Degradation Mechanisms of Platinum Nanoparticle Catalysts inProton Exchange Membrane Fuel Cells: The Role of Particle SizeKang Yu,† Daniel J. Groom,† Xiaoping Wang,∥ Zhiwei Yang,‡ Mallika Gummalla,‡ Sarah C. Ball,§
Deborah J. Myers,∥ and Paulo J. Ferreira*,†
†Materials Science and Engineering Program, The University of Texas at Austin, Austin, Texas 78712, United States‡United Technology Research Center, East Hartford, Connecticut 06118, United States§Johnson Matthey Technology Center, Blount’s Court, Sonning Common, Reading, RG4 9NH, United Kingdom∥Argonne National Laboratory, Argonne, Illinois 60439, United States
*S Supporting Information
ABSTRACT: Five membrane-electrode assemblies (MEAs) withdifferent average sizes of platinum (Pt) nanoparticles (2.2, 3.5, 5.0,6.7, and 11.3 nm) in the cathode were analyzed before and afterpotential cycling (0.6 to 1.0 V, 50 mV/s) by transmission electronmicroscopy. Cathodes loaded with 2.2 and 3.5 nm catalystnanoparticles exhibit the following changes during electrochemicalcycling: (i) substantial broadening of the size distribution relative tothe initial size distribution, (ii) presence of coalesced particles withinthe electrode, and (iii) precipitation of submicron-sized particles withcomplex shapes within the membrane. In contrast, cathodes loadedwith 5.0, 6.7, and 11.3 nm size catalyst nanoparticles are significantlyless prone to the aforementioned effects. As a result, the electrochemically active surface area (ECA) of MEA cathodes loadedwith 2.2 and 3.5 nm nanoparticle catalysts degrades dramatically within 1000 cycles of operation, while the electrochemicallyactive surface area of MEA cathodes loaded with 5.0, 6.7, and 11.3 nm nanoparticle catalysts appears to be stable even after 10000 cycles. The loss in MEA performance for cathodes loaded with 2.2 and 3.5 nm nanoparticle catalysts appears to be due to theloss in electrochemically active surface area concomitant with the observed morphological changes in these nanoparticle catalysts.
■ INTRODUCTION
There is an intense drive to switch to more efficient and lesspolluting energy conversion devices for transportation applica-tions. Proton exchange membrane fuel cells (PEMFCs) are apotential choice due to their high efficiency, high energy density(approximately 0.7−0.9 W/cm2), large dynamic range ofoperation, and low operating temperatures (approximately 80°C).1,2 Despite these advantages, PEMFCs still face significanttechnical challenges before they become viable; one of the mostcritical is the durability of the nanoparticle catalyst in the cathode,particularly during cycling, which falls short of the 5000operating hour target set by the United States Department ofEnergy.3 Several studies in the past have related morphologicalchanges in the Pt nanoparticle catalysts, during fuel celloperation, particularly in the cathode, with performancedegradation.3,4
Wilson et al.5 first reported catalyst morphology changes inPEMFCs and correlated them to lower electrochemical perform-ance. Later, several degradation mechanisms were proposed forPEMFC durability loss,8−10 namely, (i) electrochemical Ostwaldripening, (ii) particle migration and coalescence, (iii) detach-ment from carbon support (mainly from carbon corrosion), and(iv) platinum dissolution and reprecipitation inside the ionomerphase. Shao-Horn et al.8 and Campbell et al.11 have claimed that
the dissolution rate and solubility should be accelerated bysmaller initial particle sizes due to their higher specific surfaceenergy.8,11 Holby et al.12 proposed that the role of the Gibbs−Thomson energy on the stability of particles is critical for particlesize below 5 nm. In particular, as the particle size decreases from5 to 2 nm, the Gibbs−Thomson energy increases significantly.Ascarelli et al.13 proposed that under pure Ostwald ripening, thePSDs of Pt should be broader and with a shift to larger sizes of thepeak. On the other hand, PSDs with tails to larger sizes arecorrelated with migration and coalescence.18 There is extensiveresearch work that discusses changes in Pt catalysts as a functionof cycling, changes in carbon support, platinum dissolution, andmembrane degradation. However, the relationship betweeninitial nanoparticle size and the various degradation mechanismsis still not clear. The answer to this question is critical for optimalMEA performance and for maintaining performance over thelifetime of the fuel cell while also minimizing Pt loading and thuscost. In this paper, we conduct a systematic study of the influenceof nanoparticle size on active degradation mechanisms and,ultimately, on the electrochemical performance of MEAs. To our
Received: May 23, 2014Revised: September 13, 2014Published: September 14, 2014
knowledge, this is the first time that a thorough and systematictransmission electron microscopy analysis has been performedon Pt catalysts to establish a fundamental correlation betweenparticle size and the various active degradation mechanisms inPEMFCs.
