- Email: [email protected]
PEMFC contaminant tolerance limit—CO in H2
Electrochimica Acta 55 (2010) 4208–4211
Contents lists available at ScienceDirect
Electrochimica Acta journal homepage: www.elsevier.com/locate/electacta
PEMFC contaminant tolerance limit—CO in H2 Jean St-Pierre ∗,1 University of South Carolina, Department of Chemical Engineering, 301 Main Street, Columbia, SC 29208, USA
a r t i c l e
i n f o
Article history: Received 16 February 2010 Received in revised form 19 February 2010 Accepted 19 February 2010 Available online 4 March 2010 Keywords: Proton exchange membrane fuel cell Catalyst poison Mathematical model Hydrogen quality Standard
a b s t r a c t Equations are derived from a generic, transient PEMFC contamination model to predict the effect of CO contaminant concentration in H2 on both steady state performance losses and time constants. The resulting predictions allowed determination of the CO tolerance limit for the cases of a Pt and WC catalyst under specific operating conditions. An increase of the International Organization for Standardization CO tolerance limit of 0.2 ppm is possible because the CO concentration leading to a steady state performance loss of less than 1% is estimated at 0.2–0.9 ppm. An increase in CO tolerance limit is expected to reduce the analytical verification cost (quality control). The steady state performance loss is independent of catalyst loading thus avoiding a future standard change resulting from PEMFC cost reduction activities. © 2010 Elsevier Ltd. All rights reserved.
1. Introduction Proton exchange membrane fuel cell (PEMFC) contaminants have recently attracted significant attention [1,2] partly because standards are being developed for hydrogen [3]. However, the information available to define the standard is currently limited because experimental data are incomplete. The limited amount of time left to complete required tests before the draft standard target publication date (October 2010) represents a significant concern. For instance, the low concentration range is seldom if at all investigated because degradation is slow and the performance loss is small. Thus it becomes a challenge to separate the loss associated with contamination from other degradation mechanisms. The use of mathematical models in conjunction with tests performed with more highly concentrated contaminants represents a solution. Many contamination models were developed (for example, [4–6]) but they are generally poorly validated and are characterized by numerical solutions complicating rate constants evaluation needed for predictions of low contaminant concentrations performance losses. Furthermore, these models are generally developed for specific contaminants and thus are not necessarily relevant for other contaminants. These difficulties led to the development of generic models that facilitate rate constants evaluation and that are applicable to both fuel cell compartments and many contaminants [7,8].
∗ Tel.: +1 803 777 2581; fax: +1 803 777 8142. E-mail address: [email protected]. 1 ISE member. 0013-4686/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.electacta.2010.02.061
The model developed for the case of an electroactive contaminant leading to a product that subsequently desorbs from the catalyst is used to illustrate the proposed approach to derive CO tolerance limits [7]. CO is used to perform the analysis because suitable data are available and this contaminant was suggested as a potential canary to estimate the overall hydrogen fuel quality [3]. 2. Model equations The fixed electrode potential model [7] was derived from catalyst surface mass balances (Fig. 1) because the relatively fast contaminant X transport in the gas and ionomer phases is not rate determining leading to a spatially uniform distribution (zero dimensional model). Subsequently, species coverages are related to the main reaction rate expression. More specifically, the contaminant coverage decreases the active catalyst surface available to the reactant adsorbate and consequently the current density (Eqs. 3, 11, 12, 17, 22 and 26 of Ref. [7]). Both hydrogen oxidation and oxygen reduction reactions are kinetically controlled (mass transport regime is avoided in automotive applications) and involve a catalyst surface adsorbate R that produces a rapidly desorbing product P1 . The overall reaction rate for the main reaction is larger than for the contaminant reaction (pseudo-steady state). The model was derived for two rate determining step (rds) cases: contaminant X reaction leading to a product P2 , contaminant product P2 desorption. Other model derivation assumptions and model validation are discussed in the original publication [7]. For the contaminant reaction rds, the following expressions were obtained for a step change in contaminant concentration from
J. St-Pierre / Electrochimica Acta 55 (2010) 4208–4211
4209
Fig. 1. Modeled catalyst surface reactions. X, R and P respectively represent the contaminant, the reactant and the product of an electrochemical reaction.
