Selective acetylene hydrogenation over single-atom alloy

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Selective acetylene hydrogenation over singleatom alloy nanoparticles by kinetic Monte Carlo Mikkel Jørgensen, and Henrik Grönbeck J. Am. Chem. Soc., Just Accepted Manuscript • DOI: 10.1021/jacs.9b02132 • Publication Date (Web): 07 May 2019 Downloaded from http://pubs.acs.org on May 7, 2019

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Journal of the American Chemical Society

Selective acetylene hydrogenation over single-atom alloy nanoparticles by kinetic Monte Carlo Mikkel Jørgensen∗ and Henrik Grönbeck∗ Department of Physics and Competence Centre for Catalysis, Chalmers University of Technology, 412 96 Göteborg, Sweden E-mail: [email protected]; [email protected]

Abstract Single-atom alloys, which are prepared by embedding isolated metal sites in host metals, are promising systems for improved catalyst selectivity. For technical applications, catalysts based on nanoparticles are preferred, thanks to a large surface area. Herein, we investigate acetylene to ethylene hydrogenation using kinetic Monte Carlo simulations based on density functional theory, and compare the performance of Pd/Cu nanoparticles with Pd(111) and Pd/Cu(111). We find that embedding Pd in Cu systems strongly enhances the selectivity, and that the reaction mechanism is fundamentally different for nanoparticles and extended surfaces. The reaction mechanism on nanoparticles is complex and involves elementary steps that proceed preferentially over different sites. Edge and corner sites on nanoparticles are predicted to lower the selectivity, and we infer that a rational design strategy in selective acetylene hydrogenation is to maximize the number of (111) sites in relation to edge sites for Pd/Cu nanoparticles.

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Keywords: Nanoparticle catalysis, Microkinetic modeling, Kinetic Monte Carlo, Density Functional Theory, Acetylene hydrogenation, Single atom alloy.

Introduction Precious metals play an essential role in heterogeneous catalysis, where nanoparticles are typically applied to achieve a large surface to volume ratio. A catalyst should preferably be durable, have low cost, high turnover frequency, and high selectivity. Selectivity is a fairly complex property that can be accomplished by modifying the relative energy barriers or by imposing geometric constraints. 1 Metal alloying is one way to reach high selectivity, which has been studied extensively for various applications. 2–8 Hydrogenation reactions are a class of particularly important reactions, where hydrogenation of acetylene to ethylene is an important example with numerous uses, for example in the production of polymers. In producing polymer-grade ethylene, a very high selectivity is required as the ethane content in the product should be less than 5 ppm. 9 Acetylene hydrogenation can, furthermore, be considered a model reaction for more complex hydrogenation reactions. Pd-based systems are often used as catalysts for acetylene hydrogenation. 9 A general main reaction pathway is the Horiuti-Polanyi mechanism, 10 where C2 H2 adsorbs and is sequentially hydrogenated. The challenge is to produce C2 H4 without continued hydrogenation to C2 H6 . Experimentally, acetylene and ethylene hydrogenation have been investigated 11–14 on Pd(111) by temperature programmed investigations and infrared spectroscopy. At relevant temperatures, the identified species were found to be hydrogen, acetylene, vinyl-groups, and oligomers. Thus, oligomerization and decomposition of the hydrocarbons into elemental carbon and hydrogen are likely to compete with the Horiuti-Polanyi mechanism. 11,15,16 These experimental observations have been supported by first-principles calculations 17–21 and microkinetic simulations. 18–20 While the acetylene conversion is high on pure Pd systems, the selectivity is generally

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insufficient. 15,22,23 Selectivity can be improved by embedding single Pd sites into a host metal, which are systems known as Single-Atom Alloys (SAAs). 6,22 SAA catalysts have the potential to selectively affect particular elementary reaction steps and break the linear scaling relations, inherent to pure metallic systems. 6,24 Experimentally, SAAs systems of Pd embedded in Ag and Cu have been demonstrated to yield an improved selectivity for hydrogenation reactions, as compared to pure Pd. 22,23,25 As ethylene should desorb before further hydrogenation, the selectivity of bimetallic SAAs correlates with the difference between the ethylene hydrogenation barrier and the binding strength of ethylene to the surface. 26–28 The Pd concentration should be kept low to avoid significant green oil formation, which act as poison. 16,29 The reaction kinetics of selective acetylene hydrogenation has been investigated over pristine Pd(111) and Pd/Cu(111) surfaces. 18 However, technical applications are preferably based on high surface area nanoparticles. The lack of knowledge calls for explicit investigations of SAAs where Pd is embedded in Cu nanoparticles. This is a crucial extension, as nanoparticles can behave fundamentally different than extended surfaces, even for simple reactions such as CO oxidation. 30,31 Here, we investigate selective hydrogenation of acetylene-ethylene mixtures over Pd/Cu SAA nanoparticles. The results are compared to simulations for Pd(111) and Pd/Cu(111). The reaction is studied using Scaling Relations Kinetic Monte Carlo (SRMC) simulations, 32 which reveal the main reaction mechanisms, selectivity, rates, and most abundant species. Studying nanoparticles and extended surfaces in the same theoretical framework, highlights the differences between nanoparticles and extended surfaces. For the extended surfaces, we find that Pd/Cu(111) SAA has a higher selectivity than Pd(111). The improved selectivity mainly arises from the weaker ethylene binding on Cu as compared to Pd. We find that the selectivity is lower for Pd/Cu nanoparticles than over Pd/Cu(111). This is traced to the effect of edges and corners that bind ethylene strongly, preventing ethylene desorption before further hydrogenation. Thus, an efficient and selective catalyst for acetylene-ethylene hydro-

