Nickel Bimetallic

Article pubs.acs.org/JPCC

Water Adsorption and Dissociation on Copper/Nickel Bimetallic Surface Alloys: Effect of Surface Temperature on Reactivity Smita Ghosh,§ Seenivasan Hariharan,§ and Ashwani K. Tiwari* Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur 741246, India S Supporting Information *

ABSTRACT: Water dissociation is the rate-determining step (RDS) in the industrially important water gas shift (WGS) reaction. Low temperature Cu catalysts are limited by a higher barrier to dissociation whereas Ni surfaces with lower barriers for this reaction are deactivated by carbon deposition due to CO dissociation. Density functional theory (DFT) calculations are performed on a series of overlayer and subsurface bimetallics starting with Ni(111) and Cu(111) to understand the synergistic catalytic activity of Cu/Ni bimetallics toward H2O dissociation which is the RDS. Surface parameters like surface energy, work function and density of states were calculated and were correlated with the change in reactivity. Transition state (TS) calculations showed that addition of Ni to Cu(111) surfaces decreased dissociation barriers while the scenario is reversed when Cu atoms replace Ni in Ni(111) surface with no linear relation with any calculated surface properties in both cases. Linear relations were found to correlate well the reaction energies with the activation energy barriers. Effects of surface temperature were included by determining the change in the barrier heights and barrier locations with lattice atom motion calculated from TS calculations. Dissociation probabilities calculated at different surface temperatures using semiclassical methods showed that increase in surface temperature increases dissociation probabilities where the extent of increase is strongly dependent on the change in barrier heights. Overall, Ni addition to Cu(111) surface proved beneficial while the Cu addition to Ni(111) surface proved detrimental to H2O dissociation.

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properties in order to obtain optimum activity and selectivity,9 the next rational step to overcome the limitations is to combine the effectiveness of these two metals and produce an bimetallic/ alloy catalyst with superior catalytic properties. Catalysts containing two metals offer flexibility in the design of the catalysts and greater tunability in reactivity. This feature has caught the attention of many and was explored in the field of catalysis and electrocatalysis.10−19 In this study, a bimetallic Cu−Ni surface alloy catalyst is targeted which shows a lower barrier for H2O dissociation which will result in increasing the ratio of H2O dissociation over CO dissociation thereby decreasing carbon formation on surfaces. It is now clear that in many circumstances, reactivity of bimetallic surfaces can be explained by the concept of d-band center theory.20 Many informative reviews on various other aspects of bimetallics are available in the literature.21−23 These reviews identified that the interplay of electronic and geometric effects, ensemble, and ligand effects are the reasons for the increased reactivity. There are number of reports showing that bimetallic alloy surfaces/surface alloys have advantages over pure metals such as greater flexibility in chemical composition, interatomic arrangement etc., which improve both reactivity and selectivity

INTRODUCTION In the past 3 decades, water adsorption and dissociation on metal surfaces drew a great deal of attention of both theoretical and experimental researchers due to its importance in industrial reactions pertaining to heterogeneous catalysis and electrochemistry. The water gas shift (WGS) reaction1 is one of the most celebrated feedstock industrial catalytic processes producing hydrogen. This reaction also plays an important role in methane steam reforming (MSR) process2 and removal of gaseous impurities from hydrogen sources used in fuel cells.3 The industrial water gas shift reaction consists of two steps: (i) high-temperature shift (with a Fe2O3/Cr2O4 catalyst) and lowtemperature shift (with CuO/ZnO/Al2O3 catalyst). H2O dissociation is the rate-determining step in the low temperature WGS reaction where Cu-based catalysts are mainly employed. Recent theoretical and experimental studies found that Cu and Ni were more effective in catalyzing H2O dissociation, with Ni showing a lower barrier for H2O dissociation.4,5 However, monometallic Cu and Ni surfaces as catalysts have been found to have their own limitations. Cu-based catalysts showed larger dissociation barrier to water dissociation, while Ni-based catalysts, despite having a lower barrier to dissociation, were equally effective in catalyzing competing CO and H2O dissociation reactions leading to C formation on the catalysts which further degraded the activity of the catalysts.6−8 As the ultimate goal of catalytic design is to have control over the © XXXX American Chemical Society

