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High-throughput study of the influence of H2O and CO2 on the performance of nitrogen storage and reduction (NSR) catalysts
Applied Surface Science 252 (2006) 2588–2592 www.elsevier.com/locate/apsusc
High-throughput study of the influence of H2O and CO2 on the performance of nitrogen storage and reduction (NSR) catalysts R.J. Hendershot a, R. Vijay a, C.M. Snively a,b, J. Lauterbach a,* a
b
Department of Chemical Engineering, University of Delaware, Newark, DE 19716, USA Department of Materials Science and Engineering, University of Delaware, Newark, DE 19716, USA Received 8 December 2004; accepted 22 June 2005 Available online 3 October 2005
Abstract This paper describes the application of parallel high-throughput experimentation based on FTIR spectral imaging to a tolerance study for NOx storage and reduction (NSR) catalysts with respect to CO2 and H2O in the feed. It was found that both gases decrease the storage capacity of platinum/barium based NSR catalysts, with H2O having a stronger effect than CO2. # 2005 Elsevier B.V. All rights reserved. PACS: 82.65.J; 02.10.E; 82.80.C Keywords: High-throughput screening; Nitrogen storage and reduction (NSR) catalysts; FTIR imaging
1. Introduction Lean burn engines have been promoted as a method to improve the fuel efficiency of automobile engines [1]. Impeding the widespread implementation of lean burn engines is the inability of current three-way catalytic converters to reduce nitrogen oxides (NOx) under net-oxidizing conditions. NOx storage and reduction (NSR) catalysts were designed to store * Corresponding author. Tel.: +1 302 831 6327; fax: +1 302 831 1048. E-mail address: [email protected] (J. Lauterbach).
NOx during a fuel lean cycle and reduce the stored NOx during a subsequent fuel rich cycle [2,3]. Extensive research has been performed on NSR catalysts in the past decade to understand the storage and reduction mechanisms and improve overall NOx conversion [4–18]. Reaction conditions that were found to affect NSR catalysts include temperature, NOx concentration, O2 concentration, CO2 concentration, H2O concentration, reductant concentration, reductant type, space velocity, total lean/rich cycle time, lean/rich duty cycle, and the presence of sulfur. Obviously, the performance of NSR catalysts is also strongly influenced by the catalyst composition.
0169-4332/$ – see front matter # 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.apsusc.2005.06.041
R.J. Hendershot et al. / Applied Surface Science 252 (2006) 2588–2592
However, few studies were conducted under more realistic simulated exhaust gas with CO2 and/or H2O in the feed [8,12,15,19–21]. High-throughput experimentation (HTE) is increasingly being used for catalyst development [22,23] and is becoming a widely accepted tool, mainly among industrial researchers. In the research field of de-NOx catalysis, high-throughput techniques have been used to study selective catalytic reduction of nitric oxide using hydrocarbons [24–27]. One particular study looked at seven catalysts for NOx storage activity under a single reaction condition [27]. In this paper, we report the application of HTE to the study of the stability of NSR catalysts with respect to CO2 and H2O in the feed.
2. Experimental 2.1. High-throughput experimental setup and testing procedure All catalytic tests were performed using a 16 channel parallel reactor that is capable of acquiring data of comparable quality to that obtained from single reactor studies. Details concerning the reactor have been described previously [28]. Briefly, the flows across all the reactors are balanced using capillaries and the catalyst bed temperature is continuously measured for each sample. The reaction products from all 16 reactors were analyzed simultaneously using Fourier transform infrared (FTIR) imaging [29–33]. The optical setup consists of a Bruker Equinox 55 FTIR spectrometer interfaced with a 64 64 pixel mercury cadmium telluride FPA detector (Santa Barbara Focalplane, Goleta, CA, USA), and is capable of collecting IR spectra of the effluents from all 16 reactors in less than 2 s [34]. Details of the optical setup and analytical methods can be found in [23,29,33,35]. For quantification of the effluent gases in complex mixtures, standard chemometric techniques were adapted for spectral imaging data [36]. The performance of each catalyst was based on the NOx storage, defined as the integrated area between the inlet NOx concentration and outlet NOx concentration, in the fuel lean state, from time zero to the time when the outlet NOx concentration reached 300 ppm. Details of the testing procedure can be found in reference [37]. Catalytic performance was evaluated