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genation should contain minority-sites that readily dissociate hydrogen, and majority-sites where ethylene is weakly adsorbed. The simulations uncover that the reaction mechanism on extended surfaces and nanoparticles is significantly different. This is explained by the multiple available sites on nanoparticles that enable complex reaction pathways.

Computational Methods The kinetic Monte Carlo (kMC) simulations are performed using our recently developed Scaling Relations Monte Carlo (SRMC) approach. 30,32 In SRMC, the reaction energy landscape is represented using a descriptor for adsorption energies, and Brønsted-Evans-Polanyi (BEP) relations to calculate the energy barriers. This method allows for simulating nanoparticle kinetics without explicitly mapping out the entire reaction energy landscape. Using scaling relations and BEP relations, surfaces and nanoparticles are treated at the same level of theory, and the differences between these systems can be scrutinized.

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The Horiuti-Polanyi mechanism 10 with adsorbate diffusion is used to model the reaction:

C2 H2 (g) + ∗

C2 H∗2

↔

(R1)

H2 (g) + 2∗

↔

2H∗

(R2)

C2 H∗2 + H∗

↔

CHCH∗2 + ∗

(R3)

C2 H∗4 + ∗

(R4)

CHCH∗2 + H∗ C2 H∗4

↔

↔

C2 H4 (g) + ∗

(R5)

C2 H∗4 + H∗

↔

C2 H∗5 + ∗

(R6)

C2 H∗5 + H∗

→

C2 H6 (g) + ∗

(R7)

H∗ + ∗

∗ + H∗

→

C2 H∗2 + ∗

∗ + C2 H∗2

→

CHCH∗2 + ∗

(diffusion)

→

(diffusion)

∗ + CHCH∗2

(diffusion)

(R8) (R9) (R10)

C2 H∗4 + ∗

→

∗ + C2 H∗4

(diffusion)

(R11)

C2 H∗5 + ∗

→

∗ + C2 H∗5

(diffusion)

(R12)

This reaction mechanism is sufficient as verified by initial mean-field microkinetic modeling for Pd(111), which explores an extended reaction mechanism with multiple reaction pathways (see supporting information). At certain reaction conditions, it may be required to extend this reaction mehcanims with additional poisoning species, such as as ethylidene and ethylidyne. 19,20

Density Functional Theory Density Functional Theory calculations are performed in the Vienna Ab-Initio Simulation Package (VASP) 33–36 using the Projector-Augmented Wave (PAW) scheme. 37 The number of explicitly considered valence electrons are: H(1), C(4), Cu(11), Pd(10). The generalized gradient functional PBE, 38 is used to treat exchange and correlation effects, together with a 5



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D3 correction to account for dispersive interactions. 39 This approach yields reasonable lattice constants and adsorption energies. The lattice constants were calculated to be 3.57 ˚ A and 3.90 ˚ A for Cu and Pd, respectively, determined in the bulk fcc unit-cell using a (12 × 12 × 12) k-point grid. We employed a plane-wave cutoff of 450 eV, a (4 × 4 × 1) k-point grid in (3 × 3) calculation-cells , and 12 ˚ A vacuum perpendicular to the slabs. Slabs are modeled by four atomic layers, where the positions of the two bottom layers are fixed to emulate a bulk surface. Structures are optimized using the Atomistic Simulation Environment (ASE) 40 until all forces are below 0.05 eV/˚ A. Vibrational energies are determined in the harmonic approximation with two-point finite differences, and a displacement of 0.01 ˚ A. All the reaction energies in the kinetic simulations are adjusted to account for zero-point motion. Adsorbates and gas-phase molecules are considered in singlet spin-states. Gas-phase molecules are optimized in a (30 ˚ A × 30 ˚ A × 30 ˚ A) cell. Energy barriers are evaluated using climbing image Nudged Elastic Band (NEB) 41 method from the VTST tools, 42 with at least five images. Initial interpolations are performed by the image dependent pair potential method. 43 The transition states are optimized until all forces are below 0.05 eV/˚ A.

