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Atomically resolved dealloying of structurally ordered Pt nanoalloy as oxygen reduction reaction electrocatalyst Andraž Pavliši#, Primož Jovanovi#, Vid Simon Šelih, Martin Šala, Marjan Bele, Goran Draži#, Iztok Arcon, Samo B. Hocevar, Anton Kokalj, Nejc Hodnik, and Miran Gaberscek ACS Catal., Just Accepted Manuscript • DOI: 10.1021/acscatal.6b00557 • Publication Date (Web): 11 Jul 2016 Downloaded from http://pubs.acs.org on July 11, 2016
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Atomically resolved dealloying of structurally ordered Pt nanoalloy as oxygen reduction reaction electrocatalyst Andraž Pavlišič†,‡, Primož Jovanovič†, Vid Simon Šelih§, Martin Šala§, Marjan Bele†, Goran Dražić†, Iztok Arčon∥, Samo Hočevar§, Anton Kokalj⊥, Nejc Hodnik‡, Miran Gaberšček*†,# †
Department for Materials Chemistry, National Institute of Chemistry, Hajdrihova Ulica 19, SI-1000 Ljubljana, Slovenia ‡
Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Hajdrihova Ulica 19, SI-1000 Ljubljana, Slovenia §
Department of Analytical Chemistry, National Institute of Chemistry, Hajdrihova Ulica 19, SI-1000 Ljubljana, Slovenia
∥
Laboratory of Quantum Optics University of Nova Gorica Vipavska 13, SI-5000, Nova Gorica, Slovenia
⊥
Department of Physical and Organic Chemistry Jožef Stefan Institute Jamova 39, 1000 Ljubljana, Slovenia
#
Faculty of Chemistry and Chemical Technology, University of Ljubljana, Večna pot 113, SI-1000 Ljubljana, Slovenia
Supporting Information Placeholder ABSTRACT: The positive effect of intermetallic ordering of platinum alloy nanoparticles on oxygen reduction reaction (ORR) activity has been well established. What is still missing is the understanding of selective leaching of the less noble metal from ordered structure and its correlation to long-term ORR performance. Using a combination of Kinetic Monte Carlo simulations and advanced characterization techniques, we provide unprecedented insight into dealloying of intermetallic PtCu3 nanoparticles - a wellknown binary alloy. Comparison of ordered and disordered samples with identical initial composition and particle size distribution reveals an unexpected correlation: whereas the copper dealloying rates in the ordered and disordered counterparts are almost the same, in the ordered structure Pt atoms are surrounded by 15-30% more Cu atoms throughout all the stages of acid leaching. This more convenient Pt-Cu coordination explains the statistically significant increase of 23-37% in ORR activity of the ordered structure at all stages of alloy degradation. KEYWORDS: ORR activity, fuel cells, platinum alloy, nanoparticles stability, intermetallic ordering, kinetic Monte Carlo, dealloying, in-situ ICP-MS In the recent decade, efforts to build up a sustainable, renewable and environmentally friendly energy infrastructure have intensified the research on Proton 1 Exchange Membrane Fuel Cell (PEM-FC) technology . Significant progress has been made in the development of high performance cathode catalysts such as bimetallic alloys 2 of PtX (X=Ni, Co, Fe, Ru, Cu) . When in contact with platinum, transition metals can considerably enhance the rate of electrochemical oxygen reduction reaction (ORR), due to the so-called substrate-induced strain and/or the 3 ligand effect through d-band center shift . A common
method of preparing Pt nanoalloy electrocatalysts is selective 4 removal of the less noble metal or dealloying , which leaves behind a Pt rich nanoporous film, a skeletal surface or a core1a, 2e-g, 2i, 5 shell particle configuration . On the down side, Pt alloys tend to lose their performance due to thermodynamic instability of the less noble metal in highly acidic and 1b, 2h, 6 oxidative PEM-FC environment . Structural ordering of Pt based alloys has proved an efficient way to increase their 5b, 7 electrocatalytic performance . Intermetallic ordering, as a general approach, is also widely used with other non-Pt 8 9 compositions and in other important applications . However, to the best of our knowledge, there are no studies available that explain, on the atomic level, the beneficial effect of dealloyed ordered Pt nanoalloy on ORR performance. Herein time-resolved copper dissolution from ordered and disordered PtCu3 analogues is measured with on-line Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Extended X-ray Absorption fine Structure (EXAFS) and modeled with 3D Kinetic Monte Carlo simulations (KMC). Novel insights on the atomic level provide a reasonable explanation for two seemingly contradictory effects: whereas structural ordering has only a minor effect on the amount of copper that is removed from the binary alloy, it still greatly affects the activity of alloy also after prolonged dealloying times. As we show, this unexpected lack of correlation is due to formation of significantly different local structures of the remaining Cu around Pt atoms when starting from the initially ordered phase if compared to starting from the disordered alloy. In other words, we demonstrate experimentally and theoretically the beneficial effect of structural ordering on ORR activity also after prolonged alloy degradation when a large portion of the less noble metal has been removed.