an initially reactant stream free of contaminant:
i k = 1 − ek t/ − 1 icX =0 k k =
(1)
kR,ads kX,ads cR cX (p − ps )2 − kX,ads cX (p − ps ) − kX,des − kX kR,ads cR (p − ps ) + kR,des + kR (2)
k = kX,ads cX (p − ps ) −
kR,ads kX,ads cR cX (p − ps )2 kR,ads cR (p − ps ) + kR,des + kR
= − k − kX,des − kX ∝ cX
(3)
The steady state solution is (k < 0): i k =1+ icX =0 k
(4)
For the negative step change in concentration to a reactant stream free of contaminant, the expression is: i k −(kX,des +kX )t =1+ e icX =0 k
(5)
For the contaminant product desorption rds, expressions are identical with the exception that the kX,des + kX term is replaced by kP2 ,des leading to modified Eqs. (2) and (5): k =
kR,ads kX,ads cR cX (p − ps )2 − kX,ads cX (p − ps ) − kP2 ,des kR,ads cR (p − ps ) + kR,des + kR
i icX =0
=1+
k −kP2 ,des t e k
(6)
Fig. 2. Contamination processes steady state dimensionless current density and time constants as a function of contaminant concentration for a Pt based PEMFC. Eqs. (8) and (9) plots are based on k /k = −0.4358, k / = −0.008687 min−1 , (kX,des + kX )/ −1 obtained from 10 ppm CO data [9]. Curve fitting of or kP2 ,des / = 0.0356min steady state current density (k /k values from Eq. (1) fit) to Eq. (10) led to a = 18.55 and r2 = 0.15. Air/H2 + CO, 2.5/1.5 stoichiometry, 300/300 kPa, 80 ◦ C, 100% relative humidity, 0.5/0.5 mg Pt cm−2 , 0.6 V cell voltage.
Eq. (9) contains the same parameters as Eq. (8) and thus is also scalable to other contaminant concentrations. The /(kX,des + kX ) time constant (Eq. (5)) is independent of contaminant concentration. It is emphasized that the k /k parameter is not only obtained by direct experimental data fitting but is also derived from the combination of all similarly determined parameters (combination of k /k , /k and (kX,des + kX )/ as shown in Eq. (8)) thus providing a model self-consistency test. The steady state dimensionless current (Eq. (8)) and both time constants (Eq. (9)) are plotted as a function of contaminant concentration for the cases of a Pt (Fig. 2, [9]) and WC (Fig. 3, [10]) catalyst. Recent high temperature PEMFC data were also analyzed (Fig. 4, [11]) and resulting parameters were used to create similar plots (Fig. 5). The k /k parameters determined from curve fitting are also added to Figs. 2, 3 and 5 for comparison with Eq. (8) curves. The contaminant concentration is limited to 10% thus avoiding thermodynamic and mass transport model corrections which were not taken into account in the model derivation. Experimental data from [9,11] were obtained under constant cell
(7)
Because the different rds cases lead to the same solutions and only their interpretation is different, the discussion is focused on the contaminant reaction rds. Experimental data fitting to Eq. (1) leads to k /k and /k parameters whereas fitting to Eq. (5) leads to the /(kX,des + kX ) parameter. The steady state dimensionless current Eq. (4) is rewritten in terms of fitted parameters: i 1 = 1+ =1+ k icX =0 k
= 1−
1 −k −kX,des −kX k
=1−
1 1+
1 1+
kX,des +kX k k k
(8)
kX,des +kX k
In Eq. (8), only /k , obtained from the product of experimentally determined k /k and /k parameters, is proportional to the contaminant concentration (Eq. (3)) and thus is directly scalable to other contaminant concentrations. Similarly, the time constant −/k (Eq. (1)) is rewritten as: −
1 = − = −k −kX,des −kX k
1 k
+
kX,des +kX
(9)
Fig. 3. Contamination processes steady state dimensionless current density and time constants as a function of contaminant concentration for a WC based PEMFC electrode. Eqs. (8) and (9) plots are based on k /k = −0.03013, −1 k / = −3.078 min−1 , (kX,des + kX )/ or kP2 ,des / = 1.648min obtained from 1% CO data [10]. H2 + CO, 20 cm3 min−1 , 122 kPa, 70 ◦ C, 58 mg WC cm−2 , −0.35 V versus the mercury/mercurous sulfate reference electrode (equivalent to +0.299 V versus the SHE).
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J. St-Pierre / Electrochimica Acta 55 (2010) 4208–4211
cX < 0.9 ppm). The suggested value of 0.9 ppm is larger than the recommended value of 0.2 ppm [3] suggesting a tolerance limit increase is possible to reduce the analytical verification cost (quality control). An increase in CO tolerance limit from 0.2 to 2 ppm is projected to have a negligible effect on the hydrogen production cost. The suggested specification relaxation does not extend to the CO tolerance limit derived from the fitted k /k values which were correlated based on Eqs. (3) and (8): 1 i =1− icX =0 1 + ca
(10)
X
Fig. 4. Comparison between contamination and recovery transients [11], and model equations. Contamination data curve fitting led to k /k = −0.2343, k / = −0.04179 s−1 and r2 = 0.86. Recovery data curve fitting using k /k = −0.2343 led to (kX,des + kX )/ or kP2 ,des / = 0.05009 s−1 and r2 = 0.33. Air/H2 + 1.31% CO, 2 stoichiometry/400 cm3 min−1 , atmospheric pressure, 150 ◦ C, 0% relative humidity, 0.75/1 mg Pt cm−2 , 0.6 V cell voltage.