Rate constants Reaction rate constants for adsorption are calculated using collision theory, assuming unity sticking coefficients: ads kX,j

pX Asite exp =√ 2πMX kB T

act −EX,j kB T

,

(1)

where X denotes the gas-phase species, j is a site index, p is the pressure, Asite ≈ 10 ˚ A

2

is the area of a site, M is the molecular mass, and E act is the activation energy. Only H2 dissociation is assigned a non-zero activation energy. To ensure thermodynamic consistency, desorption rate constants (k des ) are calculated from the adsorption rate constants (k ads ) and

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the equilibrium constants (K) as:

des kX,j

KX,j = ads , kX,j

KX,j = exp

−∆GX,j kB T

(2)

where ∆G is the Gibbs free energy change of adsorption. Using these expressions for the rate constants, the adsorption-desorption reactions depend on the metal site, the adsorbateadsorbate interactions, and entropy losses upon chemisorption. Hydrogenation reactions and diffusion rate constants are modeled in harmonic transition state theory: 44

ki,j

kB T = exp h

−Gact i,j kB T

(3)

where i denotes the reaction, and Gact i,j is the Gibbs-free energy barrier of activation. The entropy of gas-phase molecules is calculated in the ideal gas approximation. Adsorbates and transition states are treated in the harmonic approximation. Modes lower than 100 cm−1 are set to 100 cm−1 as such modes likely are anharmonic and numerically uncertain. 45 The reaction energy landscapes on the extended surfaces is calculated on the Cu(111), Pd(111), and Pd/Cu(111) surfaces in p(3 × 3) cells. To construct the energy landscape on nanoparticles, the (111) surfaces are augmented by scaling relations in the metal site stability (∆EM ), 46 which has recently been shown to be a good descriptor for the binding energy of various molecules. 46 ∆EM reflects how stable the binding site is in the system as compared to the site in the gas-phase. Thus, ∆EM yields a different free energy landscape depending on particle shape, size, and alloying. Using ∆EM might be necessary as simple geometric descriptors, such as coordination numbers and generalized coordination numbers, 47 cannot directly describe alloying effects. The adsorption energies on the nanoparticles of each species are calculated as ads EX

(∆EM ) = αX ∆EM −

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(111) ∆EM


ads(111)

+ EX

(4)


ads(111)

where, αX is the slope we obtained from the fits, and EX

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is the adsorption energy on

the (111) surface. Thus, the metal-site stability is mapped out by first relaxing the entire nanoparticle, and later removing the sites in question. 46 The fits of the scaling relations are shown in the supporting information. αX for the considered adsorbates are found for Cu sites to be: H (0.25), C2 H2 (0.19), CHCH2 (-0.35), C2 H4 (-0.25), C2 H5 (-0.07). The corresponding values for Pd/Cu sites are: H (0.33), C2 H2 (-0.27), CHCH2 (-0.44), C2 H4 (-0.09), C2 H5 (-0.00). BEP relations are used to scale the energy barriers with respect to our calculations for the (111) surfaces. We use the general BEP relation of Wang et al. 48 for hydrocarbon dehydrogenation. This BEP relation exists for extended surfaces, clusters, and nanoparticles. 48,49 Thus, we calculate the forward reaction energy barrier change relative to the (111) surfaces as

act TS R δEHC = E TS − E R − E(111) − E(111) R = (αHC − 1) E R − E(111)

(5) (6)

where αHC is 0.84, 48 E T S is the transition state energy, and E R is the adsorption energy of the hydrocarbon and hydrogen atom. The barriers of the reverse steps were calculated from ∆G and the forward barriers. Homo and hetero-species adsorbate-adsorbate interactions are treated as a nearest neighbor repulsion, following a bond-order conservation argument. 19 The interactions are calculated in p(4 × 4) Cu(111) unit-cells for each species. The adsorbate-adsorbate interactions are reported in the supporting information. The barriers scale with the adsorbate-adsorbate interactions via the BEP relations.

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Kinetic Monte Carlo The kMC simulations are performed using the MonteCoffee code. 50 The reaction energies are calculated from the most stable binding positions for each adsorbate. However, in the kinetic simulations, one coarse grained site is defined for each surface atom. The coarse grained site entails ontop, bridge, and hollow binding positions. Thus, we use the ∆EM values for the ontop sites on the nanoparticles. This procedure leads to a maximal error in the simulations of 0.18 eV and average error of 0.07 eV, which are well-within the uncertainty of the fitted scaling relations. For the extended (111) surfaces, this error is not present as the actual sites (top, bridge, hollow) are considered. The surface kMC simulations are performed with periodic boundary conditions. The TOFs and selectivity are converged using a simulation cell-size of (18 × 18) on Pd(111) at 340 K (See supporting information). Pd(111) is chosen as the fraction of Pd changes on the Pd/Cu(111) surface with growing simulation cell-size. The Pd/Cu(111) surface is simulated with a Pd/Cu surface site ratio of 9 × 10−3 , close to the surface-concentration in the nanoparticles of 8 × 10−3 . The nanoparticle simulations are realized on a Pd/Cu single atom alloy truncated octahedron, with a diameter of 1.6 nm. The time-step in kMC simulations are governed by the fastest events, 51 which implies that non-equilibrated events are performed rarely. To overcome this, we accelerated the simulation by the generalized temporal acceleration scheme, 52 where the quasi-equilibrated reactions are slowed down dynamically.

