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Size-selective Kinetics of Nanostructured Pt/ GC Model Electrocatalysts for CO Stripping Dan Zhang, Zhong Shao, Wei Yan, Aijun Li, and Spiros S. Skourtis J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.5b04423 • Publication Date (Web): 22 Feb 2016 Downloaded from http://pubs.acs.org on February 23, 2016

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The Journal of Physical Chemistry

Size-Selective Kinetics of Nanostructured Pt/GC Model Electrocatalysts for CO Stripping Dan Zhang1, Zhong Shao1, Wei Yan2, Aijun Li3*, Spiros S. Skourtis4* 1． Shanghai Key Laboratory of Mechanics in Energy Engineering and Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai 200444, P. R. China 2． Nano Science and Technology Research Center, Shanghai University, Shanghai 200444, P. R. China 3． Research Center for Composite Materials, Shanghai University, Shanghai 200444, P. R. China 4． Department of Physics, University of Cyprus, Nicosia 1678, Cyprus

Abstract We studied using dynamic Monte Carlo (DMC) models the size-selective kinetic characteristics of CO monolayer oxidation (CO stripping) on multi-scale nanostructured Pt/GC model electrodes comprised of nanodisks with

diameters of

120 nm and nanoparticles with diameters of 6 nm. We used the DMC models to simulate pre-adsorbed CO (COad) oxidation peaks and voltammetry responses for the two types of nanostructures and compared to experiments. Our DMC simulations showed that the different CO stripping voltammetry peaks for the nanodisks and the nanoparticles observed in experiments result from different surface motilities of the COad molecules on the catalyst surfaces and from different initial COad configurations.

Key words: Size-Selective Kinetics; CO Monolayer Oxidation; Dynamic Monte Carlo Model; Intrinsic Reaction Kinetics; CO Surface Diffusion.

1. Introduction In electrochemistry, the motivation for studying idealized model electrodes is to qualitatively or semi-quantitatively describe the electrochemical and electrocatalytic processes on complex realistic electrode surfaces1-4. Studies on idealized model electrodes with well-defined structures under idealized conditions can isolate factors important for the electrochemical reactions in real systems, such as electrode morphology, mass transport and reaction conditions5-7. A fundamental understanding 1

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of the electrochemical process, in turn, helps to improve and to optimize the design of practical and realistic electrode systems. In the past decade, supported nanostructured Pt/GC (Platinum/Glass Carbon) model electrodes8,9, i.e. Pt nanostructures deposited on the surface of a planar glassy carbon support, have attracted increasing attention as such electrodes enable the control of the sizes and amounts of the deposited Pt nanostructures. At the same time, because the Pt nanostructures are polycrystalline, the studies of the electrocatalytic properties carried out on nanostructured Pt/GC model electrodes, (such as electrocatalytic oxygen reduction, and electrocatalytic methanol and CO oxidations), are more realistic than similar studies carried out on metal single crystals10-13. Behm and co-workers summarized various nano-manufacturing preparation methods of Pt/GC model catalysts previously published elsewhere14-16 and were the first to use supported nanostructured Pt/GC model electrodes to understand mass transfer mechanisms17-19. In their work, the nanostructured Pt/GC model catalysts were prepared by colloidal lithography and exhibited two clear CO monolayer oxidation (CO stripping) peaks which were centered at ca. 0.70V and 0.75 V (vs.RHE), respectively. This double-peak feature was initially explained as the adsorbed CO (COad) oxidations at the different facets of low index planes of the Pt nanostructure. However, further experimental results showed that apart from the dominant Pt nanodisks with a diameter of 120 nm on the electrode, there are smaller Pt nanoparticles with a diameter of c.a. 4~6 nm, and the second CO stripping peak at 0.75V results from these by-product Pt nanoparticles 20, 21. The oxidation on the large nanodisks starts at a lower electrode potential, compared to the oxidation on small nanoparticles. Obviously, the feature of the double CO stripping peaks on the nanostructured Pt/GC highlights distinct size-selective electrocatalytic kinetics of the nanostructured Pt/GC model catalysts. Extensive work has been carried out to study the above-mentioned size effects 22-25 in Pt nanostructures. These effects are normally attributed to morphological changes of the particles, e.g., changes in the relative concentrations of surface atoms of different coordination numbers, or in the ratio of the preferable crystal planes on the 2