voltage rather than constant working electrode potential. Although not ideal, this option leads to a lower electrode potential variation (40–50 mV) than constant current operation (300–500 mV) and a good agreement with the model [8]. Reference electrodes are susceptible to contamination because the ionomer is permeable [8]. The use of a H2 counter-electrode or an ohmic loss compensated cell voltage control need to be explored [8]. 3. CO tolerance limit For Fig. 2, the steady state dimensionless cell current (Eq. (8)) starts to decrease after the CO concentration reaches a 5 ppm level (i/icX =0 = 0.95). Beyond a ∼2000 ppm level, the cell hardly produces any power (i/icX =0 = 0.05). The time constant associated with the recovery process (Eq. (5)) is ∼30 min and of the same order as the duration of a car excursion and thus the deleterious CO effect is not avoidable. The contamination time constant is equal to the recovery process time constant for low CO concentrations as is deduced from Eqs. (3) and (9). For larger CO concentrations, the contribution of the k / term in Eq. (9) increases leading to a time constant decrease. Because, the time constants are of the same order as the duration of a car excursion, the CO concentration specification needs to be set at a level that will hardly affect the cell performance under steady state conditions (i/icX =0 > 0.99,
Fig. 5. Contamination processes steady state dimensionless current density and time constants as a function of contaminant concentration for a Pt based PEMFC. Eqs. (8) and (9) plots are based on k /k = −0.2343, k / = −0.04179 s−1 , (kX,des + kX )/ or kP2 ,des / = 0.05009 s−1 obtained from 1.31% CO data [11]. Air/H2 + CO, 2 stoichiometry/400 cm3 min−1 , atmospheric pressure, 150 ◦ C, 0% relative humidity, 0.75/1 mg Pt cm−2 , 0.6 V cell voltage.
The fitted Eq. (10) (Fig. 2) indicates a lower tolerance limit of 0.2 ppm (i/icX =0 > 0.99) in comparison to Eq. (8) and is consistent with the specification [3]. The discrepancy between both steady state current density curves is ascribed to a low experimental data recording rate (for instance, 9 data points during the recovery period [9]) and relatively high experimental variability. As already mentioned for low contaminant concentrations, the time constants associated with the contamination and recovery processes are of equal duration (∼30 min). Therefore, the assumption that mass transfer (contaminant supply) rather than catalyst surface adsorption and reaction processes are controlling appear questionable [12]. The contamination recovery process is not mass transfer controlled because the contaminant is already on the catalyst surface and, ionomer and gas phase transport processes are rapid ranging from the millisecond to the second [8]. If mass transfer is controlling during the contamination process (supply rate), the contaminant distribution is expected to be non-uniform, a front moving across the cell separating catalyst regions either covered or free from contaminant. However, data obtained with an application size cell (∼300 cm2 active area) characterized by a significant pressure drop and coolant temperature rise along the flow field length, show that the current distribution is unaffected by contamination [13]. Other data obtained with a 5 cm2 active area cell appear to contradict this observation because the contaminant is detected at the cell outlet after a significantly long breakthrough time consistent with a non-uniform distribution [14]. However, the smaller cell contains more liquid water which scavenges the contaminant by dissolution because a significant pressure drop and temperature rise along the flow field length cannot be established to mitigate water accumulation by evaporation [15]. This hypothesis is confirmed by the effect of reactant stream flow rate which leads to an increase in pressure drop, a more effective liquid water removal, a less severe contaminant scavenging effect by liquid water and thus a worse contamination effect due to a larger effective contaminant concentration [14]. Fig. 3 data were obtained with a precious metal free WC catalyst, a result of fuel cell cost reducing activities [16]. For Fig. 3, plotted curves show the same behavior as in Fig. 2 with the exception that the time constants are significantly reduced (<0.6 min) and the CO tolerance limit is significantly increased (i/icX =0 > 0.99, cX < 0.1%). The improved CO tolerance is ascribed to a lower CO desorption temperature on WC than on Pt [17,18]. Fig. 3 results are achieved with a very high catalyst loading of 58 mg WC cm−2 , favoring the appearance of mass transport losses at high current densities owing to a much thicker catalyst layer and indicating the continuing need for alternate catalysts development activities. A good agreement is also found between both sets of steady state i/icX =0 values confirming the model consistency. It is also emphasized that few alternate catalysts are tested for contamination tolerance [1] and that such characterization is necessary for catalyst selection. Transients resulting from CO contamination of a Pt catalyst at high temperature, an approach considered to mitigate the system related heat rejection issue [19,20], are illustrated in Fig. 4. The model is in good agreement with contamination data but a
J. St-Pierre / Electrochimica Acta 55 (2010) 4208–4211