Received: May 14, 2017 Revised: July 6, 2017 Published: July 6, 2017 A

DOI: 10.1021/acs.jpcc.7b04637 J. Phys. Chem. C XXXX, XXX, XXX−XXX

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The Journal of Physical Chemistry C of the catalyst for water adsorption and dissociation.6−8,24−34 Non-noble bimetallic surfaces are of greater importance in catalysts due to its low cost and abundance. Enhancement in water dissociation was observed on bimetallic alloy surfaces/ surface alloys on which dissociation is generally easier than on pure metals giving rise to new pathways for catalyst design. Trends in water dissociation on various bimetallic surfaces showed that doping of metallic surfaces with atoms of other metals leads to a stabilizing cooperative effect of both in the adsorption of water, its dissociation products and transition state configuration.27 Surface morphology dependent adsorption preference were noticed wherein Ni, Ir, and Cu atoms seems to stabilize H + OH coadsorption better among the studied alloys. The catalytic activity of bimetallic systems found to increase by lowering the activation energy for water dissociation compared to that on pure surfaces due to the presence of second metal entity at regions close to active site producing important changes in electronic structure. Recent investigations on methanol dissociation on bimetallic surfaces showed that alcohols also behave similar to H2O dissociation since the dissociating O−H bond is similar in both the molecules. 35 Energy barriers for methanol dissociation calculated from the BEP relationships for H2O dissociation on bimetallic surfaces illustrate that CH3OH and H2O follow similar dissociation mechanism. Among these bimetallic alloy surfaces/surface alloys, Cu/Ni bimetallic surface alloys and alloy surfaces are of recent interest in the context of water−gas shift reaction because nickel and copper are among the best known non-noble metallic catalysts for WGS. Copper and nickel are mutually soluble in any amount (unlimited solid solubility). With similar structure, atomic radii and electronegativities, these two metals can also form substitutional solid solutions. Nickel binds stronger with the metal having less occupied valence d-band while Cu binds stronger with metals at extreme left or right of the periodic table (either empty or fully filled valence states); half filled 4s orbital interacts strongly.23 Also, it is known that Cu transfers charge to early transition metals and withdraw charge from late transition metals. Ni−Cu alloys are long known for their role in chemical reactions. Khulbe and Mann in their review on nature of Ni−Cu alloys for their catalytic activity noted that these alloys can be good catalysts for a number of reactions.36 Similar atomic size and complete miscibility over a wide range of temperature and compositions makes them ideal for alloy catalysis.37 Ni−Cu catalysts exhibited varied activity for different surface compositions. However, they could not pin down any electronic parameter as a reason (responsible) for their catalytic activity. The effect of the Ni−Cu ratio on the weighting variation of WGS reaction in MSR reaction was studied experimentally.25 It was observed that carbon deposition on the surface, which is detrimental to the activity, increased with increase in Ni on the surface. However, addition of Cu to Ni increases WGS activity and avoids carbon formation and this rise in activity is attributed to the presence of bimetallic Cu−Ni species in the mixture. Activity of water−gas shift reaction over bimetallic Cu−Ni catalysts supported on La-doped mesoporous ceria revealed that the presence of Cu in bimetallic catalysts resulted in suppression of undesired methanation side-reaction while Ni component is important for high WGS activity.8 Catalytic activity was studied on alloys of varying Ni and Cu compositions such as Cu4Ni16, Cu10Ni10, and Cu16Ni4 and compared with that on pure Ni20 and Cu20 particles (numbers