■ EXPERIMENTAL PROCEDUREMaterials.Catalysts were prepared at nominal 40 wt % Pt loading on
Akzo Nobel Ketjen EC300J via proprietary Johnson Matthey methods.The as-prepared catalyst was annealed at increasing temperatures toproduce catalysts with larger Pt particle sizes. These Pt/C catalystpowders were studied by TEM to provide the initial particle sizes andparticle size distributions. Samples were nominally denoted as 2.2, 3.5,5.0, 6.7, and 11.3 nm, which refer to the mean equivalent diameter of theparticles in the original powders. More detailed information about thesesamples will be discussed below. The as-received Pt/C powders wereused to fabricate the cathodes of the MEAs, as described in detail byYang et al.14 The MEAs were subjected to an accelerated stress testcycling protocol, recommended by the United States Department ofEnergy3 to evaluate catalyst durability, of 0.6 to 1.0 V at 50 mV/s withnitrogen on the cathode and 4% hydrogen on the anode.14 The cycledMEAs used in this paper and their test conditions are listed in Table 1and are also given in detail in Yang et al.14
Methods. TEM Preparation of Powders and MEA Cross Sections.As received Pt/C powders were prepared for TEM characterization byimmersing the samples in ethanol, followed by ultrasonication forapproximately 10 s to ensure dispersion and subsequent deposition ofthe powder on a carbon/copper grid. The nanoparticles were analyzedwith a JEOL 2010F TEM operated at 200 kV. In addition to the as-received powders, cycled samples were prepared from 5 mm × 2 mmsections cut from the 25 cm2 active area MEAs. These sections wereinitially coated with a Gatan-J1 epoxy mixture to improve stiffness;placed in a mold filled with an Araldite 6005, benzyl dimethylamine ,anddocenyl succinic anhydride mixture; outgassed to remove air at theMEA/epoxy interface; and cured in an oven at 60 °C for 8 h. The curedmolds were microtomed at room temperature to produce electron-transparent MEA cross sections of less than 100 nm thickness. Thenanoparticles present on the cathode side of these MEA cross sections,as well as in the membrane, were analyzed with a JEOL 2010F TEMoperated at 200 kV.Particle Size Analysis. To our knowledge, the protocol for
determining particle size and morphologies has not been yetstandardized, which precludes statistically significant analysis. Withregards to TEM, image analysis is complicated due to particleorientation and the presence of agglomerates and overlapping particles.In contrast, particle size analysis by X-ray diffraction and small angle X-ray scattering provides statistically significant results, but extractinginformation about the shape of particles is challenging. In this regard, wehave used a novel protocol developed during this project15 for counting
particles in used MEAs that addresses some of the shortcomingsencountered during TEM analysis.
In the case of the as-received powder samples, 200 particles wereanalyzed from each sample, using the software Image J. To choose the200 particles within the TEM images, a protocol outlining specificrequirements for particle analysis was created.15 Herein, specificmagnifications to obtain the TEM images were selected to set theequivalent error under 5%.
Image J’s outlining hand tool was used to highlight each particle thatmatched the above criteria. Because each image contains a differentnumber of distinguishable platinum particles, a second protocol wasneeded to determine how many particles should be collected from eachrepresentative image. The analysis represented in this paper selectedrandomly one of the representative images and collected all thedistinguishable particles from this image. Once completed, anotherrepresentative image was randomly chosen and all of its distinguishedparticles were outlined. This process continued until 200 particles werecollected. If a total of 200 particles were reached before analyzing all thedistinguishable particles within an image, a random generator picked outthe number of particles needed to complete the set of 200 from all thedistinguishable particles in that specific image.
In the case ofMEA samples, the cathode region was divided into threeareas, each approximately 3 μm wide and thereby covering a cathodewidth of approximately 10 μm. Two hundred particles were analyzedfrom each of the regions to give a total of six hundred particles for acathode section in a used MEA. The cathodes were intensivelyinvestigated relative to the anode side because previous studies7 haveshown that cathodes undergo substantial change relative to the anodesduring fuel cell operation.