discrepancy is noted at the end of the recovery period. Model parameters illustrated in Fig. 5 again show a similar behavior as in Figs. 2 and 3. Time constants are shorter than 20 s and the CO tolerance limit is significantly increased (i/icX =0 > 0.99, cX < 0.07%) in comparison to a cell operated at a lower temperature (Fig. 2). This observation is ascribed to the significant lowering effect of temperature on CO surface coverage [21]. The good agreement found between both sets of steady state i/icX =0 values, thus confirming the model consistency, likely indicates that the discrepancy noted in Fig. 4 is due to another process. By comparison, Bergmann et al. found better agreement between their model and experimental data [11]. Although, significant differences exist between both models, including dimensionality (2 versus 0 dimension), adsorption kinetics (non-linear versus linear) and CO oxidation kinetics (water involvement is either taken or not into account), it is not possible to isolate a likely cause. Thus, additional data and analysis are required to reach a conclusion as already stated [11]. Eqs. (1), (5) and (7) indicate that the cell performance loss is independent of catalyst loading. Thus, a catalyst loading decrease to 0.1 mg Pt cm−2 necessary to successfully commercialize fuel cells [16] will not affect the cell performance loss and CO tolerance limit. 4. Conclusions A mathematical contamination model was used to derive CO tolerance limits for hydrogen used in PEMFCs. The proposed approach is advantageous because experiments performed with a single contaminant concentration value are sufficient to predict fuel cell behavior at other concentration values. A similar approach was developed for a contaminant that leads to an irreversibly adsorbed product such as SO2 or H2 S [8]. Implementation of these approaches requires experimental data obtained at a fixed electrode potential (use of a H2 counter-electrode or an ohmic loss compensated cell voltage control) and with step changes in contaminant concentration, still an uncommon practice. The determination of tolerance limits for other contaminants that do not lead to irreversibly adsorbed products under normal fuel cell operating conditions such as NO2 in air [13] and CO2 in H2 is not presently possible because experimental data obtained under these specific conditions are not available. Experimental data obtained under other expected operating conditions are also desirable (wider electrode potential, temperature and water balance ranges, both fuel cell compartments) and are under investigation within this funded program. Acknowledgements The author is indebted to the United States Department of Energy, Energy Efficiency and Renewable Energy for funding (National Renewable Energy Laboratory sub-contract ZGB-099180-01).
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Appendix A. Nomenclature
a cR cX i icX =0 k k kP2 ,des kR kR,ads kR,des kX kX,ads kX,des p ps t
curve fitting parameter defined by Eq. (10) reactant volume fraction in the dry stream contaminant volume fraction in the dry reactant stream current density (A m−2 ) steady state current density in absence of a contaminant (A m−2 ) lumped parameter defined by Eqs. (2) and (6) lumped parameter defined by Eq. (3) reacted contaminant desorption rate constant (mol m−2 s−1 ) reaction rate constant associated with a reactant (mol m−2 s−1 ) reactant adsorption rate constant (mol s−1 N−1 ) reactant desorption rate constant (mol m−2 s−1 ) forward reaction rate constant associated with a contaminant (mol m−2 s−1 ) contaminant adsorption rate constant (mol s−1 N−1 ) contaminant desorption rate constant (mol m−2 s−1 ) reactant stream pressure (N m−2 ) water vapor saturation pressure (N m−2 ) time (s) Pt site molar density (mol m−2 )
References [1] J. St-Pierre, in: F.N. Büchi, M. Inaba, T.J. Schmidt (Eds.), Polymer Electrolyte Fuel Cell Durability, Springer, New York, 2009, p. 289. [2] X. Cheng, Z. Shi, N. Glass, L. Zhang, J. Zhang, D. Song, Z.-S. Liu, H. Wang, J. Shen, J. Power Sources 165 (2007) 739. [3] ISO/CD 14687-2:2009. [4] T.E. Springer, T. Rockward, T.A. Zawodzinski, S. Gottesfeld, J. Electrochem. Soc. 148 (2001) A11. [5] T. Zhou, H. Liu, J. Power Sources 138 (2004) 101. [6] S. Enbäck, G. Lindbergh, J. Electrochem. Soc. 152 (2005) A23. [7] J. St-Pierre, J. Electrochem. Soc. 156 (2009) B291. [8] J. St-Pierre, J. Power Sources submitted for publication. [9] K.K. Bhatia, C.-Y. Wang, Electrochim. Acta 49 (2004) 2333. [10] D.R. McIntyre, G.T. Burstein, A. Vossen, J. Power Sources 107 (2002) 67. [11] A. Bergmann, D. Gerteisen, T. Kurz, Fuel Cells, in press. [12] J. Zhang, T. Thampan, R. Datta, J. Electrochem. Soc. 149 (2002) A765. [13] J. St-Pierre, N. Jia, R. Rahmani, J. Electrochem. Soc. 155 (2008) B315. [14] J. Zhang, R. Datta, Electrochem. Solid-State Lett. 6 (2003) A5. [15] D.P. Wilkinson, J. St-Pierre, J. Power Sources 113 (2003) 101. [16] H.A. Gasteiger, S.S. Kocha, B. Sompalli, F.T. Wagner, Appl. Catal. B 56 (2005) 9. [17] M.B. Zellner, J.G. Chen, J. Electrochem. Soc. 152 (2005) A1483. [18] M. Rosenbaum, F. Zhao, M. Quaas, H. Wulff, U. Schröder, F. Scholz, Appl. Catal. B 74 (2007) 261. [19] N.L. Garland, J.P. Kopasz, J. Power Sources 172 (2007) 94. [20] J. Mader, L. Xiao, T.J. Schmidt, B.C. Benicewicz, in: G.G. Scherer (Ed.), Advances in Polymer Science, vol.216, Springer, Berlin, 2008, p. 63. [21] A. Pitois, J.C. Davies, A. Pilenga, A. Pfrang, G. Tsotridis, J. Catal. 265 (2009) 199.