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crystalline surface. Based on an analytic solution with a number of approximations, Maillard et al. found that the sluggish oxidation of CO on 2~4 nm nanoparticles might be attributed to the limited surface mobility of COad instead of morphological changes26,

27

. In his theoretical analysis, a simplified model represented by a

macroscopic one dimensional diffusion equation was proposed to obtain an analytic solution, the important assumption of which was that the active sites are located only on the circumference of a circular domain. Koper et al. first used the dynamic Monte Carlo (DMC) technique of statistical mechanics to accurately simulate the CO oxidation on Pt (100) electrode. DMC offers the possibility to deal with the surface migration of COad with fewer approximations28,29. Saravanan et al30,31 used DMC simulations to predict that increasing the surface diffusion coefficient is beneficial for obtaining better electrocatalytic activity and that

high surface coverage can result in

negative voltammetry peak shifts. Wang and Reuter also applied kinetic Monte Carlo models to simulate COad electro-oxidation by considering the diffusivity of COad32,33. Hernández-Ortiz etal34 proposed a lattice-gas model including effective lateral interactions for CO electro-oxidation on metallic surfaces. In the present work we use a DMC model with mutual interaction energy among reactants to investigate further the effects of COad surface mobility on

CO

monolayer oxidation and to explore an additional parameter that is likely to influence the voltametric response: the

initial configuration of COad which is expected to be

different among nanodisks and nanoparticles. Our aim is to obtain further insight on the effects of

nanostructure

size on electrocatalytic activity.

2. Experimental All details of the catalyst preparation and characterization have been reported by Behm and coworkers21 and Table 1 shows the parameters and properties of the Pt nanostructures of the catalytic electrode in Ref. 21.

Table 1: The geometric and physical surface parameters of Pt nanodisks and Pt nanoparticles assuming Pt nanoparticles to be a disk21 3



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Sample

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Pt

Pt

Density

Geometric

Diameter

Fraction of

Nano-

surface

( 1 µm2 )

Pt surface

(nm)

the

structure

coverage

area(cm2)

geometric Pt surface area

(%)

(%) CL-20

CL-40

Nanodisks

22

16

0.1

134 ± 19

69

Nanoparticles

4

2760

0.045

4.3 ± 3.2

31

Nanodisks

40

26

0.24

140 ± 24

84

Nanoparticles

3

2510

0.034

3.9 ± 2.6

16

Fig.1 The experimental current voltammograms of the CL-20 sample21.

In the above-mentioned experiment, before the electrochemical oxidation reaction, a CO saturated solution was maintained at low positive potential 0.06 V for 10 min. Subsequently, the cell was rinsed with CO-free base electrolyte for 20 min, and then the adsorbed CO was oxidized in an anodic potential scan from 0.06V to 1.16V at a sweep rate 10 mV/s (solid black line in Fig.1). Following this scan, a base CV (BCV) 4


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was also recorded (dashed lines in Fig.1), and all experiments were performed at room temperature. Fig.1 shows the experimental voltammogram of the CL-20 sample, in which the voltammogram curves of the first positive and negative scans are black solid and blue dash lines, and the red dash line represents the voltammogram of the second positive scan21. It is clear that the experimental voltammogram shows double “irreversible” oxidation waves in the first positive scan. By changing the loading of the Pt nanodisks on the electrode, researchers have observed a shift of the COad oxidation peak to higher potentials as the coverage of the Pt nanodisks decreases21. It has, therefore, been concluded experimentally that the low potential CO stripping peak corresponds to COad oxidation on the Pt nanodisks, while the high-potential peak results from COad oxidation on the Pt nanoparticles, which implies that the reactive energy barrier of Pt nanodisks is lower than that of Pt nanoparticles.