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when the NOx storage behavior became reproducible over several cycles. The feed gas, in absence of CO2 and H2O, consisted of 0.14% (v/v) NO, 6% (v/v) O2, 0.9% (v/v) CO, 0.15% (v/v) C2H4 in helium for the fuel lean phase at a space velocity of 42,000 mL/(h/gm catalyst). The fuel rich phase was simulated by replacing the oxygen with an equal volume of helium while holding all other flow rates constant. Similarly, the desired volume of helium was replaced by H2O and/or CO2 (in both the rich and the lean phase) to quantify the effect of their presence on NOx storage capacity of the catalysts. For this study, concentrations of 0.26 and 4.4% (v/v) were employed for H2O and CO2, respectively. The catalysts were cycled multiple times between 15 min in the fuel rich phase and 30 min in the fuel lean phase. For all results reported, 150 mg of catalyst was loaded into each reactor, and all experiments reported in this paper were performed at 648 K. 2.2. Catalyst synthesis Fig. 1 shows the surface response design [35,42,43] used for the catalyst compositions tested in this study. All catalysts were synthesized with Pt, Ba, and Fe supported on g-Al2O3 (Catalox1 Sba-200, 200 m2/g) via incipient wetness. Pt was added to the NSR catalysts for it ability to oxidize and reduce NOx, Ba was added as a NOx storage component, and Fe was added because of previous reports that it improved the resistance of Pt/Ba NSR catalysts to sulfur poisoning
Fig. 1. Statistically designed combinations for catalyst compositions.
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[38]. Chloroplatinic acid hexahydrate, barium nitrate, and iron(III) nitrate nonahydrate precursors (all from Strem Chemicals) were dissolved in distilled water before impregnation. Because of the low solubility of Ba(NO3)2 in water, it was necessary to utilize multiple impregnation steps to achieve the desired weight loadings. Verification of the Pt, Ba, and Fe weight loadings was performed using atomic absorption spectroscopy. After completion of the impregnation, the powders were crushed and calcined in a tube furnace. The calcination procedure consisted of heating to 473 K over 2 h, followed by holding the temperature at 473 K for 1 h, further heating to 823 K over 3 h, holding at 823 K for 2 h, and then cooling to 298 K over 4 h. Before the first run, the catalysts were reduced in situ in the high-throughput reactor for 1 h in 10% (v/v) H2 in He at 773 K.
3. Results Catalysts were tested under four different conditions: in the absence of H2O and CO2, in the presence of only H2O, in the presence of only CO2, and in the presence of both CO2 and H2O. As a representative result, the effluent NOx concentrations as a function of NOx exposure are shown in Fig. 2 for a 0.5 wt% Pt/ 7.5 wt% Ba/2.5 wt% Fe catalyst in all four of these cases. In addition, the average initial NOx storage/ reduction results for these four different feed conditions are graphed in Fig. 3. From these two
Fig. 3. Average influence of CO2 and H2O on initial NOx storage and reduction for a 0.5 wt% Pt/7.5 wt% Ba/2.5 wt% Fe catalysts).
figures, it is clear that both CO2 and H2O significantly decrease the initial NOx storage/reduction of Pt/Ba based NSR catalysts. Breakthrough of NOx occurs much earlier with CO2/H2O in the feed as compared to the case without these gases in the feed. These results are in good agreement with previous work that demonstrated the harmful effect of both CO2 [12,19,20], H2O [21] and the combination CO2 and H2O [8,15] on the performance of NSR catalysts. The effects of CO2 and H2O were quantified based on the change in NOx storage (DNOx Storage) caused by their presence in the feed, i.e., the difference between the NOx storage in the absence of CO2 and H2O and the NOx storage with either one or both of them present. This change in NOx storage was then modeled as a function of metal composition using a surface response methodology [35,42,43]. The model equations are based on the high-throughput data and relate the effect of adding CO2 and H2O on the NOx storage (in micromoles) of the catalyst to the metal composition: DNOx storage ðCO2 presentÞ ¼ 3:688 þ 0:98 Pt þ 4:723 Ba 0:91 Fe 3:654 ðBa2 Þ þ 4:758 Ba Fe DNOx storage ðH2 O presentÞ ¼ 5:6 0:870 Pt 3:580 Ba þ 2:5 Fe 1:55 ðPt2 Þ þ 1:4 Ba2 þ 3:4 Fe2
Fig. 2. Characteristic influence of CO2 and H2O in the feed on initial NOx storage/reduction for a 7.5Ba/0.5Pt catalyst.