Cathode Catalyst Surface Area and Performance Analysis. Theelectrochemically active surface area (ECA) of the cathode catalyst wasmeasured using a cyclic voltammogram taken at 10 mV/s between 0.03and 1.0 V (vs anode) with nitrogen flowing on the cathode, 4%hydrogen (balance nitrogen) on the anode, and a cell temperature of 80°C. The ECA values (m2/g-Pt) were calculated by integrating thehydrogen adsorption charge in the cathodic-going sweep of thevoltammogram, multiplying by the cell area, and dividing by 210 μC/cm2 (theoretical hydrogen monolayer adsorption on Pt) and thecathode Pt loading.14
Aqueous Dissolution Rates. The dissolution rate of Pt from the fivePt/C catalysts was studied under the same potential cycling profile aswas used for the MEAs. Gas diffusion electrodes (GDE) were preparedusing the five catalysts powders as described in Ahluwalia et al.16 TheGDE samples were immersed in 0.57 M HClO4 (GFS, double distilled,<0.1 ppm of Cl−, in 18 MΩMillipore water) in a rotating disk electrode(RDE) cell in a traditional three-electrode configuration with a goldcounter electrode located in a fritted compartment and an Hg/Hg2SO4reference also located in a separate fritted compartment (all potentialshave been converted to the reversible hydrogen electrode scale). Theelectrolyte was bubbled (saturated) with Ar while the GDEs were cycledbetween 0.6 and 1.0 V at 50 mV s−1 for 50 cycles. A small volume ofelectrolyte (∼1−1.5 mL) was removed from the cell and analyzed fordissolved Pt content using high-resolution inductively coupled plasma-mass spectrometry (Fisons Quadrupole PQII+ ICPMS and VGElemental High-Resolution AXIOM ICPMS). The ECAs of the Pt/Csamples were determined by integrating the background-correctedcharge in the hydrogen adsorption region and using a specific charge of210 μC/cm2. Dissolution rates were determined by calculating theamount of dissolved Pt in the electrolyte from the ICP-MS-determinedPt concentration and the electrolyte volume in the RDE cell and theECAs measured prior to potential cycling. Additional information aboutthese measurements is reported in Ahluwalia et al.16
■ RESULTS AND DISCUSSION
Figure 1 shows the average equivalent diameter and particle sizedistributions (PSDs) obtained from the TEM characterization ofthe as-received powders used to fabricate the MEAs. Clearly, thePSDs become broader with increasing particle size. A similar
Table 1. MEAs Used in This Study, Number of PotentialCycles to Which the MEAs Were Subjected, the CatalystLoading of the MEAs, and the MEA Test Protocols
TEM analysis of the as-prepared MEAs revealed no meaningfulchange in the PSDs associated with MEA fabrication.Subsequent to this analysis, the samples were subjected to
electrochemical cycling in MEAs under the conditions shown inTable 1 and described in greater detail in Yang et al.14 Figure 2shows the changes in the ECA of the five different Pt cathodecatalysts resulting from potential cycling of MEAs.According to the ECA decay rates, the degradation of the
MEAs as a function of the number of cycles was substantiallygreater for the MEAs containing the 2.2 and 3.5 nm Ptnanoparticle cathode catalysts compared to the 5.0, 6.7, and 11.3nm catalysts. While ECA losses proceeded at a significant ratewithin 10 000 cycles for the 2.2 and 3.5 nm samples, the othersamples exhibited good stability up to 10 000 cycles. In the caseof the 11.3 nm sample, the initial performance was too low forcell feasibility.14 As the ECA for the 5.0 and 6.7 nm samplesshowed minimal decay after 10 000 cycles, these MEAs werefurther subjected to a total of 30 000 cycles. As shown in Figure 2,the ECA of the 6.7 nm sample decreased only slightly from 10
000 cycles to 30 000 cycles, while the 5.0 nm sample showedremarkable stability.The TEM characterization of these cycled MEAs offers further
insight into the electrochemical data. The mean particle size,obtained by TEM, of cycled MEAs as a function of initial particlesizes, is shown in Figure 3. Clearly, the catalysts with the smallest
initial particle sizes end up with the largest particle sizes after 10000 cycles, except for the 11.3 nm sample. Relative to their initialsize, the 2.2 and 3.5 nm particles exhibit an increase of 370% and170% after 10 000 cycles, whereas the 5.0 nm, 6.7 and 11.3 nmsamples show an increase of 23%, 1% and 13%, respectively, afterthe same number of cycles. For the samples with initial sizes of5.0 and 6.7 nm after 30 000 cycles, there is an increase in particlesize of 43% for both samples. A more detailed characterizationcan be seen in Figures S1−S7. For MEAs with initial sizes of 2.2and 3.5 nm, after 10 000 potential cycles the mean particle size inthe three regions (A−C) has grown significantly, and the PSDshave broadened. On the other hand, for the MEAs with initialsizes of 5.0, 6.7, and 11.3 nm, after 10 000 cycles there is only aslight increase in the mean particle size in regions A−C. After 30000 cycles, for the MEAs with cathodes comprised of the Pt withinitial sizes of 5.0 and 6.7 nm, larger mean particle sizes andbroader PSDs could be observed in the three regions whencompared to that of the cathode subjected to 10 000 potentialcycles. In contrast to a previous study,7 the particle size is foundto not differ significantly throughout the cathode thickness foreach of the samples. We believe that the larger particle size closeto the membrane in ref 7 partly resulted from faceted anddendritic particles within the cathode. These two kinds of