Results and discussion Reaction energy landscape The kinetics is based on the reaction free energy landscape. Figure 1 (a) shows the Gibbs free energy at representative reaction conditions for Pd(111), Cu(111), and an SAA of a Pd atom embedded in Cu(111) [Pd/Cu(111)]. Table 1 shows the reaction energy barriers for complete-

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ness. The first step is C2 H2 adsorption, which is barrierless for all surfaces. C2 H2 adsorption is strongly exothermic on Pd(111), whereas C2 H2 binds weakly to Cu(111) and Pd/Cu(111). H2 dissociative adsorption is barrierless on the Pd containing surfaces, whereas this step is highly activated on Cu(111) (0.43 eV). The absence of an H2 dissociation barrier on Pd and a considerable barrier on Cu is consistent with previous experimental observations 22,53 and calculations. 54–56 All hydrogenation barriers on the three surfaces are lower than 0.8 eV. However, a significant difference is that the first hydrogenation step (C2 H∗2 + H∗ → CHCH∗2 ) has the highest activation energy on Pd(111), whereas on Cu(111) and Pd/Cu(111), the second hydrogenation step (CHCH∗2 + H∗ → C2 H∗4 ) has a high activation energy. As mentioned, the selectivity depends on the ethylene hydrogenation barrier relative to the ethylene desorption energy. 26–28 On Cu(111) and Pd/Cu(111), the desorption energy of ethylene is lower than the hydrogenation barrier, which suggests that Cu(111) and Pd/Cu(111) may provide selectivity. In contrast, on Pd(111) the ethylene desorption energy is higher than the hydrogenation barrier. The ethane formation step [C2 H∗5 + H∗ → C2 H6 (g)] may also affect the selectivity. Ethane formation has similar barriers on all three systems, and is fast relative to ethylene hydrogenation on Pd(111) 57 and Pd/Cu(111), whereas it is slow on Cu(111). Thus, the presence of Pd could lower the selectivity by this step. Another factor that can affect selectivity is the ethylene pressure. High ethylene pressures tend to lower the selectivity as the free energy of C2 H4 (g) will be higher than for the adsorbed species. We considered truncated octahedral Pd/Cu nanoparticles of 1.6 nm in diameter, with one Pd site placed in different locations. Figure 1 (b) shows the considered nanoparticle geometry (top), and the calculated ∆EM for the ontop sites on the Pd/Cu nanoparticle, having Pd in the topmost (100) facet. The energy landscape on Pd/Cu nanoparticles is slightly different than for the extended surfaces. One important difference is the presence of low-coordinated sites with different reactivities. This is illustrated by the different values of the ∆EM descriptor in Figure 1 (b). The scaling relation between the adsorption energy and ∆EM are given in the supporting information. For the Cu sites, H and C2 H2 have positive

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Figure 1: (a) Reaction free energy landscape for the Pd sites in Pd(111), Cu sites in Cu(111), and Pd site in Pd/Cu(111), without zero-point energy corrections (The kinetic simulations include zero-point corrections). Triangles show the C2 H4 (g) energy. Temperature: 300 K, pressures: pC2 H2 = 1 mbar, pH2 = 10 mbar, pC2 H4 = 10 mbar. (b) Top: Considered nanoparticle (Cu: brown, Pd: blue). Bottom: Color map of calculated ontop metal site stability ∆EM .

Table 1: Table of reaction energy barriers in eV on (111) surfaces, without zero-point energy corrections. Backward barriers are calculated as E b = E f − ∆Eads . C2 H2 (g) + ∗ ↔ C2 H∗2 H2 (g) + 2∗ ↔ 2H∗ C2 H∗2 + H∗ ↔ CHCH∗2 + ∗ CHCH∗2 + H∗ ↔ C2 H∗4 + ∗ C2 H∗4 ↔ C2 H4 (g) + ∗ C2 H∗4 + H∗ ↔ C2 H∗5 + ∗ C2 H∗5 + H∗ ↔ C2 H6 (g) + 2∗ H∗ diffusion C2 H∗2 diffusion CHCH∗2 diffusion C2 H∗4 diffusion C2 H∗5 diffusion

f ECu(111) 0.43 0.26 0.72 0.70 0.39 0.63 0.14 0.38 0.30 0.17 0.05

b ECu(111) 0.90 1.24 0.97 1.26 0.33 -

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f EPd(111) 0.72 0.67 1.30 0.52 0.50 -