þ 3:6 Pt Ba 7:4 Pt Fe 7 Ba Fe
R.J. Hendershot et al. / Applied Surface Science 252 (2006) 2588–2592
Fig. 4. Model predictions compared to experimental observations for the decrease in NOx storage with only water present.
DNOx storage ðH2 O þ CO2 presentÞ ¼ 8:4 þ 1:57 Pt 0:97 Ba þ 2:7 Fe 2:45 ðPt2 Þ þ 2:05 Ba2 þ 2:2 Fe2 þ 3:95 Pt Ba 5:975 Pt Fe 4:875 Ba Fe In order to find the relative importance of different metal loadings in the above models, the compositions of the Pt, Ba, and Fe were normalized with respect to the maximum loading of each. Fig. 4 shows the comparison between the model prediction and experimental observations for the observed decrease in NOx storage in the presence of water. The large error bar for the experimental observation is mainly due to overlap of the spectral absorption bands of NO and water. From the above quantitative models for the decrease in NOx storage in the presence of H2O only, CO2 only, and CO2 and H2O, several conclusions can be drawn. When only CO2 was present, the Ba and Fe content are the primary factors that affect the total NOx storage of the catalyst. It has been previously reported that CO2 increases the rate of NO2 desorption, aiding in catalyst regeneration during the rich phase [15,19]. This regenerative effect of CO2 decreases the need for noble metals for catalytic reduction. This effect can be seen in the model, as the Pt content of the catalyst is of little importance as compared to Ba and Fe, the NOx storage components. However, in the lean phase, CO2 adsorbs both on Ba and Fe NOx storage sites, decreasing the net storage capacity of the catalyst.
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From the H2O inclusive model, it can be seen that the Pt content of the catalyst is of significant importance. Fig. 3 shows that there is a greater decrease in NOx storage in the presence of water alone than CO2 alone. It has been reported that H2O hinders the release of NO2 and thus decreases the regeneration rate, resulting in less NOx storage [21]. Thus, the decrease in the regeneration rate increases the need for a noble metal (in this case Pt) to activate hydrocarbon reducing agents, such as ethylene or propylene, which can remove NO2 during the rich phase [3] and aid in increasing the NOx storage. The interaction between Pt, Ba, and Fe also becomes important as Ba and Fe sites adjacent to Pt are primarily responsible for the NOx storage of the catalyst [3,11,37,39,40]. Under reaction conditions in which both CO2 and H2O are present, it was found that CO2 partially compensates for the reduced catalyst regeneration due to water. However, the total NOx storage is still lower compared to the case than when only CO2 or H2O are present. This can be seen in the response surface model, as the contributions of Pt, Ba, Fe, and the interaction between them decrease relative to the constant term in the model. However, the model equation still resembles that of the H2O inclusive case with considerable significance of the noble metal. This indicates that the storage behavior is for the most part governed by H2O, which is in agreement with previous results stating that Ba(OH)2 are more preferred cites for storage [41].
Acknowledgement The authors acknowledge financial support by the National Science Foundation, Grant 0343758-CTS. References [1] H.S. Gandhi, G.W. Graham, R.W. McCabe, J. Catal. 216 (2003) 433–442. [2] S. Matsumoto, Catal. Today 29 (1996) 43–45. [3] N. Takahashi, et al. Catal. Today 27 (1996) 63–69. [4] L. Olsson, H. Persson, E. Fridell, M. Skoglundh, B. Andersson, J. Phys. Chem. B 105 (2001) 6895–6906. [5] E.F. Bjorn Westerberg, J. Mol. Catal. A Chem. 165 (2001) 249–263. [6] P.-H. Han, Y.-K. Lee, S.-M. Han, H.-K. Rhee, Top. Catal. 16/17 (2001) 165–170.