3. Methodology 3.1 Elementary surface electrochemical reaction mechanism The reaction mechanism of CO electrocatalytic oxidation on Pt surfaces has been studied extensively. For the electrochemical CO stripping, COad is already pre-adsorbed before the reaction starts and the elementary reaction scheme adheres to the Langmuir-Hinshelwood mechanism H 2O + ∗

k1 k −1

OH ad + H + + e −

0 CO ad +OH ad  k → CO 2 + H + + e − + 2 ∗

(1) (2)

where k1 and k −1 are the reaction rate constants of OH adsorption and desorption reactions respectively, and k0 is the reaction rate constant of the CO oxidation reaction. In step (1), the formation of a surface species OHad results in the production of one electron with a decrease of free surface sites denoted by “*” . In step (2), OHad reacts with an adjacent COad to produce another electron, together with the restoration of two surface free sites. 5



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The reaction rate constants of reactions (1-2) obey the Butler-Volmer law of electrochemical reactions and are given by:

k1 = k10exp α eϕ ( t ) ( k BT ) 

(3)

k−1 = k−01exp  −(1 − α )eϕ ( t ) ( k BT ) 

(4)

k0 = k00 exp α eϕ ( t ) ( kBT )  exp(− ∆f θCO N AkBT )

(5)

where subscripts “1”, “-1”, and “0” denote OH adsorption, OH desorption, and CO oxidation reactions, respectively. Reaction rate constants k10 , k−01 , k00 are independent of the reactant lateral interactions and have the dimension of reciprocal seconds. α is the electron transfer coefficient which depends on the intrinsic properties of the electrode material, e the charge of an electron, T the temperature, kB the Boltzmann constant, and N A the Avogadro constant. θ CO is the coverage of the surface species COad on the electrode surface. In Eq.5, ∆f =f ( ≠ ) − f ( R ) , where f ( ≠ ) and f ( R ) are the mutual (lateral) interaction energies of the activated

complex and of the reactants, respectively13 (in J/mol units). If the electrode is held initially at a potential of ϕ 0 and the potential is then swept linearly with a rate of υ , the measured potential of the half-cell (vs. RHE) ϕ at any time t is given by

ϕ ( t ) = ϕ0 + υ t

(6)

For CO oxidation, the desorption of COad will offer more active sites for OHad. Therefore, it is necessary to consider the desorption/re-adsorption reaction: CO + ∗

k2

CO ad

k −2

(7)

where k2 and k−2 are the reaction rate constants of COad re-adsorption and desorption, respectively. These rate constants may depend on the electrode potential, but this dependence is expected to be weak compared to that of the other reaction steps because COad diffusion does not involve charge transfer. Therefore in this work k −2 6


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is regarded as a constant. At the same time k2 can be ignored because the CO species in bulk solution will be taken away quickly in the flow cell. To include in the CO stripping the effect of CO diffusion on the electrode surface, we must consider the process of CO exchanging places with an empty neighboring site (or with a adsorbed water molecule), i.e., kd COad + ∗  →∗ + COad .

(8)

This ‘reaction’ has a rate constant of kd (s-1), reflecting a surface diffusion coefficient D (m2·s-1). In our simulations the parameter kd was varied in order to assess the influence of COad surface diffusion on the electrochemical response. Diffusion of OHad was not considered since the excess of water is always satisfied in the present work.

3.2 Dynamic Monte Carlo simulations Since details of the DMC method have been published elsewhere35, 36, only the main principles will be given in the present work. In the DMC method, the evolution of the system over time is described by the chemical master equation, which is derived from first principles 31. dPγ dt

= ∑ Wγ ′→γ Pγ ′ − Wγ →γ ′ Pγ 

(9)