Figure 1. (a−e) PSDs and TEM images from the 2.2, 3.5, 5.0, 6.7, and11.3 nm mean diameter Pt/C powders, respectively.
Figure 2.Change in the ECAs of the cathode catalyst in variousMEAs asa function of the number of potential cycles of the cathode between 0.6and 1.0 V at 50 mV/s.
Figure 3.Mean particle size of cycled MEAs with various initial particlesizes.
particles result from dissolution and reprecipitation as describedin ref 6. However, in our work, this type of reprecipitated particleis hardly found across the cathode. The difference between ref 7and our work is the fact that the sweep rate of the potentialcycling is different. In ref 7, the sweep rate is 20 mv/s, while ourwork is 50 mv/s. It has been proposed that a slower sweep rateleads to a higher dissolution of Pt.17 Thus, there are more Pt ionsin the cathode-membrane interface for the case of ref 7, which inturn lead to higher reprecipitation of Pt particles within thecathode. Moreover, the sample in ref 7 has higher Pt loading (0.4mg-Pt/cm2) than the current work (0.2 mg-Pt/cm2), whichresults in a higher amount of dissolved Pt and consequentlyhigher reprecipitation within the cathode. In order to correlatethe ECA loss with the mean particle size growth, the ratio ofcycled ECA to initial ECA and ratio of initial particle size tocycled particle sizes are plotted as a function of initial particle size,as shown in Figure 4. Basically, the ECA loss is in agreement withthe particle size growth in each sample.
To explain the results shown in Figure 3 and Figures S1−S7 inthe Supporting Information, a simple first approach is to considerthe PSDs of the various samples. Granqvist and Buhrman haveshown that PSDs with tails to larger particle sizes are associatedwith particle growth via migration and coalescence.18 In contrast,a PSD indicative of growth through electrochemical Ostwaldripening involves a peak toward large particle sizes with tailing tosmaller sizes.18 As Figures S1−S7 show broadened PSDs withtails to large sizes, this seems to suggest that the resultant ECAloss is due to a migration and coalescence mechanism. However,the above models make several assumptions that do not apply toPEMFCs. Most importantly, the models assume that only onegrowth mode occurs and that the system is thermodynamicallyclosed. However, the presence of Pt in the membrane of each ofthese MEAs renders these models inapplicable to this study.Furthermore, previous studies have demonstrated that othergrowth mechanisms can lead to PSDs similar to this work. Forexample, in the work of Ferreira and Shao-Horn,6 a log-normalPSD with tailing to large particles was found in the cathode areaand off-carbon support. This PSD was claimed to be related withdissolution and reprecipitation of Pt rather than migration andcoalescence. Hence, to fully understand the changes in particlesize and related PSDs shown in Figures S1−S7, various possiblemechanisms must be addressed.Consider first the dissolution and reprecipitation of Pt in the
ionomer. This mechanism is associated with the chemicalreduction of Pt ions by crossover hydrogen from the anode.Reprecipitated particles can be located either in the membrane or
off carbon support in the cathode area. Ferreira et al. have shownthat these reprecipitated particles exhibit specific shapes otherthan spherical.7 After careful observation of the TEM imagesshown in Figures S1−S7, it is clear that no particlesreprecipitated in the ionomer phase of the cathode. However, asignificant amount of particles reprecipitated within themembrane. Figure 5a−g show TEM bright-field images of the
cathode-membrane interface for all the samples. It is evident thatfor the 2.2 nm sample there is a dense region of reprecipitated Ptparticles at the cathode−membrane interface and in themembrane (Figure 5a), while for the 11.3 nm sample thisphenomenon is practically absent (Figure 5e).To quantify the amount of reprecipitated particles in the
membrane, the ratio of the mass of reprecipitated particles in themembrane to the total mass of particles in the cathode before
Figure 4.Correlation between ECA loss andmean particle sizes increaseamong MEAs after 10 000 potential cycles.