b EPd(111) 2.25 1.32 0.54 0.86 0.25 -

f EPd/Cu(111) 0.44 0.58 0.98 0.55 0.42 -

b EPd/Cu(111) 0.97 0.83 1.01 1.46 0.35 -


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slopes and prefer to bind to high-coordinated sites, such as facets. In contrast, CHCH2 , C2 H4 and C2 H5 have negative slopes and prefer binding to low-coordinated sites at the edges and corners. The site-preference is strongest for CHCH2 and weakest for C2 H5 . In this way, the adsorbates prefer to occupy different sites on the nanoparticle, which can be mediated by adsorbate diffusion. On Pd/Cu sites, the chemisorption energies depend on the placement of the Pd site. Thus, the adsorbate binding depends on whether Pd is placed at a facet, edge, or corner. H, C2 H2 , and CHCH2 are strongly affected by the Pd site-placement, whereas C2 H4 and C2 H5 depend weakly on the Pd location. In the kMC simulations, the reaction energy barriers are scaled with the universal Brønsted-Evans-Polanyi (BEP) relation. 48 Thus, the barriers are functions of the adsorption energies, described by ∆EM . The difference in ∆EM between the inner (111) facet and corner leads to 0.46 eV in difference in the barrier of C2 H∗2 + H∗ → CHCH∗2 . This large difference suggests that the different elementary steps can be steered to proceed over particular sites of the nanoparticle.

Selectivity and turnover frequency Turnover frequency and selectivity is simulated using kMC. 50 Here, selectivity is defined as the turnover frequency of C2 H4 production relative to the total product turnover frequency:

S=

TOFC2 H4 . TOFC2 H4 + TOFC2 H6

(7)

We performed kMC simulations for the extended Pd(111), Pd/Cu(111) SAA surfaces, and the 1.6 nm truncated octahedral Pd/Cu SAA nanoparticle with Pd in one (100) facet, which is the most stable embedding configuration. The Pd/Cu site ratio was 8 × 10−3 for nanoparticles, and 9 × 10−3 for Pd/Cu(111). In most technical applications, acetylene is hydrogenated in an acetylene-ethylene gas mixture, and therefore an ethylene pressure is applied in the simulations. The presence of ethylene leads to a lower selectivity as compared to the

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Figure 2: Turnover frequency and selectivity as a function of temperature for (a) Pd(111), (b) Pd/Cu(111), and (c) Pd/Cu nanoparticle with Pd in the (100) facet. Pressures: pC2 H2 = 1 mbar, pH2 = 10 mbar, pC2 H4 = 10 mbar. Error-bars are one standard deviation of 10 simulations. 13



case of hydrogenating pure acetylene. Figure 2 shows the resulting TOFs and selectivity. For Pd(111), both TOFs are high, up to 105 site−1 s−1 , over the investigated temperature range. The selectivity is between 0.14-0.93, which is high at low temperatures and drops rapidly above 300 K. Pd/Cu(111) has TOFs between 10−1 −104 site−1 s−1 , slightly lower than Pd(111). The selectivity is high, between 0.98-0.99, over the entire investigated temperature range. The drop of the TOFs below 300 K on Pd(111) is due to the higher hydrogenation barriers as compared to Pd/Cu(111). The lower selectivity of Pd(111) is reasonable given the reaction energy landscape in Figure 1. On Pd(111), the free energy barrier for hydrogenating C2 H4 is smaller than the C2 H4 adsorption free energy, which favors further hydrogenation. 26–28 The situation is reversed for Pd/Cu(111) as the reaction energy barrier is higher than the C2 H4 desorption energy, for both Pd and Cu sites. The variation of the selectivity with temperature is related to the slope of the BEP relation that makes the barriers scale weakly with adsorption energies. That is, if increasing the temperature makes the C2 H4 binding strength decrease 1 eV, the C2 H4 hydrogenation barrier decreases only by 0.16 eV. The simulations of extended surfaces form the basis for understanding the kinetics over the nanoparticles, where the reaction energy landscape is less symmetric. On the nanoparticle, the C2 H4 TOF ranges between 4 × 100 − 3 × 104 site−1 s−1 , and the C2 H6 TOF lies within 9 × 100 − 2 × 105 site−1 s−1 . The C2 H6 production rate is high and the selectivity is between 0.12-0.31. The low selectivity is attributed to the high binding strength of C2 H4 on the edge and corner sites (see supporting information). On the edges, the C2 H4 binding strength is increased by 0.22 eV relative to the (111) facet, whereas the barrier for hydrogenation only increases with 0.04 eV. This stabilization makes C2 H4 hydrogenation more likely than desorption, yielding a lower selectivity of the nanoparticle. The C2 H4 TOF arising from the (111) facets are different than the value on Pd/Cu(111). This is despite the fact that the simulated Pd/Cu ratios are similar on the nanoparticle [8 × 10−3 ] and Pd/Cu(111) [9 × 10−3 ]. That a site placed in the nanoparticle has a different activity than when placed