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[7] F. Prinetto, G. Ghiotti, I. Nova, L. Lietti, E. Tronconi, P. Forzatti, J. Phys. Chem. B 105 (2001) 12732–12745. [8] L. Lietti, P. Forzatti, I. Nova, E. Tronconi, J. Catal. 204 (2001) 175–191. [9] C. Hess, J.H. Lunsford, J. Phys. Chem. B 106 (2002) 6358– 6360. [10] C. Sedlmair, K. Seshan, A. Jentys, J.A. Lercher, J. Catal. 214 (2003) 308–316. [11] D. James, E. Fourre, M. Ishii, M. Bowker, Appl. Catal. B Environ. 45 (2003) 147–159. [12] F. Rodrigues, L. Juste, C. Potvin, J.F. Tempere, G. Blanchard, G. Djega-Mariadassou, Catal. Lett. 72 (2001) 59–64. [13] H. Mahzoul, J.F. Brilhac, P. Gilot, Appl. Catal. B 20 (1999) 47– 55. [14] H. Mahzoul, P. Gilot, J.F. Brilhac, B.R. Stanmore, Top. Catal. 16 (2001) 293–298. [15] A. Amberntsson, H. Persson, P. Engstrom, B. Kasemo, Appl. Catal. B 31 (2001) 27–38. [16] G. Centi, G.E. Arena, S. Perathoner, J. Catal. 216 (2003) 443– 454. [17] S. Hodjati, K. Vaezzadeh, P.C.V. Pitchon, A. Kiennemann, Appl. Catal. B Environ. 26 (2000) 5–16. [18] K. Vaezzadeh, C. Petit, V. Pitchon, A. Kiennemann, Catal. Commun. 3 (2002) 179–183. [19] S. Balcon, C. Potvin, L. Salin, J.F. Tempere, G. Djega-Mariadassou, Catal. Lett. 60 (1999) 39–43. [20] E. Fridell, M. Skoglundh, B. Westerberg, S. Johansson, G. Smedler, J. Catal. 183 (1999) 196–209. [21] N.W. Cant, M.J. Patterson, Catal. Lett. 85 (2003) 153–157. [22] S. Senkan, Angew. Chem. Int. Ed. 40 (2001) 312–329. [23] R.J. Hendershot, C.M. Snively, J. Lauterbach, Chem. Eur. J. 11 (3) (2005) 806–814. [24] K. Krantz, S. Ozturk, S. Senkan, Catal. Today 62 (2000) 281– 289. [25] S. Ozturk, S. Senkan, Appl. Catal. B Environ. 38 (2002) 243– 248. [26] A. Richter, M. Langpape, S. Kolf, G. Grubert, R. Eckelt, J. Radnik, A. Schneider, M.M. Pohl, R. Fricke, Appl. Catal. B Environ. 36 (2002) 261–277.
[27] O.M. Busch, C. Hoffmann, T.R.F. Johann, H.W. Schmidt, W. Strehlau, F. Schuth, J. Am. Chem. Soc. 124 (2002) 13527– 13532. [28] R.J. Hendershot, S.S. Lasko, M.-F. Fellmann, G. Oskarsdottir, W.N. Delgass, C.M. Snively, J. Lauterbach, Appl. Catal. A Gen. 254 (2003) 107–120. [29] C.M. Snively, S. Katzenberger, G. Oskarsdottir, J. Lauterbach, Opt. Lett. 24 (1999) 1841–1843. [30] C.M. Snively, G. Oskarsdottir, J. Lauterbach, J. Combi. Chem. 2 (2000) 243–245. [31] C.M. Snively, G. Oskarsdottir, J. Lauterbach, Angew. Chem. Int. Ed. 40 (2001) 3028–3030. [32] C.M. Snively, G. Oskarsdottir, J. Lauterbach, Catal. Today 67 (2001) 357–368. [33] C.M. Snively, J. Lauterbach, Spectroscopy 17 (2002) 26– 33. [34] R.J. Hendershot, P.T. Fanson, C.M. Snively, J. Lauterbach, Angew. Chem. Int. Ed. 42 (2003) 1152–1155. [35] R.J. Hendershot, W.B. Rogers, C.M. Snively, B.A. Ogunnaike, J. Lauterbach, Catal. Today 98 (2004) 375–385. [36] R.J. Hendershot, R. Vijay, B.J. Feist, C.M. Snively, J. Lauterbach, Meas. Sci. Technol. 16 (2004) 302–308. [37] R. Vijay, R.J. Hendershot, S.M. Rivera-Jimenez, W.B. Rogers, B.J. Feist, C.M. Snively, J. Lauterbach, Catal. Commun. 6 (2004) 167–171. [38] K. Yamazaki, T. Suzuki, N. Takahashi, K. Yokota, M. Suguira, Appl. Catal. B Environ. 30 (2001) 459–468. [39] E. Fridell, H. Persson, B. Westerberg, L. Olsson, M. Skoglundh, Catal. Lett. 66 (2000) 71–74. [40] L.J. Gill, P.G. Blakeman, M.V. Twigg, A.P. Walker, Top. Catal. 28 (2004) 157–164. [41] I. Nova, L. Castoldi, L. Lietti, E. Tronconi, P. Forzatti, Catal. Today 75 (2002) 431–437. [42] J. Lawson, J. Erjavec, Modern Statistics for Engineering and Quality Improvement, Brooks/Cole-Thomson Learning, Pacific Grove, CA, 2000. [43] J.N. Cawse, Experimental Design for Combinatorial and High Throughput Materials Development, John Wiley and Sons, Inc., Hoboken, NJ, 2002.