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Although dealloying of Pt based alloyed materials has 2e, 2i, 5a, 5d, 5e, 6d, 6e, 7c, 7d, 10 already been thoroughly investigated , the focus has been on disordered alloyed structures in which the constituent atoms are randomly scattered throughout the structure (Figure 1). By contrast, much less effort has been devoted to the fundamental understanding of enhanced 5b, 6d, 6e, 7c-e , performance of intermetallic Pt nanoalloys especially on the atomic scale. Unlike in disordered alloys, in the ordered counterparts the atoms of different components occupy well defined positions, so the local interatomic interactions are different, which has been shown to exhibit a markedly positive effect on the electrocatalytic performance. In general, during thermal treatment of alloys the ordering 7d, 11 initially develops in the outer shell of the particles . An example of PtCu3 structure (Pm̅3̄m) recorded by atomically resolved High-Angle Annular Dark Field imaging Scanning Transmission Electron Microscopy (HAADF/STEM) is shown in Figure 1. The corresponding simulation grids of nanoparticles are displayed as well. As already shown before, even a small portion of shell ordering has a considerable 6d, 7d effect on alloy activity . In this paper, the thickness of the ordered phase in the so-called “shell-ordered material” was typically several nanometers. The disordered sample was prepared by quenching the ordered sample; therefore both the ordered and disordered samples have identical 7d composition and particle size distribution (see Supporting Information for sample preparation, powder XRD - Figure S1 and particle size distribution - Figure S2). As a proof of concept and reversibility, again ordering was induced by annealing the disordered sample, which recovered all of the beneficial effects of intermetallic ordering.
Figure 1. HAADF/STEM images of representative shellordered (left) and disordered (right) nanoparticles. Half of the particles are schematically presented by atomic simulation for better understanding. In one type of dissolution experiments the PtCu3/C catalyst (ordered or disordered) was soaked in a 0.1 M HClO4 and the released copper was monitored using ICP-MS (Figure 2a). Further experimental information can be found in the Supporting Information. It can be seen that the rate of dealloying is slightly higher for the disordered alloy throughout the experiment. The relative difference in the dissolved amount of copper is rather small (in average less than 5%) (Figure 2d) and tends to vanish as the time is extrapolated to infinity. In both cases, under present conditions a quasi-steady state seems to be achieved soon after the last points shown (12 h), as the copper content remains more or less unchanged even after 72 h (see Table S1). This final copper content was found comparable to the one determined for the same type of sample after the socalled severe electrochemical degradation test, that is after
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50,000 cycles between 0.4 V and 1.4 V vs. RHE using a rate of 12 1 V/s and 0.1 M HClO4 .