Figure 5. Cathode−membrane interface of MEAs of initial sizes of (a)2.2 nm, (b) 3.5 nm, (c) 5.0 nm, (d) 6.7 nm, (e) 11.3 nm after 10 000cycles, (f) 5.0 nm, and (g) 6.7 nm after 30 000 cycles.
cycling is compared in each sample. The ratio is denoted as Rpand expressed as
=∑∑
=
=R
m
min
inp
1 membrane
1 cathode (1)
Herein, mmembrane is the mass per unit area of eachreprecipitated particle in the membrane after cycling and mcathodeis the mass per unit area of each particle in the cathode beforecycling. To calculate the mass of each particle in the membraneand cathode, the equivalent diameter is obtained from theprojected area for each particle, and the volume is calculatedassuming the particles are spherical. The Rp values calculated forsamples with initial sizes of 2.2, 3.5, 5.0, 6.7, and 11.3 nm with 10000 cycles are 8.0%, 5.9%, 2.9%, 2.8%, and <0.1%. In this regard,the mass loss due to the reprecipitation of Pt ions to the cathode/membrane interface and/or membrane is not significant for the5.0 nm, 6.7 nm, and 11.3 nm samples after 10 000 cycles, whichindicates that platinum dissolution and reprecipitation shouldnot be the main degradation mechanism for these particle sizes.However, for the 2.2 and 3.5 nm samples, the reprecipitation ofPt ions seems to be relevant.In general, the larger the initial particle size, the lower the
amount of reprecipitated particles in the membrane. This is dueto the particle size dependence of the dissolution rate of Pt, asillustrated in Figure 6, which can be attributed to the Gibbs−
Thomson effect, which induces an effectively higher potential onthe particles with decreasing particle size.8 For example, theeffective potential is approximately 180 mV higher for a 2.5 nmparticle as compared to an extended surface of Pt (e.g., a Ptwire).8
Second, consider the electrochemical Ostwald ripeningmechanism. This involves the dissolution of Pt, followed bythe diffusion of Pt ions through the ionomer and redeposition ofPt ions on larger Pt particles. The redeposition process does notchange the original morphology of larger particles, as electro-chemical Ostwald ripening is an isotropic process. Therefore,since the as-received powder contains predominantly sphericalparticles, a careful measurement of spherical particles on thecarbon support in cycled MEA should quantify the extent ofelectrochemical Ostwald ripening. This is shown in Figures 7 and8.For the measurements of spherical particles, the cathode area
was divided into three regions and 200 were selected from eachregion, following the procedure described in the Experimental
Procedure. The particles were selected only if their roundness, R,was larger than 0.9. The parameter R is defined in terms of itsprojected area A and the major axis (a) of an ellipse fitted to theparticle outline, according to the expression
π=R
Aa
42 (2)
In digital images, the major axis (a) equals the equivalentdiameter of a circle. As shown in Figures 7 and 8, the mean size ofspherical particles for the 2.2 and 3.5 nm MEAs after 10 000cycles exhibits significant growth, while for the 5.0, 6.7, and 11.3nmMEAs, the growth is negligible. However, it is evident that forthe 5.0 and 6.7 nm MEAs, after 30 000 cycles, spherical particlesgrow considerably. This overall growth behavior indicates thatelectrochemical Ostwald ripening is severe in 2.2 and 3.5 nmcycled MEAs and significant in the 6.7 nm MEA after 30 000cycles. On the other hand, 5.0 nm cycled MEAs showednegligible growth after 10 000 cycles and 30 000 cycles, as well as11.3 nm cycled MEAs. This is contradictory to the typical PSDscaused by electrochemical Ostwald ripening, which show a tailfor small particle sizes and a maximum particle size cutoff.18 Yet,as discussed above, the cathode is not a closed system due to theloss of Pt into reprecipitated particles in the membrane.To illustrate the impact of the electrochemical Ostwald
ripening mechanism on the overall degradation process, Figure 9shows the ratio rd/ra between the mean of spherical particle sizesin cycled MEAs (rd) and the mean of as-received particle sizes(ra), as well as the ratio rt/ra between the mean of all particle sizesin cycled MEAs (rt), which comprise spherical and nonsphericalparticles, and the mean of as-received particle sizes (ra).It is evident that the ratio rd/ra increases drastically for the