Contents lists available at ScienceDirect
Electrochimica Acta journal homepage: www.elsevier.com/locate/electacta
PEMFC contaminant tolerance limit—CO in H2 Jean St-Pierre ∗,1 University of South Carolina, Department of Chemical Engineering, 301 Main Street, Columbia, SC 29208, USA
a r t i c l e
i n f o
Article history: Received 16 February 2010 Received in revised form 19 February 2010 Accepted 19 February 2010 Available online 4 March 2010 Keywords: Proton exchange membrane fuel cell Catalyst poison Mathematical model Hydrogen quality Standard
a b s t r a c t Equations are derived from a generic, transient PEMFC contamination model to predict the effect of CO contaminant concentration in H2 on both steady state performance losses and time constants. The resulting predictions allowed determination of the CO tolerance limit for the cases of a Pt and WC catalyst under specific operating conditions. An increase of the International Organization for Standardization CO tolerance limit of 0.2 ppm is possible because the CO concentration leading to a steady state performance loss of less than 1% is estimated at 0.2–0.9 ppm. An increase in CO tolerance limit is expected to reduce the analytical verification cost (quality control). The steady state performance loss is independent of catalyst loading thus avoiding a future standard change resulting from PEMFC cost reduction activities. © 2010 Elsevier Ltd. All rights reserved.
1. Introduction Proton exchange membrane fuel cell (PEMFC) contaminants have recently attracted significant attention [1,2] partly because standards are being developed for hydrogen [3]. However, the information available to define the standard is currently limited because experimental data are incomplete. The limited amount of time left to complete required tests before the draft standard target publication date (October 2010) represents a significant concern. For instance, the low concentration range is seldom if at all investigated because degradation is slow and the performance loss is small. Thus it becomes a challenge to separate the loss associated with contamination from other degradation mechanisms. The use of mathematical models in conjunction with tests performed with more highly concentrated contaminants represents a solution. Many contamination models were developed (for example, [4–6]) but they are generally poorly validated and are characterized by numerical solutions complicating rate constants evaluation needed for predictions of low contaminant concentrations performance losses. Furthermore, these models are generally developed for specific contaminants and thus are not necessarily relevant for other contaminants. These difficulties led to the development of generic models that facilitate rate constants evaluation and that are applicable to both fuel cell compartments and many contaminants [7,8].
∗ Tel.: +1 803 777 2581; fax: +1 803 777 8142. E-mail address: [email protected]. 1 ISE member. 0013-4686/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.electacta.2010.02.061
The model developed for the case of an electroactive contaminant leading to a product that subsequently desorbs from the catalyst is used to illustrate the proposed approach to derive CO tolerance limits [7]. CO is used to perform the analysis because suitable data are available and this contaminant was suggested as a potential canary to estimate the overall hydrogen fuel quality [3]. 2. Model equations The fixed electrode potential model [7] was derived from catalyst surface mass balances (Fig. 1) because the relatively fast contaminant X transport in the gas and ionomer phases is not rate determining leading to a spatially uniform distribution (zero dimensional model). Subsequently, species coverages are related to the main reaction rate expression. More specifically, the contaminant coverage decreases the active catalyst surface available to the reactant adsorbate and consequently the current density (Eqs. 3, 11, 12, 17, 22 and 26 of Ref. [7]). Both hydrogen oxidation and oxygen reduction reactions are kinetically controlled (mass transport regime is avoided in automotive applications) and involve a catalyst surface adsorbate R that produces a rapidly desorbing product P1 . The overall reaction rate for the main reaction is larger than for the contaminant reaction (pseudo-steady state). The model was derived for two rate determining step (rds) cases: contaminant X reaction leading to a product P2 , contaminant product P2 desorption. Other model derivation assumptions and model validation are discussed in the original publication [7]. For the contaminant reaction rds, the following expressions were obtained for a step change in contaminant concentration from
J. St-Pierre / Electrochimica Acta 55 (2010) 4208–4211
4209
Fig. 1. Modeled catalyst surface reactions. X, R and P respectively represent the contaminant, the reactant and the product of an electrochemical reaction.
an initially reactant stream free of contaminant:
i k = 1 − ek t/ − 1 icX =0 k k =
(1)
kR,ads kX,ads cR cX (p − ps )2 − kX,ads cX (p − ps ) − kX,des − kX kR,ads cR (p − ps ) + kR,des + kR (2)
k = kX,ads cX (p − ps ) −
kR,ads kX,ads cR cX (p − ps )2 kR,ads cR (p − ps ) + kR,des + kR
= − k − kX,des − kX ∝ cX
(3)
The steady state solution is (k < 0): i k =1+ icX =0 k
(4)
For the negative step change in concentration to a reactant stream free of contaminant, the expression is: i k −(kX,des +kX )t =1+ e icX =0 k
(5)
For the contaminant product desorption rds, expressions are identical with the exception that the kX,des + kX term is replaced by kP2 ,des leading to modified Eqs. (2) and (5): k =
kR,ads kX,ads cR cX (p − ps )2 − kX,ads cX (p − ps ) − kP2 ,des kR,ads cR (p − ps ) + kR,des + kR
i icX =0
=1+
k −kP2 ,des t e k
(6)
Fig. 2. Contamination processes steady state dimensionless current density and time constants as a function of contaminant concentration for a Pt based PEMFC. Eqs. (8) and (9) plots are based on k /k = −0.4358, k / = −0.008687 min−1 , (kX,des + kX )/ −1 obtained from 10 ppm CO data [9]. Curve fitting of or kP2 ,des / = 0.0356min steady state current density (k /k values from Eq. (1) fit) to Eq. (10) led to a = 18.55 and r2 = 0.15. Air/H2 + CO, 2.5/1.5 stoichiometry, 300/300 kPa, 80 ◦ C, 100% relative humidity, 0.5/0.5 mg Pt cm−2 , 0.6 V cell voltage.