are wt %). Presence of Cu in bimetallic catalysts reduced CO conversion compared to Ni20. Cu4Ni16 catalyst showed the best WGS performance among all the catalysts studied at 300−400 °C. In a DFT study, different Ni ensembles such as a monomer, dimer, trimer, pseudomomolayer on Cu(111) were investigated for its WGS activity.6 Presence of subsurface Ni showed reaction barrier comparable to that on Cu(111). Using weighted d-band centers they showed that H2O dissociation enhances as the d-band center gets close to the Fermi level. Introducing moderate amount of Ni into Cu enhances water dissociation and promotes undesired methanation on Ni-doped surfaces. It was concluded that Cu−Ni bimetallic catalysts with highly dispersed Ni ensembles containing lower Ni concentration may have relatively better activity and selectivity toward WGS. In another study, using DFT, Huang et al., addressed the difference between Ni and Cu, and the reverse combination toward WGS reaction.30 Four alloys with different Ni and Cu concentrations on Cu and Ni surfaces were investigated and reported that alloying reduced H2O dissociation barriers compared to Cu, that are very similar to the values reported on nickel. Irrespective of the bulk metal, alloys surfaces containing two atoms of Ni always tend to favor water dissociation thermodynamically and adsorption of H and OH is stronger on this alloy. No clear kinetic difference between Cu/ Ni and Ni/Cu alloys were found while these alloys also tend to favor CO dissociation thermodynamically which will benefit resistance to unfavorable methanation reaction. Cu/Ni alloys increased WGS activity (both on Cu/Ni and Ni/Cu) and the activity was attributed to dispersed or low-concentration Ni which provides excellent balance between activity and selectivity. In addition to Ni based alloys, several Pt- and Pd-based alloys were also studied for water dissociation. Cu−Pt near surface alloy (NSA) was tested as water gas shift catalysis using STM, XPS, TPD, and DFT.26 Enhanced Cu concentration in the subsurface layer of the Pt host is found to improve the lowtemperature WGS catalyst. DFT calculations showed that the Cu−Pt NSAs can activate H2O easily and can be resistant to CO and formate poisoning thereby make them a better catalyst. Another important alloy which has received some attention is the PdZn alloys and near surface alloys. Pd/ZnO displayed high selectivity and activity toward methane steam reforming and can be considered to be a promising replacement for Cu/ZnO catalysts which is thermally unstable. Previous studies showed that water dissociation can occur on multilayer PdZn surface alloy while water keeps intact on 1:1 monolayer surface alloy. To validate this observation, H2O dissociation was studied on monolayer and multilayer flat (111) and stepped (221) PdZn surfaces.32 Water interacts more strongly and is more stable on the multilayer while dissociation barriers on the monolayer surface alloy are lower. On flat surfaces, water monomer has a tendency to desorb instead of dissociation, whereas on rough surfaces, defects favor H2O dissociation. Studies on low (LT) and high temperature (HT) annealed PdZn alloys were carried out for their activity toward water dissociation using kinetic Monte Carlo (KMC) simulations.33 It was concluded that the water dissociation is likely on LT alloy than on HT alloy owing to the presence of triple Zn ensembles (3-fold sites). Moreover, surface atomic arrangement and subsurface composition was found to affect the surface chemistry significantly. Similarly, Pd alloyed with Au was also studied for the water gas shift reaction using DFT.34 On Pd−Au alloy, the energy barrier for B


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The Journal of Physical Chemistry C

wave expansion truncated at 400 eV. For the adsorption energy calculations, convergence criterion is when all the forces are smaller than 0.01 eV/Å. Transition state geometries are identified by climbing image-nudged elastic band (CI-NEB) method.48 Transition state calculations are considered converged when the forces are less than 0.05 eV/Å. Adsorption energy, Eads is expressed as Eads = E(adsorbate+surface) − [Eadsorbate + Esurface], where E(adsorbate+surface), Esurface, and Eadsorbate are energies of the adsorption systems, metal slab, and the molecule in the gas phase, respectively. 2.2. Lattice Motion: Sudden Model. Majority of DFT calculations were carried out under the rigid surface approximation in which the motion of the surface atoms are frozen. However, including the motion of lattice atoms has shown to decrease the energy barrier and resulted in higher reaction probabilities with increasing surface temperatures. Dynamical studies of methane,49−51 nitrogen,52 hydrogen,53−55 and water dissociation56,57 on metal surfaces invariably showed that the effect of lattice motion is important and is emphasized in a recent perspective that examines the dissociative chemisorption of CH4, H2O, and CO2 on smooth and rough metal surfaces.58 Including motion of heavy lattice explicitly in quantum calculations involves a multidimensional model with exact potential energy surface (PES) which is computationally expensive. Herein, a simple and physically meaningful sudden model is used to include the effect of surface temperature.49,50 This approach involves the calculation of two linear parameters, α (mechanical coupling), and β (electronic coupling), defined by ΔEbarrier = −βΔQ, and ΔZbarrier = −αΔQ, where, Q is the lattice degree of freedom perpendicular to the surface.ΔEbarrier, and ΔZbarrier account for the change in barrier height, and relative collision velocity, respectively, with the change in the position of lattice atom from equilibrium position (Q = 0). Q is chosen to vary to a maximum of ±0.2 Å on the either side of the equilibrium position. Both on Ni-based and Cu-based surfaces, the TS is modified, to a good approximation, only by the motion of the atom over which water dissociates. In other words, the force on this atom, with the molecule at the TS, is significant while that on the other lattice atoms are relatively very small. Using the reaction path model with 9 degrees of freedom for a fixed value of Q, the minimum energy path is described by a mass-weighted coordinate s. The potential energy for this system is approximated as an inverted parabola having the width equal to the square of iω9(0), which is the imaginary frequency at the transition state. Neglecting the effective mass contribution to tunneling, semiclassical tunneling probability through this barrier is calculated as,