Figure 2. Dissolution and electrochemistry results of ordered and disordered samples: a) time-resolved copper dissolution ICP-MS response and b) specific activities (SA) during dissolution experiments (0.1 M HClO4). c) ICP-MS response during chronoamperometry experiment at 0.9 V in 0.1 M HClO4 (zig-zag curves) and KMC simulation (lines). d) Relative difference between the ORR activities and copper contents of the two samples. Along the same timescale, the values of electrochemical ORR activities for the same PtCu3/C analogues were also collected (Figure 2b and in Table S2; further experimental data is provided in Supporting Information). During the whole experiment, the activities of the ordered sample are markedly higher than those of the disordered counterpart (Figure 2d). This is rather unexpected since, as shown above, the corresponding differences in the amounts of dissolved copper are hardly noticeable. More specifically, in the timeframe between 3-12 h, the differences in dissolved copper are 2-5% whereas the differences in measured catalytic activities are between 23-37% in favor of the ordered sample (Figure 2d). The latter result is in good agreement with ORR 7d measurements performed in our previous study where the specific activities of the ordered sample were consistently higher by 20-30% than in the disordered one (the values from that previous study were interpolated to the same copper content and are represented in Figure 2d as the red hatched area). This implies that the activity of Pt-alloys is not only a function of alloy average composition, but rather a consequence of a more complex interplay of compositional 2f, 3c, 7c, and structural dynamics taking place during dealloying 7d . In order to gain atomic-level insight into this dynamics, extensive continuum kinetic Monte Carlo (KMC) model simulations in conjunction with Extended X-ray Absorption Fine Structure (EXAFS) measurements were performed. The goal was to collect quantitative and qualitative information about the development of local structure in both alloys (ordered and disordered) during the dealloying process. In KMC simulation, which was based on the well4, 13 established principles of Erlebacher´s works , the appropriate green mash was initialized with atoms arranged either in a disordered Fm3̄̄m crystal structure or a core-shell
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disordered/ordered (Fm3̄̄m / Pm3̄̄m) crystal structure (see Figure 1). These structures were created based on HAADF/STEM observation of various shell-ordered and 7d, 11c 13 disordered Cu-Pt alloys . As in Erlebacher’s model, the driving equations describing the degradation mechanism of bimetallic alloy were site coordination-dependent dissolution of less noble metal and site coordinationdependent surface diffusion of Pt and Cu atoms (for more information about the model see Supporting info). The prediction ability of the KMC model was tested by directly comparing the simulation results to the measurements of online coupling of electrochemical cell to the ICP-MS at the constant potential of 0.9 V (simulating the open circuit 2e voltage in acid leaching experiment ). This way, copper dissolution was very precisely monitored for the first 950 s (Figure 2c) where the main difference in the dealloying occurs. This initial dissolution response can be divided into two different regions. In region A the superficial Cu atoms are stripped away into solution which leads to a delayed transport of dissolved Cu with respect to simulated prediction (where transport phenomena to the ICP-MS is not taken in consideration). Here both samples evolve a similar rough surface since dissolution slopes (rates) are similar. After ~400 s the first differences in samples start to appear (region B in the Figure 2c); these are seen in both experiment (zig-zag curves) and in model prediction (solid curves). For the case of disordered sample (grey curve) the dissolution rate is increased due to easier removal of Cu atoms from the interior of nanoparticles (i.e. evolution of pores). Specifically, the removal of Cu is facilitated due to the presence of preexisting copper percolation clusters and inability of Pt atoms 4, 13 . Examples of transitional to passivate the surface structures from region A to B are visualized in Figure 3a where 3D KMC simulations were stopped at the same time (a movie is presented in Supp. Info.). Consistently with previous reports by Erlebacher et al. for disordered 13 structure , fluctuation in composition may lead to local enrichment of the less noble metal resulting in creation of pits. This way, disordered particles evolve a hilly surface with a higher curvature than the ordered analogues where local enrichment is initially absent. This makes the disordered sample more susceptible for getting hills undercut which, in turn, leads to creation of pores. In contrast, created pits on ordered particles are not deep enough to have any effect on bulk Cu within given timeframe, as indicated by unchanged slope between the transition region A and B (in Figure 2b and visualized in Figure 3a). Furthermore, because Pt atoms of the ordered structure collapse on one another smoother transition Pt surface morphology (“skin-like”) is formed. Compared to the disordered sample, which has Pt atoms that are less mobile (see Supporting video), ordered sample develops porosity quicker and as we will show in the next section also higher average pore volume (bigger pores can be seen in Figure 3b). This is consistent with lower electrochemical surface area (ESA) of ordered sample at all stages of dealloying (see Supp. Info. Table S2). Furthermore, one could relate the morphological phenomena described above to the well-established fact that skin-type Pt-based catalysts exhibit enhanced activities compared to the skeleton type (i.e. smoother surfaces are more active) first 14 shown by Stamenkovic et. al. and afterwards confirmed in 2f, 2g, 15 other important studies. Such a relation would be particularly interesting, since it could provide a reasonable
explanation why ordered catalysts exhibit a higher ORR activity even after prolonged time despite the relatively small difference in dissolved copper (Figure 2d). In addition, due to the slight difference in dealloying of the two types of samples, the Pt-enriched surface has a different under-layer atomic structure. This additionally alters the Pt activity and is discussed in more detail in continuation.