Eq. (9) contains the same parameters as Eq. (8) and thus is also scalable to other contaminant concentrations. The /(kX,des + kX ) time constant (Eq. (5)) is independent of contaminant concentration. It is emphasized that the k /k parameter is not only obtained by direct experimental data fitting but is also derived from the combination of all similarly determined parameters (combination of k /k , /k and (kX,des + kX )/ as shown in Eq. (8)) thus providing a model self-consistency test. The steady state dimensionless current (Eq. (8)) and both time constants (Eq. (9)) are plotted as a function of contaminant concentration for the cases of a Pt (Fig. 2, [9]) and WC (Fig. 3, [10]) catalyst. Recent high temperature PEMFC data were also analyzed (Fig. 4, [11]) and resulting parameters were used to create similar plots (Fig. 5). The k /k parameters determined from curve fitting are also added to Figs. 2, 3 and 5 for comparison with Eq. (8) curves. The contaminant concentration is limited to 10% thus avoiding thermodynamic and mass transport model corrections which were not taken into account in the model derivation. Experimental data from [9,11] were obtained under constant cell
(7)
Because the different rds cases lead to the same solutions and only their interpretation is different, the discussion is focused on the contaminant reaction rds. Experimental data fitting to Eq. (1) leads to k /k and /k parameters whereas fitting to Eq. (5) leads to the /(kX,des + kX ) parameter. The steady state dimensionless current Eq. (4) is rewritten in terms of fitted parameters: i 1 = 1+ =1+ k icX =0 k
= 1−
1 −k −kX,des −kX k
=1−
1 1+
1 1+
kX,des +kX k k k
(8)
kX,des +kX k
In Eq. (8), only /k , obtained from the product of experimentally determined k /k and /k parameters, is proportional to the contaminant concentration (Eq. (3)) and thus is directly scalable to other contaminant concentrations. Similarly, the time constant −/k (Eq. (1)) is rewritten as: −
1 = − = −k −kX,des −kX k
1 k
+
kX,des +kX
(9)
Fig. 3. Contamination processes steady state dimensionless current density and time constants as a function of contaminant concentration for a WC based PEMFC electrode. Eqs. (8) and (9) plots are based on k /k = −0.03013, −1 k / = −3.078 min−1 , (kX,des + kX )/ or kP2 ,des / = 1.648min obtained from 1% CO data [10]. H2 + CO, 20 cm3 min−1 , 122 kPa, 70 ◦ C, 58 mg WC cm−2 , −0.35 V versus the mercury/mercurous sulfate reference electrode (equivalent to +0.299 V versus the SHE).
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J. St-Pierre / Electrochimica Acta 55 (2010) 4208–4211
cX < 0.9 ppm). The suggested value of 0.9 ppm is larger than the recommended value of 0.2 ppm [3] suggesting a tolerance limit increase is possible to reduce the analytical verification cost (quality control). An increase in CO tolerance limit from 0.2 to 2 ppm is projected to have a negligible effect on the hydrogen production cost. The suggested specification relaxation does not extend to the CO tolerance limit derived from the fitted k /k values which were correlated based on Eqs. (3) and (8): 1 i =1− icX =0 1 + ca
(10)
X
Fig. 4. Comparison between contamination and recovery transients [11], and model equations. Contamination data curve fitting led to k /k = −0.2343, k / = −0.04179 s−1 and r2 = 0.86. Recovery data curve fitting using k /k = −0.2343 led to (kX,des + kX )/ or kP2 ,des / = 0.05009 s−1 and r2 = 0.33. Air/H2 + 1.31% CO, 2 stoichiometry/400 cm3 min−1 , atmospheric pressure, 150 ◦ C, 0% relative humidity, 0.75/1 mg Pt cm−2 , 0.6 V cell voltage.