γ′

The master equation describes how the reacting species probabilities Pγ ′ change with time due to the surface reactions with rates Wγ →γ ′ . To simplify the calculations, it was assumed that the CO species only adsorb on a single type of adsorption site, and that the H2O species occupy the empty sites quickly. We used a variable time step dynamic Monte Carlo (VTSMC) to perform the CV simulations. The simulation was started by defining the initial configuration of CO on the Pt surface. In a VTSMC algorithm, a process list is prepared that contains all possible reactions for the system at a particular configuration . Then a time step ∆t ( γ ) is chosen such that exactly one event occurs during the time step. The chosen 7



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event occurs with a probability proportional to its rate coefficient and is given by: ∆t (γ ) = − ln(1 − x) ktot (γ )

(10)

where x ∈ [ 0,1) is a uniform random number and k tot is the total rate of all possible processes available at time t.28 Once ∆t is picked and the chosen event is performed, the process list is updated for choosing an event in the next VTSMC step. For the voltammetry simulations, C++ programs were written to run a VTSMC that is complete when the potential scan reaches a final preset value. The current transient, during a VTSMC run, is determined by calculating the net rate of electrons flowing into the electrode per second because of reactions (1) and (2): + −  δ nOH − δ nOH e δn e  δ nCO i (t ) = =  + . A δt A  δt δt  

(11)

In the equation above

A=

n2 ρ AN A

(12)

represents the equivalent area of the simulation lattice, which depends on the density + − of active sites . In Eq.11, nOH is the number of adsorbing OH groups, and nOH is

the number of desorbing OH groups. For voltammetry experiments, δ E δ t is the scan rate υ such that Eq. 11 may be written as: i (t ) =

+ − δ nOH − δ nOH e δ n υ e  δ nCO  = + A δt A  δE δE 

  

(13)

In our studies the simulations were started using different initial configurations of COad on the Pt surface. For nanodisks the initial COad configuration was chosen to be random (homogeneous) as expected on physical grounds. For nanoparticles we explored different agglomeration configurations of varying randomness, ranging from 8


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homogeneous configurations for nanodisks to agglomeration (or domain) distributions for nanoparticles. The simulations were performed on a square lattice of binding sites (100x100 or 200x200) with periodic boundary conditions for nanodisks and non-periodic boundary conditions for nanoparticles. The temperature was fixed at 300K. A larger lattice was also tested, and there was no difference in the results compared to the smaller lattice (except for a lower noise level).

4. Results and discussion 4.1 Estimation of the coverage and active site properties of the electrodes used in experiment For every DMC calculation the density of active sites ρA determines the total amount of the charge resulting from COad oxidation (eqs. 11-12). Since we fit our DMC simulations to particular voltammetry experiments it is important to estimate the average density of active sites that are representative of the electrodes used in these experiments. Given that the electrodes are mostly comprised of nanodisks (Table 1) which are expected to have homogeneous COad configurations, our approach to performing the above-mentioned estimation is to use the following formula for calculating ρA :

QCOad = 2 F ⋅ S ⋅ ρ A .

(14)

QCOad is the charge resulting from COad oxidation and S is the geometric surface area of Pt nanostructures, which can be estimated by the morphology and density of the nanostructured Pt/GC model electrode. For CO stripping QCOad is related to the loading of the Pt nanostructure and it can be deduced from the area of the voltammetry peak by comparing the charges of the COad monolayer (the area of the peak) for the Pt nanodisk versus the nanoparticle. For the CL-20 sample, an initial CO coverage of 0.814 was calculated from the published experimental data.

4.2 Intrinsic oxidation reaction rate constants Several VTSMC runs were averaged to obtain a voltammogram. Fig.2 shows the numerical simulation results for CO stripping performed by fixing the CO initial 9



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0 coverage to the values θ CO = 0.814 at the 10mVs-1. The reaction rate constants were

obtained by fitting the simulations to the experiments and they are listed in Table 2.