Figure 3. Disordered and ordered particles after acidic treatment. a) Simulated ordered particles (left) at the tipping point of pore creation and disordered particle (right) with developed porosity, taken at the same time. B) STEM image and simulation of 12h acid treated particles (Movie can be seen in Supp. Info.). The theoretical predictions discussed above on the basis of KMC simulations were scrutinized with HAADF/STEM and detailed EXAFS studies of 12h acid treated and untreated samples. Microscopy analysis of samples’ morphology after acidic treatment showed a good agreement with the KMC simulated structures (Figure 3b). A closer inspection has shown that indeed the average ordered particle possesses bigger pores and thus a lower number of pores (effectively seen as a lower porosity), consistent with KMC prediction and with lower ESA values. Cu K-edge and Pt L3-edge in EXAFS analysis on both samples before and after acidic treatment (Supp. Info. S3 and S4) are shown in Table 1 and extended Table S3 in Supp. Info. As anticipated, in the beginning the ordered sample contained less Pt-Pt than the disordered alloy (0.6 < 1.7) and more Pt-Cu neighbors (11.5 > 9.7) in the first coordination shell. After dealloying in 0.1 M HClO4 for 12 h the number of Pt neighbors around Pt atoms in the ordered sample significantly increased (4.9) whereas the number of Pt-Cu coordination dropped (2.8), indicating agglomeration of Pt on the surface of pores with Cu atoms captured underneath. However, the overall number of platinum neighbors decreased, suggesting a creation of nanosized pores in accordance with TEM analysis. Further information about EXAFS data can be found in Supporting Information.
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EXAFS results are consistent with predictions of KMC simulations (Figure 3 and Table 1). Probably the most important outcome of present combined KMC-EXAFS study, however, is that in the case of ordered particles Pt atoms are surrounded with about 15-30% more Cu atoms - at all times studied - making the alloy more prone to ligand and/or 3 strain effect. This offers a reasonable, and even a quantitative explanation why the ordered catalyst is considerably more active through all of the dealloying process (Figure 2d). Table 1. Average coordination numbers of nearest neighbors around Pt atoms obtained by Cu and Pt K-edge EXAFS analysis and EXAFS by theoretical simulations of ordered and disordered samples before and after 12 h acidic treatment (dealloying). Pt EXAFS Simulation neighbors (N) (N) Cu 11.5(5) 10.5 Ordered Pt 0.6(4) 1.2 Cu 9.7(4) 9.2 Disordered Pt 1.7(6) 2.4 Cu 2.8(1) 2.6 Ordereddealloyed Pt 4.9(6) 4.8 Cu 2.0(4) 1.7 Disordereddealloyed Pt 4.6(6) 5.1 In summary, the positive effect of structural ordering on the performance of Pt nanoalloy electrocatalysts was explained on the atomic level. Although the rates of copper removal from ordered and disordered Pt-Cu binary alloy were found comparable, significant differences in morphological and structural development of alloy nanoparticles were observed. HAADF/STEM and ESA measurements together with 3D Kinetic Monte Carlo simulations revealed formation of a smoother and “skin-like” surface on the ordered sample. Most importantly, both the EXAFS experiments and KMC simulations showed that in the ordered sample the copper coordination number around the Pt atoms was consistently higher by about 15-30%. The identified morphological and structural differences provide a reasonable explanation for the observed 23-37% higher ORR activities of the ordered sample if compared to the disordered one.
ASSOCIATED CONTENT Supporting Information “This material is available free of charge via the Internet at http://pubs.acs.org.” Sample preparation, in-situ and ex-situ degradation analysis, activity measurements, EXAFS, Kinetic Monte Carlo (pdf)
AUTHOR INFORMATION Corresponding Author *
[email protected] Notes The authors declare no competing financial interests.
ACKNOWLEDGMENT
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Financial support from Slovenian Research Agency is gratefully acknowledged (Research program). Part of the work was carried out within the NATO Science for Peace Project EAP.SFPP 984925 – “DURAPEM”.
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