voltage rather than constant working electrode potential. Although not ideal, this option leads to a lower electrode potential variation (40–50 mV) than constant current operation (300–500 mV) and a good agreement with the model [8]. Reference electrodes are susceptible to contamination because the ionomer is permeable [8]. The use of a H2 counter-electrode or an ohmic loss compensated cell voltage control need to be explored [8]. 3. CO tolerance limit For Fig. 2, the steady state dimensionless cell current (Eq. (8)) starts to decrease after the CO concentration reaches a 5 ppm level (i/icX =0 = 0.95). Beyond a ∼2000 ppm level, the cell hardly produces any power (i/icX =0 = 0.05). The time constant associated with the recovery process (Eq. (5)) is ∼30 min and of the same order as the duration of a car excursion and thus the deleterious CO effect is not avoidable. The contamination time constant is equal to the recovery process time constant for low CO concentrations as is deduced from Eqs. (3) and (9). For larger CO concentrations, the contribution of the k / term in Eq. (9) increases leading to a time constant decrease. Because, the time constants are of the same order as the duration of a car excursion, the CO concentration specification needs to be set at a level that will hardly affect the cell performance under steady state conditions (i/icX =0 > 0.99,
Fig. 5. Contamination processes steady state dimensionless current density and time constants as a function of contaminant concentration for a Pt based PEMFC. Eqs. (8) and (9) plots are based on k /k = −0.2343, k / = −0.04179 s−1 , (kX,des + kX )/ or kP2 ,des / = 0.05009 s−1 obtained from 1.31% CO data [11]. Air/H2 + CO, 2 stoichiometry/400 cm3 min−1 , atmospheric pressure, 150 ◦ C, 0% relative humidity, 0.75/1 mg Pt cm−2 , 0.6 V cell voltage.
The fitted Eq. (10) (Fig. 2) indicates a lower tolerance limit of 0.2 ppm (i/icX =0 > 0.99) in comparison to Eq. (8) and is consistent with the specification [3]. The discrepancy between both steady state current density curves is ascribed to a low experimental data recording rate (for instance, 9 data points during the recovery period [9]) and relatively high experimental variability. As already mentioned for low contaminant concentrations, the time constants associated with the contamination and recovery processes are of equal duration (∼30 min). Therefore, the assumption that mass transfer (contaminant supply) rather than catalyst surface adsorption and reaction processes are controlling appear questionable [12]. The contamination recovery process is not mass transfer controlled because the contaminant is already on the catalyst surface and, ionomer and gas phase transport processes are rapid ranging from the millisecond to the second [8]. If mass transfer is controlling during the contamination process (supply rate), the contaminant distribution is expected to be non-uniform, a front moving across the cell separating catalyst regions either covered or free from contaminant. However, data obtained with an application size cell (∼300 cm2 active area) characterized by a significant pressure drop and coolant temperature rise along the flow field length, show that the current distribution is unaffected by contamination [13]. Other data obtained with a 5 cm2 active area cell appear to contradict this observation because the contaminant is detected at the cell outlet after a significantly long breakthrough time consistent with a non-uniform distribution [14]. However, the smaller cell contains more liquid water which scavenges the contaminant by dissolution because a significant pressure drop and temperature rise along the flow field length cannot be established to mitigate water accumulation by evaporation [15]. This hypothesis is confirmed by the effect of reactant stream flow rate which leads to an increase in pressure drop, a more effective liquid water removal, a less severe contaminant scavenging effect by liquid water and thus a worse contamination effect due to a larger effective contaminant concentration [14]. Fig. 3 data were obtained with a precious metal free WC catalyst, a result of fuel cell cost reducing activities [16]. For Fig. 3, plotted curves show the same behavior as in Fig. 2 with the exception that the time constants are significantly reduced (<0.6 min) and the CO tolerance limit is significantly increased (i/icX =0 > 0.99, cX < 0.1%). The improved CO tolerance is ascribed to a lower CO desorption temperature on WC than on Pt [17,18]. Fig. 3 results are achieved with a very high catalyst loading of 58 mg WC cm−2 , favoring the appearance of mass transport losses at high current densities owing to a much thicker catalyst layer and indicating the continuing need for alternate catalysts development activities. A good agreement is also found between both sets of steady state i/icX =0 values confirming the model consistency. It is also emphasized that few alternate catalysts are tested for contamination tolerance [1] and that such characterization is necessary for catalyst selection. Transients resulting from CO contamination of a Pt catalyst at high temperature, an approach considered to mitigate the system related heat rejection issue [19,20], are illustrated in Fig. 4. The model is in good agreement with contamination data but a
J. St-Pierre / Electrochimica Acta 55 (2010) 4208–4211
discrepancy is noted at the end of the recovery period. Model parameters illustrated in Fig. 5 again show a similar behavior as in Figs. 2 and 3. Time constants are shorter than 20 s and the CO tolerance limit is significantly increased (i/icX =0 > 0.99, cX < 0.07%) in comparison to a cell operated at a lower temperature (Fig. 2). This observation is ascribed to the significant lowering effect of temperature on CO surface coverage [21]. The good agreement found between both sets of steady state i/icX =0 values, thus confirming the model consistency, likely indicates that the discrepancy noted in Fig. 4 is due to another process. By comparison, Bergmann et al. found better agreement between their model and experimental data [11]. Although, significant differences exist between both models, including dimensionality (2 versus 0 dimension), adsorption kinetics (non-linear versus linear) and CO oxidation kinetics (water involvement is either taken or not into account), it is not possible to isolate a likely cause. Thus, additional data and analysis are required to reach a conclusion as already stated [11]. Eqs. (1), (5) and (7) indicate that the cell performance loss is independent of catalyst loading. Thus, a catalyst loading decrease to 0.1 mg Pt cm−2 necessary to successfully commercialize fuel cells [16] will not affect the cell performance loss and CO tolerance limit. 4. Conclusions A mathematical contamination model was used to derive CO tolerance limits for hydrogen used in PEMFCs. The proposed approach is advantageous because experiments performed with a single contaminant concentration value are sufficient to predict fuel cell behavior at other concentration values. A similar approach was developed for a contaminant that leads to an irreversibly adsorbed product such as SO2 or H2 S [8]. Implementation of these approaches requires experimental data obtained at a fixed electrode potential (use of a H2 counter-electrode or an ohmic loss compensated cell voltage control) and with step changes in contaminant concentration, still an uncommon practice. The determination of tolerance limits for other contaminants that do not lead to irreversibly adsorbed products under normal fuel cell operating conditions such as NO2 in air [13] and CO2 in H2 is not presently possible because experimental data obtained under these specific conditions are not available. Experimental data obtained under other expected operating conditions are also desirable (wider electrode potential, temperature and water balance ranges, both fuel cell compartments) and are under investigation within this funded program. Acknowledgements The author is indebted to the United States Department of Energy, Energy Efficiency and Renewable Energy for funding (National Renewable Energy Laboratory sub-contract ZGB-099180-01).