samples with initial particle sizes of 2.2 and 3.5 nm. In addition,Figure 9 shows that as the initial particle size increases thedifference between ratios rt/ra and rd/ra decreases. These tworesults confirm that the electrochemical Ostwald ripening ispredominant inmost of the samples, except for the case of the 2.2nm sample, where other mechanisms are playing an importantrole.A third possible mechanism is the migration and coalescence
of nanoparticles. Coalesced particles were present in all thecycled MEAs, as shown in Figure 10. Morphologies resultingfrom aggregation−coalescence represent a form of ECA loss notdirectly quantified by the PSDs.The widespread presence of necked nanoparticles and larger
coalesced particles in each sample provides a means to quantifythe percentage of Pt that has experienced ECA loss due to theaggregation and coalescence and thus a means to compare therelative impact of this mechanism as a function of initial particlesize. To this end, the projected area (A) of Pt in each image wasseparated into one of two categories: (1) Pt in the form ofindividual nanoparticles (AIndividual) and (2) Pt exhibiting clearaggregation−coalescence (ACoalesced). Particle overlap wasexcluded from this analysis but accounted for no more than10% of Pt for each image.The area percentage of coalesced particles was calculated from
the ratio of the projected area of coalesced Pt (ACoalesced) to thetotal projected area of Pt (ATotal = ACoalesced + AIndividual). Figure 11shows the result of this analysis. For the MEAs with 10 000cycles, the coalesced area for the 2.2 and 3.5 nm samples aremuch higher than other samples, while the coalesced area for the2.2 nm sample is the highest of all samples.Despite these results, the formation mechanisms associated
with coalescence are ambiguous. Figure 12 shows several
Figure 6. Pt dissolution rate as a function of initial particle size inaqueous environment.
hypotheses. First, coalesced particles may result from nano-particles migrating and coalescing on the carbon support (Figure12a). However, in situ TEM experiments performed on these
particles at 1000 °C in the absence of current/voltage showed noparticle migration.19 Yet, the lack of ionomer, water, the oxidizingconditions of high potentials, and potential cycling could alter
Figure 7. PSDs of spherical particles in MEAs after 10 000 cycles.
Figure 8. PSDs of spherical particles in MEAs after 30 000 cycles.
significantly the migration process. Second, it is possible thatcoalesced particles are the result of growth of adjacent particlesinto each other due to Pt redeposition on the surface (Figure12b).Third, it is plausible for Pt atoms to reprecipitate between two
spherical particles and form a bridge between pre-existingparticles. In recent simulations of the changes in Pt nanoparticlePSDs induced by potential cycling, Ahluwalia et al.18 concludedthat the observed growth in Pt particle size and loss of ECA inaqueous andMEA tests are primarily due to particle coalescence/sintering resulting from redeposition of dissolved Pt betweenadjacent Pt particles. Asoro19 has provided evidence forcoalescence by reprecipitation in their high temperature in situTEM experiments. The coalesced particles could result, however,from migration, followed by electrochemical Ostwald ripening.In general, as the Pt loading is the same for all samples, the
mean separation distance between particles decreases as theaverage particle size decreases. Thus, assuming each particle isspherical, the number of particles per unit area can be expressedas
π ρ=
· ·N
md(4/3) ( /2)3
(3)
where d is the mean equivalent diameter of the particles, m is themass of Pt per unit area, and ρ is the density of Pt. Assuming aunit area of sample, if we have N particles uniformly distributedper unit area, then the number of particles per unit length isN1/2,which is equal to 1/D, whereD is the distance between the center
Figure 9. Comparison of mean particle size between cycled MEAs after10 000 cycles and powders.