Table 2: relevant model parameters obtained by fitting the DMC with experimental data Names

Units

configuration Boundary Condition

Nano Disks

Nano Particles

Names

Units

Nano Disks

Nano Particles

random

agglomeration

k−01

1/s

1E4

1E4

periodic

non-periodic

k00

1/s

2

2

α

/

0.5

0.5

k-2

1/s

1E-6

1E-6

0 θ CO

/

0.814

0.814

kd

1/s

100

10

ρA

mol/m2

2.65E-5

7.43E-5

∆f

J/mol

0.019θCO

0.019θCO

+ 0.004

+ 0.004

k10

1/s

7.3E-3

7.3E-3

Since the experimental work has confirmed that the double peaks of the faradaic current result from the nanodisks and the nanoparticles, a reasonable assumption was made in the present work that

the two Pt nanostructures are distributed on the

electrode surface in an uncorrelated way (as there is no information to suggest otherwise). Further, it was assumed that the pre-adsorbed CO on each nanodisk or nanoparticle cannot

move to other nanostructures substantially and sufficiently

rapidly to affect the kinetics. With these assumptions, either the nanodisk or the nanoparticle can be treated as an independent system of which the current density can be calculated from DMC simulations. Then the total currents can be calculated by using the weighted summation of the geometric surface areas of the Pt nanostructures shown in Table 1. It was found that the double peaks of the experimental voltammetry currents can be well reproduced as shown in Fig. 2 with the same set of reaction rate parameters for the nanodisks and the nanoparticles. Because the COad+OHad oxidation reaction is much faster than the OH adsorption reaction, the electrochemical response 10


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belongs to the fast set of rate constants according to Koper’s theory28.

Fig.2 Predicted current voltammograms for the CL-20 sample by the DMC model in which the feature of double peaks can be reproduced by using the parameters listed in Table 2. (a)

(b)

Fig.3(a) Snapshots of the DMC model which represents a Pt nanodisk during the voltammograms. (b) Snapshots of the DMC model which represents a Pt nanoparticle during the voltammograms. Green: OHad; Red: COad; Black: empty site.

In the DMC model, these two kinds of Pt nanostructures differ only in the initial configuration of COad used in the simulation. An initial random configuration was defined on the Pt nanodisk as it was supposed to be an expanded surface as shown in 11



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Fig.3(a), while an initial agglomeration configuration was defined on the Pt nanoparticle as it was supposed to be a restricted surface as shown in Fig.3(b) . Fig.3 (a) and 3(b) show the evolutions of the configurations of COad. It was confirmed that the initial COad configuration on the electrode surface has a greater influence on the voltammogram than the COad diffusion rate does. The initial distribution of COad restricts the reaction front and the propagation of the reaction front only occurs at the edges of COad agglomeration. Fig.4 shows the effect of k d on the voltammogram by fixing other kinetic parameters and varying k d from 10 to 1E4. For the nanodisk, there is a small effect on the voltammograms, while for the nanoparticles the voltammetry peak slightly shifts to the left and gets narrower with increasing kd . This can be understood as follows. Due to the surface diffusion, COad can jump to a free site or can replace a site occupied by water, thus improving the degree of mixing between OHad and COad. However, for the homogeneous configuration in which the degree of mixing is already high, COad surface diffusion has almost no effect on COad oxidation.

Fig.4 Effect of CO diffusion rate on CO stripping voltammetry for Pt nanoparticle electrode

Therefore, COad surface diffusion only plays an important role for some 12


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agglomeration configurations, in which COad islands can be found on the electrode surface. The simulation results illustrate that rapid COad diffusion washes out the effects of COad agglomeration, and it also results in a higher reaction probability for CO oxidation. In this case, the voltammogram peak becomes wider and slightly shifts to more negative potentials. As shown above, the COad surface diffusion plays different roles for homogeneous and agglomeration configurations of COad on the electrode surface. To gain a deeper understanding of initial COad configuration effects, a set of simulations were performed in which COad molecules were partially dispersed on some specific domains at the initial stage (t 0), as shown in Fig.5(a) (φ=0.06 V configurations). The initial coverage of CO and the active site density are the same in all examples of Fig.5(a) ( denotes the number of domains). In our simulations water molecules initially occupy the empty sites among the domains. We observed that when the onset potential arrived the COad and OHad began to react on the boundaries of the domains. As a consequence, these COad islands gradually narrowed with the increasing potential.