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in Pd/Cu(111) is related to the principle of least resistance. 58 At steady-state, catalytic reactions will follow the lowest energy pathway, 58 which in the presence of different sites can be optimized for each elementary step. Thus, a nanoparticle may be more efficient than a fully symmetric extended surface, which can compromise the selectivity. While there are no direct experiments comparing Pd/Cu(111) to nanoparticles, comparing different measurements support the slightly lower activity of nanoparticles. 22,23,29 Larger Pd/Cu particles of ca. 4 nm were previously shown to be highly selective for phenylacetylene hydrogenation to styrene, even at high conversion. 23 Without ethylene in the reaction mixture, we obtain a selectivity of 84% at 300 K, which is in good agreement with experimental measurements that showed about 90% for phenylacetylene hydrogenation. 23 As we include ethylene in the gas-mixture, we observe a significantly lower selectivity since an ethylene pressure increases ethylene hydrogenation to ethane. We expect that phenylacetylene hydrogenation proceeds with a slightly different reaction mechanism than acetylene hydrogenation and that the hydrogen pressure can play a significant role for the selectivity. 19 The reaction energy landscape on nanoparticles suggests that the placement of Pd sites is important for the selectivity. Figure 3 shows the C2 H4 selectivity as a function of temperature for different Pd site-placements. The Pd site-placement is here indicated by a subscript, where NP(100) means that Pd is placed in the (100) facet of the Cu nanoparticle. For the particular particle shape and size, we calculated the most stable configurations to be (in decreasing order): NP(100) , NP(100)-(111)edge , NP(111) , NP(111)-(111)edge , and NPcorner (see supporting information). For all Pd site-placements, the selectivity ranges between 0.05-0.3. Thus, the site-placement significantly influences the selectivity. The NPcorner has the highest selectivity, and the NP(111) has the lowest selectivity. Thus, there is no obvious relation between the Pd-site stability and selectivity. This suggests that the effect of site-placement depends on the detailed particle geometry and the resulting reaction mechanisms.

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Figure 3: Ethylene selectivity for different site-placements on the Pd/Cu SAA nanoparticle. Energies of Pd site-placement relative to the minimum indicated below particles. Pressures: pC2 H2 = 1 mbar, pH2 = 10 mbar, pC2 H4 = 10 mbar. Error-bars are one standard deviation of 10 simulations.

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Figure 4: Total steady-state net-rates on the Pd and Cu sites of (a) Pd/Cu(111) and (b) NP(111) . Arrow-patterned bars indicate net-negative rates. Temperature 320 K, pressures: 17 pC2 H2 = 1 mbar, pH2 = 10 mbar, pCACS = 10 mbar. 2 H4 Paragon Plus Environment


Reaction Mechanisms The net-rate of each elementary step gives insights into the governing reaction mechanism. Figure 4 (a) shows the net steady-state rates for the elementary reaction steps on Pd/Cu(111), separately for Cu and Pd sites. As H is more mobile than the hydrocarbons, the reported rates for the hydrogenation reactions are attributed to the sites where the hydrocarbons bind. The rate of C2 H2 adsorption is similar on Pd and Cu sites, despite the low Pd concentration. This is reasonable as the binding strength of C2 H2 is 0.53 eV stronger on Pd than Cu sites. H2 dissociation occurs with similar rates on Pd and Cu sites, which is reasonable as the reaction is barrierless on Pd, which has a low concentration. C2 H2 is primarily hydrogenated on Cu sites. However, the ratio of rates between Pd and Cu is roughly two orders of magnitude, which is similar to the Pd/Cu ratio. Next, CHCH2 is hydrogenated to C2 H4 , with similar rates on Pd and Cu, again suggesting that Pd is efficient for this step. Interestingly, C2 H4 adsorption proceeds in the forward direction on the Pd sites, whereas it desorbs from Cu sites. This is related to the low C2 H4 desorption energy on Cu, as compared to Pd. Thus, the Pd/Cu ratio should be kept low to for a high selectivity of Pd/Cu(111). Further hydrogenation of C2 H4 is slow and occurs primarily on the Cu sites. However, C2 H4 desorption is more likely than hydrogenation on the Cu sites, according to the energy landscape. Thus, the low Pd concentration makes this step proceed over Cu. Similarly, C2 H5 hydrogenation proceeds on the Cu sites, albeit with a very low net-rate. On nanoparticles, the elementary step rates differ significantly between the different types of sites, such as edges and facets. Figure 4 (b) shows the net steady-state rates, for the NP(111) particle. We analyze two energetically distinct (111) sites; one neighboring the edge [(111)out] and one in the inner part of the facet [(111)in]. Similarly, the analysis concerns two types of edges: (100)-(111) edges [(100)edge] and the (111)-(111) edges [(111)edge]. C2 H2 adsorption proceeds primarily on the (111)out sites, whereas H2 dissociation proceeds solely on Pd. Hydrogenation of C2 H2 occurs only on the (111)out sites. Further hydrogenation of CHCH2 proceeds on both Pd and the two Cu-(111) sites. For this step, the edges and 18