High-throughput study of the influence of H2O and CO2 on the performance of nitrogen storage and reduction (NSR) catalysts R.J. Hendershot a, R. Vijay a, C.M. Snively a,b, J. Lauterbach a,* a
b
Department of Chemical Engineering, University of Delaware, Newark, DE 19716, USA Department of Materials Science and Engineering, University of Delaware, Newark, DE 19716, USA Received 8 December 2004; accepted 22 June 2005 Available online 3 October 2005
Abstract This paper describes the application of parallel high-throughput experimentation based on FTIR spectral imaging to a tolerance study for NOx storage and reduction (NSR) catalysts with respect to CO2 and H2O in the feed. It was found that both gases decrease the storage capacity of platinum/barium based NSR catalysts, with H2O having a stronger effect than CO2. # 2005 Elsevier B.V. All rights reserved. PACS: 82.65.J; 02.10.E; 82.80.C Keywords: High-throughput screening; Nitrogen storage and reduction (NSR) catalysts; FTIR imaging
1. Introduction Lean burn engines have been promoted as a method to improve the fuel efficiency of automobile engines [1]. Impeding the widespread implementation of lean burn engines is the inability of current three-way catalytic converters to reduce nitrogen oxides (NOx) under net-oxidizing conditions. NOx storage and reduction (NSR) catalysts were designed to store * Corresponding author. Tel.: +1 302 831 6327; fax: +1 302 831 1048. E-mail address: [email protected] (J. Lauterbach).
NOx during a fuel lean cycle and reduce the stored NOx during a subsequent fuel rich cycle [2,3]. Extensive research has been performed on NSR catalysts in the past decade to understand the storage and reduction mechanisms and improve overall NOx conversion [4–18]. Reaction conditions that were found to affect NSR catalysts include temperature, NOx concentration, O2 concentration, CO2 concentration, H2O concentration, reductant concentration, reductant type, space velocity, total lean/rich cycle time, lean/rich duty cycle, and the presence of sulfur. Obviously, the performance of NSR catalysts is also strongly influenced by the catalyst composition.
0169-4332/$ – see front matter # 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.apsusc.2005.06.041
R.J. Hendershot et al. / Applied Surface Science 252 (2006) 2588–2592
However, few studies were conducted under more realistic simulated exhaust gas with CO2 and/or H2O in the feed [8,12,15,19–21]. High-throughput experimentation (HTE) is increasingly being used for catalyst development [22,23] and is becoming a widely accepted tool, mainly among industrial researchers. In the research field of de-NOx catalysis, high-throughput techniques have been used to study selective catalytic reduction of nitric oxide using hydrocarbons [24–27]. One particular study looked at seven catalysts for NOx storage activity under a single reaction condition [27]. In this paper, we report the application of HTE to the study of the stability of NSR catalysts with respect to CO2 and H2O in the feed.