Figure 10. Coalesced particles in cycled MEAs with initial sizes of (a)2.2 nm, (b) 3.5 nm, (c) 5.0 nm after 10 000 cycles, (d) 6.7 nm after 10000 cycles, (e) 11.3 nm, (f) 5.0 nm after 30 000 cycles, (g) 6.7 nm after30 000 cycles.
Figure 11. Area fraction (%) of Pt formed by coalescence in usedcathodes as a function of initial Pt particle size.
Figure 12. (a) Coalesced particles formed by particle migration. (b)Coalesced particles formed by increased particle sizes throughdissolution and redeposition. (c) Soluble Pt species reprecipitated andbridged two particles.
of the particles. As a result, D = N−1/2, and thus, from eq 3, D isproportional to d2/3.Under the ideal conditions described above, the distances
between particles in samples with initial particle sizes of 2.2, 3.5,5.0, 6.7, and 11.3 nm were found to be 1.0, 3.0, 6.2, 10.6, and 27.9nm, respectively. Therefore, the coalescence mechanismsdescribed in Figure 12 should be enhanced by the shorterdistances between particles, and their prevalence should increasewith decreasing particle size. This explains well the comparativelylarge difference between rt/ra and rd/ra among samples withinitial sizes of 2.2 and 3.5 nm. This also means that there is astrong correlation between the electrochemical Ostwald ripeningmechanism and the coalescence mechanism through growth ofadjacent particles into each other (Figure 12b). In fact, a higherdissolution rate with decreasing particle size and the consequentredeposition of Pt onto larger particles will cause degradation ofthe MEAs through both electrochemical Ostwald ripening andcoalescence. Ahluwalia et al.16 have provided evidence for thisthrough modeling. Thus, prevention of the dissolution of Ptshould be one of the main considerations to stop loss of Ptnanoparticle ECA and the consequent decrease of PEMFCperformance.We are now left with the task of comparing the TEM
observations with the ECA degradation as a function of thenumber of cycles (Figure 2). To better understand thiscorrelation, we compare the geometric surface area (GSA),which is the calculated surface area from the particles observed inthe TEM images of the cathode (in units of m2/gPt) and the ECA.Assuming each particle is spherical, the calculation of GSA isshown in ref 7. To calculate the initial GSA of each sample, 200nanoparticles from the as-received powder were used, while tocalculate the GSA of the cycled samples, 600 nanoparticles fromthe three regions were used.Figure 13 shows the ECA to GSA ratio before cycling, which
refers to the utilization of the nanoparticles.20 Surprisingly, the
ECA/GSA value for each sample is below 1 except for the 11.3nm sample, which is approximately 1. A similar result has beenalso shown by Ahluwalia et al.20 These data mean that not all ofthe available surface area of the nanoparticles is contributing tothe ECA measurement and to the ORR process.One possible explanation for this is that due to agglomeration,
part of the geometric surface area is not available for thehydrogen adsorption reaction used for the ECA measurements,which would lead to lower ECA/GSA values. Anotherexplanation is that the applied MEA conditioning procedurecauses significant degradation of the particles prior to the firstECA measurement. Ahluwalia et al.20 have compared ECA/GSAratios for the same catalysts in aqueous acidic electrolyte and in
MEAs and found that the ECA/GSA ratios in the aqueousenvironment were either identical to or slightly lower than thosein the MEA environment, indicating that ionic conductivitylimitations in the MEA cathodes are not responsible for theobserved decrease in ECA with decreasing particle size. Anotherplausible reason has to do with the contact area between thenanoparticles and the carbon support. Figure 14 shows
tomographic TEM images of the nanoparticles on the carbonsupport. Clearly, the carbon support exhibits a convoluted 3Dstructure. As a result, the larger particles are likely to have smallerfractions of surface area in contact with the carbon support, thanthe smaller particles, as illustrated in Figure 14d and e. Thus, thesmaller particles may not have ready access to protons for theECA measurements and oxygen for the ORR reaction in the fuelcell. This trend indicates that the utilization of surface area in thecatalysts increases with increasing initial particle size.For the cycled MEAs, the relationship between ECA and GSA
is shown in Figure 15. Ahluwalia et al.20 also showed cycled
ECA/GSA values in aqueous environment. It is evident that forthe samples with initial sizes of 2.2, 3.5, and 11.3 nm, the cycledECA/GSA values are larger than for samples with initial sizes of5.0 and 6.7 nm after 10 000 cycles, while the ECA/GSA values forthe samples with 5.0 and 6.7 nm after 30 000 cycles are higherthan that after 10 000 cycles. This may be attributed to the largermean particle sizes after cycling among the samples with higher
Figure 13. Value of initial ECA/GSA as a function of initial particle size.