(b)

Fig.5 (a) The changes of COad configurations at the initial (φ=0.06 V) and the final (φp) peak potentials as a function of the different number of domains ( ). (b) Comparison of the stripping voltammograms with different partial dispersion of COad on the Pt nanoparticle surface by using DMC models without the interaction energy.

The effect is apparent in the configurations attained at the peak potentials φp for the 13



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different cases shown in Fig.5(a). Fig.5(b) shows a clear relationship between the peak potential and the initial configuration of COad. For all cases considered, the onset potentials are very close, while increasing of the domain number results in the peak potential shifting toward negative, which means that more COad becomes available to react. When 64, the CO stripping voltammograms approach the behavior of a homogeneous surface voltammograms. In Fig.6, we also compare the results of CO stripping for two different DMC models with and without the mutual interaction energy. For the model without the mutual interaction energy, a pre-wave current is observed followed by a sharp peak around 0.55 V. In studies of CO oxidation on Pt (111)

37

this current was interpreted

as being due to the attack by solution-phase OH- on the adsorbed CO based to an Eley-Rideal mechanism. In the numerical simulations of the DMC model with the interaction energy, we find that the pre-wave current vanishes and the peak shifts to negative potentials. This effect is attributed to a decrease of the COad oxidation rate due to the inter-molecular repulsions which arise from the nearest neighbor interactions. As a result, the voltammogram peak becomes sharp and bimodal reflecting the different peak potential values for nanodisks and nanoparticles.

Fig.6 Comparison of the simulation results by using DMC models with and without the mutual interaction energy. For the model without the mutual interaction energy, a pre-wave current is 14


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observed followed by a sharp peak around 0.55 V.

5. Conclusions We performed DMC modeling of electrochemical CO oxidation using a Langmuir-Hinshelwood mechanism that included effective interactions between adsorbed CO molecules and surface diffusion of COad. Our DMC simulations reproduced well the experimentally-observed double-peak characteristics of CO stripping voltammograms on multi-scale nanostructured Pt/GC electrodes comprised of nanodisks and nanoparticles. The reaction rate constants of the elementary steps of the Langmuir-Hinshelwood mechanism were determined by fitting experimental data to the simulations. Our results indicate that CO oxidation on Pt nanodisks and nanoparticles has identical intrinsic charge transfer kinetic parameters. The double-peak feature of the voltammograms is a consequence of different surface diffusion rates of COad molecules and different configurations of COad for these two kinds of nanostructures. The simulations clearly demonstrate that the surface diffusion of COad depends on the size of the Pt nanoparticles but also that the effect of surface diffusion of COad on the CO oxidation depends on the initial configuration of COad molecules, which tends to be homogeneous on the Pt nanodisk, while be heterogeneous on the Pt nanoparticle due to a limited space. Therefore, it can be concluded that homogeneous COad configurations consistent with fast COad diffusion rates give the correct physical picture for Pt nanostructured catalysts of 100nm diameter or more. In contrast, for Pt nanostructured catalysts of a few nanometers diameter, both the effects of slower COad surface diffusion and of nonhomogeneous COad configurations must be taken into account to understand the CO oxidation kinetics. In our future work, the effects of Pt surface structure on the adsorption configuration of COad will be studied, and the mechanism underlying the changes of CO initial configuration on nanoparticles will be explored further.

Acknowledgment 15



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The authors acknowledge the support of the National Natural Science Foundation of China (11202124); Project “Molecular Scale Electrochemistry and Nontraditional Electrochemical materials Science” (ELECTRONANOMAT，grant agreement number: PIRSES-GA-2012-318990) granted by the European framework program-Marie Curie Actions (People International Research Staff Exchange Scheme). S.S. Skourtis acknowledges the hospitality of the Freiburg Institute of Advanced Studies during the writing of this manuscript.

Author information Corresponding Author *E-mail: [email protected], [email protected],

tel:(+86 21)56331451 tel: (+357 22) 892831

Notes The authors declare no competing financial interests.

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GC Model

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