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corners show a smaller, yet appreciable net-rate. C2 H4 adsorbs on all types of sites, however, most facile on the corners and Pd site. Further C2 H4 hydrogenation proceeds primarily over the corners and edges, however, with a non-zero rate over all sites. C2 H5 hydrogenation is fastest over the Pd and (111)out sites. The large difference in net rates for the nanoparticle sites suggests that the elementary steps flow over the sites where they are most efficient. 58 The local selectivity of each site is related to how fast the desorption of C2 H4 is compared to further hydrogenation. There is a net C2 H4 desorption rate only on the (111)in and (100)edge sites. On the (111)in sites, desorption of C2 H4 is about 100 times faster than further hydrogenation, whereas on the edge, desorption is 10 times slower than hydrogenation. This is the reason for the lower selectivity on edges and corners. Moreover, analyzing the site-dependent TOFs reveals that the selectivity is particularly low near the Pd site (see supporting information). This implies that the Pd concentration should be low to maximize the selectivity. Comparing the nanoparticle to the extended Pd/Cu(111) surface, we find that the rates are slightly higher on nanoparticles. This is surprising as most barriers are higher on the nanoparticle, however, it agrees with the principle of least resistance, as the rates can be faster over multiple types of sites. The reaction mechanism is complex on the nanoparticle, in agreement with the corrugated energy landscape. For example, on the particle, H2 dissociation proceeds solely over Pd, whereas on Pd/Cu(111) both Pd and Cu sites contribute to H2 dissociation. Moreover, the Cu sites have varying energies on the nanoparticle, and C2 H4 can prefer adsorption or desorption, depending on the site. This complex reaction mechanism likely affects selectivity significantly. Comparing the Pd site in the nanoparticle (111) facet to Pd in Pd/Cu(111), the Pd site seems to affect the selectivity stronger when placed in the nanoparticle. The finite size of the nanoparticle (111) facet causes a lower selectivity near the edges. Thus, to improve selectivity, the ratio between (111) sites and edges should be maximized. In conclusion, the analysis shows that the sites exhibit complex kinetic couplings, and we expect that the reaction rates has significant shape and size

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dependencies. 30,31

Adsorbate coverage

Figure 5: Average steady-state coverages as function of temperature for the sites of NP(111) , and the sites in Pd/Cu(111). Pressures: pC2 H2 = 1 mbar, pH2 = 10 mbar, pC2 H4 = 10 mbar. Error-bars are one standard deviation of 10 simulations. Analysis of the adsorbate coverages aid in understanding the selectivity. In Figure 5, we show the coverages of all the included species for the sites on NP(111) and the extended surfaces as functions of temperature. For Pd(111), the most abundant species is CHCH2 , which is reasonable as the binding strength of CHCH2 is high, and since CHCH2 hydrogenation is kinetically hindered. The next most abundant species on Pd(111) is C2 H2 . This is caused by the high binding strength (-1.5 eV at 300 K and 1 mbar), and the endothermic hydrogenation to CHCH2 . C2 H5 has a coverage that is closely correlated with the C2 H2 coverage. This reflects the low selectivity of Pd(111). Although H binds strongly to Pd(111), the coverage 20


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is below 0.1, and is highest in the limit of high temperatures. This is due to the fact that H2 needs two free sites to dissociate, which is more likely at high temperatures where the total coverage is low. For Pd/Cu(111), CHCH2 covers both the Pd and Cu sites with similar coverages. We attribute this to the exothermic C2 H2 hydrogenation to CHCH2 , and to the relatively low binding strength of C2 H4 . Thus, when approaching steady-state, the kinetics causes a slow build-up of CHCH2 . H has a slightly higher coverage on the Pd-sites as compared to the Cu sites. This is reasonable considering that Pd allows for barrierless H2 dissociation and slightly higher binding strength of H. The fact that there is only CHCH2 on the surface is consistent with the high selectivity of Pd/Cu(111). On the nanoparticles, the multiple different sites result in a range of different coverages. H is the most abundant species for both types of (111) facet sites, and the Pd site. This is owing to the fact that H2 needs two sites to dissociate, and that Pd enables barrierless H2 dissociation. CHCH2 is the dominating species for the corners, edges, and (100) sites. This is reasonable as the hydrocarbons prefer diffusing towards edges and corners, whereas H is most stable on the (111) facet. CHCH2 spans a wide range of coverages between all the sites. This reflects that CHCH2 hydrogenation is the slowest step in the reaction branch of C2 H2 hydrogenation to C2 H4 . C2 H5 is present both on the (111) facets and edges, which indicates that the selectivity is lowered owing to the presence of edges. Comparing the Pd site in the extended Pd/Cu(111) surface to the Pd sites in the nanoparticle, the coverages on the nanoparticles are generally larger than for the extended Pd/Cu(111). This is rationalized by the stronger binding energy of the hydrocarbons on the nanoparticles. The H coverage on the nanoparticle facet is high, whereas it is a minority species on Pd/Cu(111). This is partly due to the finite size of the nanoparticle facet, which allows the hydrocarbons to diffuse to edges, leaving more free site-pairs for H2 dissociation. In contrast, on Pd/Cu(111) there is a more homogeneous distribution of CHCH2 that blocks the sites for H2 dissociation. The coverages reflect the presence of kinetic couplings, which