Figure 14. Tomographic images for the carbon support tilted to (a)−60°, (b) 0°, and (c) +60°. (d) Small and (e) large particles in contactwith carbon support.
Figure 15. Cycled ECA/GSA as a function of initial particle sizes.
ECA/GSA values, which result in less surface area in contact withthe carbon support. Surprisingly, some of the ECA/GSA valuesare larger than 1, which indicates that the surface area calculatedfrom TEM images is underestimated or the ECA is over-estimated. In the former case, one possible explanation for thesedata is the shape of particles. Spheres have the smallest surfacearea to volume ratio and thus the smallest GSA. This was theassumption when calculating the GSA in the cycled MEAs andthe powders. However, while particles are spherical in the as-received powders, the fraction of nonspherical particles increasesin the cycled MEAs, especially for the 2.2 and 3.5 nm samples,which is likely to lead to cycled ECA/GSA ratios >1. In terms ofoverestimating the ECA, it could result from inclusion of chargedue to hydrogen evolution in the calculation of ECA fromhydrogen adsorption.
■ CONCLUSIONSIn this work, we show that the catalysts with the smallest initialparticle sizes end up with the largest particle sizes after 10 000cycles, except for the 11.3 nm sample. As a result, the ECA lossfor Pt nanoparticle catalysts with initial sizes of 2.2 and 3.5 nm,after 10 000 potential cycles, was found to be more significantthan for particles with sizes ranging from 5.0 to 11.3 nm. In termsof degradation mechanisms, this research shows that, bycomparing the mean size of spherical particles of the powdersamples and cycled MEAs, electrochemical Ostwald ripening ismore pronounced in MEA samples with initial particles sizes of2.2 and 3.5 nm. In addition, the ECA loss due to dissolution andreprecipitation of Pt particles in the membrane is only relevantfor the 2.2 and 3.5 nm particles. Finally, coalescence is evidentamong all the samples, and the prevalence of this mechanismincreases with decreasing particle size. Overall, Pt dissolutionseems to be the controlling mechanism for degradation, as itassists the electrochemical Ostwald ripening process and twoplausible mechanisms of coalescence. Thus, reducing Ptdissolution, which is more severe in the smallest particle sizes,is the most important factor to prevent ECA loss and catalystperformance degradation under these potential and potentialcycling conditions. The correlation between the TEM-determined geometric surface area (GSA) of the Pt particlesand the experimentally determined ECA data, where the initialECA/GSA ratio increases with increasing particle size, seems toindicate that the contact area between the particles and thecarbon support is affected by particle size due to the 3-D nature ofthe carbon support.
■ ASSOCIATED CONTENT
*S Supporting InformationPSDs and representative TEM-bright field images of cycledMEAs are provided. This material is available free of charge viathe Internet at http://pubs.acs.org.
Author ContributionsThe manuscript was written through contributions of all authors.All authors have given approval to the final version of themanuscript.
NotesThe authors declare no competing financial interest.
■ ACKNOWLEDGMENTSThe authors would like to thank Dwight Romanovicz, SamanthaChen, and Andres Godoy from UT−Austin for preparing themicrotomed MEA samples for TEM cross-section observation.The authors would also like to thank Brian Theobald, ElvisChristian, and the Analytical Team at the Johnson MattheyTechnology Centre for preparation and initial characterization ofcatalyst materials. The authors wish to thank the AnalyticalChemistry Laboratory and Dr. Yifen Tsai at Argonne NationalLaboratory for the ICP-MS analyses. This work was supported bythe Fuel Cell Technologies Office of the U.S. Department ofEnergy’s (DOE) Office of Energy Efficiency and RenewableEnergy. Dr. Nancy Garland was the DOE technology develop-ment manager for this work. Argonne is a DOE, Office of ScienceLaboratory operated under Contract No. DE-AC02-06CH11357by UChicago, Argonne, LLC.
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