mentioned, small pore zeolites are the ones that seem more suitable for SCR technology. Recently it was reported (19) that a Cu-SSZ-13, a zeolite with the Chabazite structure is more active and selective for this technology comparing to other zeolites, which suggests that an SCR model should take into account this phenomena. The model used in this study should be improved in this way, and later one must prove its accuracy comparing to experimental data. Concerning the Si/Al ratio effect on NH 3 storage, it seems to be a dependent relation as shown in study 2.

10 Additional experiments are required to eventually find a mathematic model to well describe this relation, which will allow the storage capacity to be directly computed from Si/Al ratio. The effect of Si/Al ratio on desorption activation energy is still not clear, further experiments, as the ones performed for study 2, could be repeated, but using similar particle sizes, in order to avoid diffusional limitations effects. The analysis of the type of predominant acid sites for each Si/Al ratio would also help to understand these variations. The adsorption of NH 3 is one of the key steps of the SCR system. As such, it is important to well understand the acid sites concentration, type, strength and accessibility. Zeolite acidity characterization would be a valuable tool to understand the different zeolite acidity in different conditions namely the Si/Al ratio variation and the high temperatures the catalyst undergoes in an exhaust afte treatment system. Nevertheless, it would be valuable to test the accuracy of the final model towards other types of zeolites used in SCR technology, such as metal-exchanged ZSM-5 or Chabazite. It also should be interesting to improve the kinetic model in order to consider the complete exhaust gas composition and deno x reactions. 6. Bibliografia 1. Guisnet, M., Gilson, J-P.,. Zeolites for Cleaner Technologies Vol. vol Depcik, C., Assanis, D.,. One-dimensional automotive catayst modeling. Progress in Energ and Combustion Science. 2005, Vol. 31, pp Depcik, C., Srinivasan, A.,. One+One-Dimensional Modeling of Monolithic Catalytic Coverters. Chemical Engineering Technology. 2011, Vol. 34, pp Watling, T., Ravenscroft, M., Avery, G.,. Development, validation and application of a model for an SCR catalyst coated diesel particulate Filter. Catalysis Today. Vol. 188, pp Kwak, JH., Tran, D., Burton, S., Szanyi, J., Peden, H.F.,. Effects of hydrothermal aging on NH3 - SCR reaction over Cu zeolites. Journal of Catalysis. 2012, Vol. 287, pp Sjovall, H., Blint, R., Olsson, L.,. Detailed Kinetic Modeling of NH3 and H2O Adsorption, and NH3 Oxidation over Cu-ZSM-5. J. Phys. Chem.,. 2008, Vol. 113, pp Geiei, O., Vasenkov, S., Freude, D., Karger, J.,. PFG NMR observation of an extremely strong dependence of the ammonia self-difusivity on its loadings in H-ZMS-5. J. Catal. 2003, 213, pp Pinho, M., Prazeres, D.M.,. Fundamentos de Transferencia de Massa. [ed.] IST Press Cruz, P., Magalhães, F.D., Mendes, A.,. Generalized Linear Driving Force Aproximation for Adsorption of Multicomponent Mixtures. 2006, Vol. 61, pp Serbezov, A., Sortirchos, S.V.,. On the formulation of linear driving forc approximations for adsorption and desorption of multicomponent gaseous mixtures in sorbent particles. Separation Purification Technology. 2001, Vol. 24, pp Poling, B., Prausnitz, J.M, O'Connell, J.P.,. The properties of gases and Liquids Derouane, E.G., Védrine, J.C., Ramos Pinto, R., Borges, P.M., Costa,L., Lemos, M.A.N.D.A., Lemos. F., Râmoa Ribeiro, F.,. The Acidity of Zeolites: Concepts, Measurements and Relation to Catalysis: A Review on Experimental and Theoretical Methods for the Study of Zeolite Acidity. Catalysis Reviews: Science and Engineering. 2013, pp R.Ramos Pinto, P. Borges, M.A.N.D.A. Lemos, F. Lemos, J.C. Védrine, E.G. Derouane, F. Ramôa Ribeiro. Correlating NH3- TPD and 1H MAS NMR measurements of zeolity acidity: proposal of an acidity scale. Applied Catalysis A: General. 2005, Vol. 284, pp N.Wilken, K. Kamasamudram, N. W.Currier, J. Li, A. Yezerets, L. Olsson,. Heat of adsorption for NH3, NO2 and NO on Cu-Beta zeolite using microcalorimeter for NH3 SCR applications. Catalysis Today. 2010, Vol. 151, pp Kwak, JH., Tran, D., Burton, S., Szanyi, J., Peden, H.F.,. Effects of hydrothermal aging on NH3 - SCR reaction over Cu zeolites. Journal of Catalysis. 2012, Vol. 287, pp Srinivasan, A., Depcik, C.,. One-Dimensional Pseudo- Homogeneous Packed-Bed Reacyor Modeling: II. Energy Equation and Effective Thermal Conductivity. Chemical Engineering Technology. 2013, Vol. 36, 3, pp Sjovall, H., Bilnt, R., Olsson, L. Detailed kinetic modeling of NH3 SCR over Cu-ZMS , Vol. 92, pp Colombo, M., Koltsakis, G., Nova, i., Tronconi, E.,. Modelling the ammonia adsorption desorption process over an Fe zeolite. Catalysis Today. 2012, Vol. 188, pp Kouva, S., Kanervo, J., Schubler, F., Olindo, R.,. Sorption and diffusion parameters from vaccum-tpd of ammonia on H-ZMS- 5. Chemical Engineering Science. 2013, Vol. 89, pp Figueiredo, JL., Ramoa Ribeiro, F.,. Catálise Heterogénea. 2,