2. Experimental 2.1. High-throughput experimental setup and testing procedure All catalytic tests were performed using a 16 channel parallel reactor that is capable of acquiring data of comparable quality to that obtained from single reactor studies. Details concerning the reactor have been described previously [28]. Briefly, the flows across all the reactors are balanced using capillaries and the catalyst bed temperature is continuously measured for each sample. The reaction products from all 16 reactors were analyzed simultaneously using Fourier transform infrared (FTIR) imaging [29–33]. The optical setup consists of a Bruker Equinox 55 FTIR spectrometer interfaced with a 64 64 pixel mercury cadmium telluride FPA detector (Santa Barbara Focalplane, Goleta, CA, USA), and is capable of collecting IR spectra of the effluents from all 16 reactors in less than 2 s [34]. Details of the optical setup and analytical methods can be found in [23,29,33,35]. For quantification of the effluent gases in complex mixtures, standard chemometric techniques were adapted for spectral imaging data [36]. The performance of each catalyst was based on the NOx storage, defined as the integrated area between the inlet NOx concentration and outlet NOx concentration, in the fuel lean state, from time zero to the time when the outlet NOx concentration reached 300 ppm. Details of the testing procedure can be found in reference [37]. Catalytic performance was evaluated
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when the NOx storage behavior became reproducible over several cycles. The feed gas, in absence of CO2 and H2O, consisted of 0.14% (v/v) NO, 6% (v/v) O2, 0.9% (v/v) CO, 0.15% (v/v) C2H4 in helium for the fuel lean phase at a space velocity of 42,000 mL/(h/gm catalyst). The fuel rich phase was simulated by replacing the oxygen with an equal volume of helium while holding all other flow rates constant. Similarly, the desired volume of helium was replaced by H2O and/or CO2 (in both the rich and the lean phase) to quantify the effect of their presence on NOx storage capacity of the catalysts. For this study, concentrations of 0.26 and 4.4% (v/v) were employed for H2O and CO2, respectively. The catalysts were cycled multiple times between 15 min in the fuel rich phase and 30 min in the fuel lean phase. For all results reported, 150 mg of catalyst was loaded into each reactor, and all experiments reported in this paper were performed at 648 K. 2.2. Catalyst synthesis Fig. 1 shows the surface response design [35,42,43] used for the catalyst compositions tested in this study. All catalysts were synthesized with Pt, Ba, and Fe supported on g-Al2O3 (Catalox1 Sba-200, 200 m2/g) via incipient wetness. Pt was added to the NSR catalysts for it ability to oxidize and reduce NOx, Ba was added as a NOx storage component, and Fe was added because of previous reports that it improved the resistance of Pt/Ba NSR catalysts to sulfur poisoning
Fig. 1. Statistically designed combinations for catalyst compositions.
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[38]. Chloroplatinic acid hexahydrate, barium nitrate, and iron(III) nitrate nonahydrate precursors (all from Strem Chemicals) were dissolved in distilled water before impregnation. Because of the low solubility of Ba(NO3)2 in water, it was necessary to utilize multiple impregnation steps to achieve the desired weight loadings. Verification of the Pt, Ba, and Fe weight loadings was performed using atomic absorption spectroscopy. After completion of the impregnation, the powders were crushed and calcined in a tube furnace. The calcination procedure consisted of heating to 473 K over 2 h, followed by holding the temperature at 473 K for 1 h, further heating to 823 K over 3 h, holding at 823 K for 2 h, and then cooling to 298 K over 4 h. Before the first run, the catalysts were reduced in situ in the high-throughput reactor for 1 h in 10% (v/v) H2 in He at 773 K.
3. Results Catalysts were tested under four different conditions: in the absence of H2O and CO2, in the presence of only H2O, in the presence of only CO2, and in the presence of both CO2 and H2O. As a representative result, the effluent NOx concentrations as a function of NOx exposure are shown in Fig. 2 for a 0.5 wt% Pt/ 7.5 wt% Ba/2.5 wt% Fe catalyst in all four of these cases. In addition, the average initial NOx storage/ reduction results for these four different feed conditions are graphed in Fig. 3. From these two
Fig. 3. Average influence of CO2 and H2O on initial NOx storage and reduction for a 0.5 wt% Pt/7.5 wt% Ba/2.5 wt% Fe catalysts).
figures, it is clear that both CO2 and H2O significantly decrease the initial NOx storage/reduction of Pt/Ba based NSR catalysts. Breakthrough of NOx occurs much earlier with CO2/H2O in the feed as compared to the case without these gases in the feed. These results are in good agreement with previous work that demonstrated the harmful effect of both CO2 [12,19,20], H2O [21] and the combination CO2 and H2O [8,15] on the performance of NSR catalysts. The effects of CO2 and H2O were quantified based on the change in NOx storage (DNOx Storage) caused by their presence in the feed, i.e., the difference between the NOx storage in the absence of CO2 and H2O and the NOx storage with either one or both of them present. This change in NOx storage was then modeled as a function of metal composition using a surface response methodology [35,42,43]. The model equations are based on the high-throughput data and relate the effect of adding CO2 and H2O on the NOx storage (in micromoles) of the catalyst to the metal composition: DNOx storage ðCO2 presentÞ ¼ 3:688 þ 0:98 Pt þ 4:723 Ba 0:91 Fe 3:654 ðBa2 Þ þ 4:758 Ba Fe DNOx storage ðH2 O presentÞ ¼ 5:6 0:870 Pt 3:580 Ba þ 2:5 Fe 1:55 ðPt2 Þ þ 1:4 Ba2 þ 3:4 Fe2
Fig. 2. Characteristic influence of CO2 and H2O in the feed on initial NOx storage/reduction for a 7.5Ba/0.5Pt catalyst.