21



cause different elementary steps to proceed preferentially over particular sites. Thus, the coverages on nanoparticles are complicated to predict solely from the reaction energy landscape, in contrast to the case of extended surfaces. Consequently, full kinetic simulations, explicitly over nanopartilces are required to predict the kinetic behavior of the present reaction.

Discussion and conclusions Here, we have shown that Pd/Cu(111) SAA surfaces can yield high selectivities and rates. Pd/Cu nanoparticles were found to have a lower selectivity, primarily owing to edge and corner sites. The results suggest that a rational design strategy is to maximize the number of (111) facet sites and to minimize low-coordinated sites. This can be achieved by large icosahedral Cu particles, which have been theoretically calculated to be stable up to over 1500 atoms, 59 corresponding to about 3.5 nm. Moreover, the Pd concentration must be kept low. Another possibility to enhance selectivity could be to block the edge sites, similar to what has been demonstrated for 1-epoxybutane formation over Pd catalysts. 1 Kinetic couplings imply that extended surfaces cannot adequately capture the complex reaction mechanism over nanoparticles, which we have observed previously for CO oxidation over Pt nanoparticles. 30,31 Assuming that the principle of least resistance holds universally, selectivities could consistently be lower on nanoparticles than on extended surfaces for reactions, where diffusion is facile. This is a consequence of the fact that the reaction path for both desired and unwanted products will be optimized by the kinetic couplings between nanoparticle sites. This phenomenon will imply that particle shape and size affect the reaction to a significant degree. The selectivities we predict for nanoparticles are in an intermediate range between 0 and 1. Calculating an intermediate selectivity requires a large accuracy in the electronic structure calculations, as opposed to cases where the selectivity is close to 0 or 1. For example, at 300 K, changing the selectivity from 0.5 to 0.75, requires only an energy difference of 0.03 eV between the rate-determining steps of the C2 H4 and C2 H6 reaction channels. Thus, 22


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the conclusion that nanoparticles lower the selectivity remains robust, however, with an uncertainty in the absolute number. In summary, we have presented explicit simulations of acetylene hydrogenation over Pd(111), Pd/Cu(111), and small Pd/Cu single-atom alloy nanoparticles. The extended Pd/Cu(111) surface was shown to yield a superior selectivity as compared to Pd(111). This is primarily owing to the Pd sites, which tend to hydrogenate C2 H4 to a larger degree than Cu sites. For the nanoparticles, edge and corner sites lower the selectivity. This is due to strong C2 H4 binding, allowing for C2 H4 hydrogenation to C2 H5 . The presence of multiple different sites on nanoparticles cause complex kinetic couplings, which enable the elementary steps to proceed over different sites. Thus, extended surfaces are inadequate model systems for nanoparticles as they cannot capture the complexity in the kinetics. By elucidating the characteristics of single-atom alloy surfaces and nanoparticles, we have taken an important step towards bridging the materials gap of heterogeneous catalysis.

Supporting Information Available Fits of scaling relations (∆EM ) and used structures, verification of the applied mechanism by mean-field kinetics, relaxed structures, adsorbate-adsorbate interactions, sensitivity to BEP relation, and site-specific turnover frequencies (values and color maps on nanoparticle).

Acknowledgement Financial support is acknowledged from the Chalmers Excellence Initiative Nanoscience and Nanotechnology and the Swedish Research Council (2016-05234). The calculations were performed at PDC (Stockholm) and C3SE (Göteborg) via a SNIC grant. The Competence Centre for Catalysis (KCK) is hosted by Chalmers University of Technology and is financially supported by the Swedish Energy Agency and the member companies AB Volvo, ECAPS AB, Johnson Matthey AB, Preem AB, Scania CV AB, Umicore Denmark ApS and Volvo 23



Car Corporation AB. We gratefully acknowledge Professor J. Will Medlin for valuable discussions.

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Selective acetylene hydrogenation over single-atom alloy

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