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Appendix A. Nomenclature
a cR cX i icX =0 k k kP2 ,des kR kR,ads kR,des kX kX,ads kX,des p ps t
curve fitting parameter defined by Eq. (10) reactant volume fraction in the dry stream contaminant volume fraction in the dry reactant stream current density (A m−2 ) steady state current density in absence of a contaminant (A m−2 ) lumped parameter defined by Eqs. (2) and (6) lumped parameter defined by Eq. (3) reacted contaminant desorption rate constant (mol m−2 s−1 ) reaction rate constant associated with a reactant (mol m−2 s−1 ) reactant adsorption rate constant (mol s−1 N−1 ) reactant desorption rate constant (mol m−2 s−1 ) forward reaction rate constant associated with a contaminant (mol m−2 s−1 ) contaminant adsorption rate constant (mol s−1 N−1 ) contaminant desorption rate constant (mol m−2 s−1 ) reactant stream pressure (N m−2 ) water vapor saturation pressure (N m−2 ) time (s) Pt site molar density (mol m−2 )
References [1] J. St-Pierre, in: F.N. Büchi, M. Inaba, T.J. Schmidt (Eds.), Polymer Electrolyte Fuel Cell Durability, Springer, New York, 2009, p. 289. [2] X. Cheng, Z. Shi, N. Glass, L. Zhang, J. Zhang, D. Song, Z.-S. Liu, H. Wang, J. Shen, J. Power Sources 165 (2007) 739. [3] ISO/CD 14687-2:2009. [4] T.E. Springer, T. Rockward, T.A. Zawodzinski, S. Gottesfeld, J. Electrochem. Soc. 148 (2001) A11. [5] T. Zhou, H. Liu, J. Power Sources 138 (2004) 101. [6] S. Enbäck, G. Lindbergh, J. Electrochem. Soc. 152 (2005) A23. [7] J. St-Pierre, J. Electrochem. Soc. 156 (2009) B291. [8] J. St-Pierre, J. Power Sources submitted for publication. [9] K.K. Bhatia, C.-Y. Wang, Electrochim. Acta 49 (2004) 2333. [10] D.R. McIntyre, G.T. Burstein, A. Vossen, J. Power Sources 107 (2002) 67. [11] A. Bergmann, D. Gerteisen, T. Kurz, Fuel Cells, in press. [12] J. Zhang, T. Thampan, R. Datta, J. Electrochem. Soc. 149 (2002) A765. [13] J. St-Pierre, N. Jia, R. Rahmani, J. Electrochem. Soc. 155 (2008) B315. [14] J. Zhang, R. Datta, Electrochem. Solid-State Lett. 6 (2003) A5. [15] D.P. Wilkinson, J. St-Pierre, J. Power Sources 113 (2003) 101. [16] H.A. Gasteiger, S.S. Kocha, B. Sompalli, F.T. Wagner, Appl. Catal. B 56 (2005) 9. [17] M.B. Zellner, J.G. Chen, J. Electrochem. Soc. 152 (2005) A1483. [18] M. Rosenbaum, F. Zhao, M. Quaas, H. Wulff, U. Schröder, F. Scholz, Appl. Catal. B 74 (2007) 261. [19] N.L. Garland, J.P. Kopasz, J. Power Sources 172 (2007) 94. [20] J. Mader, L. Xiao, T.J. Schmidt, B.C. Benicewicz, in: G.G. Scherer (Ed.), Advances in Polymer Science, vol.216, Springer, Berlin, 2008, p. 63. [21] A. Pitois, J.C. Davies, A. Pilenga, A. Pfrang, G. Tsotridis, J. Catal. 265 (2009) 199.