þ 3:6 Pt Ba 7:4 Pt Fe 7 Ba Fe
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Fig. 4. Model predictions compared to experimental observations for the decrease in NOx storage with only water present.
DNOx storage ðH2 O þ CO2 presentÞ ¼ 8:4 þ 1:57 Pt 0:97 Ba þ 2:7 Fe 2:45 ðPt2 Þ þ 2:05 Ba2 þ 2:2 Fe2 þ 3:95 Pt Ba 5:975 Pt Fe 4:875 Ba Fe In order to find the relative importance of different metal loadings in the above models, the compositions of the Pt, Ba, and Fe were normalized with respect to the maximum loading of each. Fig. 4 shows the comparison between the model prediction and experimental observations for the observed decrease in NOx storage in the presence of water. The large error bar for the experimental observation is mainly due to overlap of the spectral absorption bands of NO and water. From the above quantitative models for the decrease in NOx storage in the presence of H2O only, CO2 only, and CO2 and H2O, several conclusions can be drawn. When only CO2 was present, the Ba and Fe content are the primary factors that affect the total NOx storage of the catalyst. It has been previously reported that CO2 increases the rate of NO2 desorption, aiding in catalyst regeneration during the rich phase [15,19]. This regenerative effect of CO2 decreases the need for noble metals for catalytic reduction. This effect can be seen in the model, as the Pt content of the catalyst is of little importance as compared to Ba and Fe, the NOx storage components. However, in the lean phase, CO2 adsorbs both on Ba and Fe NOx storage sites, decreasing the net storage capacity of the catalyst.
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From the H2O inclusive model, it can be seen that the Pt content of the catalyst is of significant importance. Fig. 3 shows that there is a greater decrease in NOx storage in the presence of water alone than CO2 alone. It has been reported that H2O hinders the release of NO2 and thus decreases the regeneration rate, resulting in less NOx storage [21]. Thus, the decrease in the regeneration rate increases the need for a noble metal (in this case Pt) to activate hydrocarbon reducing agents, such as ethylene or propylene, which can remove NO2 during the rich phase [3] and aid in increasing the NOx storage. The interaction between Pt, Ba, and Fe also becomes important as Ba and Fe sites adjacent to Pt are primarily responsible for the NOx storage of the catalyst [3,11,37,39,40]. Under reaction conditions in which both CO2 and H2O are present, it was found that CO2 partially compensates for the reduced catalyst regeneration due to water. However, the total NOx storage is still lower compared to the case than when only CO2 or H2O are present. This can be seen in the response surface model, as the contributions of Pt, Ba, Fe, and the interaction between them decrease relative to the constant term in the model. However, the model equation still resembles that of the H2O inclusive case with considerable significance of the noble metal. This indicates that the storage behavior is for the most part governed by H2O, which is in agreement with previous results stating that Ba(OH)2 are more preferred cites for storage [41].
Acknowledgement The authors acknowledge financial support by the National Science Foundation, Grant 0343758-CTS. References [1] H.S. Gandhi, G.W. Graham, R.W. McCabe, J. Catal. 216 (2003) 433–442. [2] S. Matsumoto, Catal. Today 29 (1996) 43–45. [3] N. Takahashi, et al. Catal. Today 27 (1996) 63–69. [4] L. Olsson, H. Persson, E. Fridell, M. Skoglundh, B. Andersson, J. Phys. Chem. B 105 (2001) 6895–6906. [5] E.F. Bjorn Westerberg, J. Mol. Catal. A Chem. 165 (2001) 249–263. [6] P.-H. Han, Y.-K. Lee, S.-M. Han, H.-K. Rhee, Top. Catal. 16/17 (2001) 165–170.
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