dissociation is 0.60 eV and this barrier is lower compared to that for water dissociation on Au(100) and Pd(111) surface showing synergy between two metals and offering extra stabilization for transition states. Reduction in barrier is attributed to the strain induced by lattice mismatch (1.69 and 1.74 Å for Pd and Au). Very recently, H2O adsorption and dissociation was studied on Pd−Cu(100) bimetallic surface alloy wherein Pd metal belongs to the same group as nickel. Among the five surface alloys with varying concentration of Pd (Pdx−Cu4‑x; x = 0−4), Pd2−Cu2(100) surface with two surface Pd atoms was found to be kinetically and thermodynamically optimal for H2O dissociation.38 Similarly, Fe(111) surface with a barrier of 1.05 eV for H2O dissociation showed a decrease in the activation barrier heights to 0.55 and 0.43 eV, respectively, for surface alloys obtained by replacement of 1 and 2 surface atoms by W thereby highlighting the advantages of using surface alloys in catalysis.39 The aim of this work is to understand the rate-determining water adsorption and dissociation step of WGS reaction on bimetallic close-packed surface alloys of Cu and Ni and pin down the reactivity change to one or more electronic effects. In addition, we study in detail the effect of surface temperature on reactivity using the parameters calculated from density functional theory (DFT) and compare them with the results from rigid surface calculations. Here we worked with Cu- and Ni- based bimetallic surface alloys for water adsorption and dissociation for the following reasons: (i) Cu and Ni metals are abundant and less expensive compared to the metals like Au, Pt, Ag, Pd, and other metals discussed in the above paragraphs, (ii) the miscibility of Cu and Ni is high in a wide composition range and temperature, and (iii) Cu-based catalysts are currently employed in the WGS reaction, and recent studies have shown that Ni can catalyze H2O dissociation better than Cu. To the best our knowledge, there are no theoretical studies addressing the effect of surface temperature on water dissociation on any bimetallic surface alloys. Using DFT and semiclassical methods, this study shows the change in reaction probability with surface temperature for all the bimetallic surface alloys considered.

2. METHODS 2.1. Density Functional Theory Calculations. DFT based Vienna ab initio simulation package (VASP)40−43 was used to perform all total energy calculations. Plane wave basis set and Perdew−Burke−Ernzerhof (PBE)44,45 exchangecorrelation functional within generalized gradient approximation was used to treat non local exchange−correlation effects. Fully non local optimized projector augmented wave (PAW)46,47 potentials are used to express the interaction between the ionic cores and electrons. Metal surface was modeled as slab super cell with periodic boundary conditions. The Ni(111), Cu(111), and all bimetallic surfaces consist of four layers within 2 × 2 unit cell. Vacuum space of 11 Å is maintained between layers in the z-direction to avoid the interaction with surfaces of adjacent slabs. Equilibrium lattice constant 3.52 Å for Ni and 3.61 Å for Cu surfaces as found from the bulk geometry optimization in VASP is used for constructing the initial geometries for all surfaces. All the atoms of these surfaces are relaxed and optimized before using these surfaces for other calculations. For bimetallic surfaces we use the lattice constant of host metal surfaces. The 5 × 5 × 1 Γcentered grid of k-points was used for structure optimization. Spin-polarized calculations have been performed with plane

P(E ; Q ) =

where b =

1 1+e

2π , ℏ |ω9(0)|

b(Eb − βQ − E)

≈ eb(E − Eb + βQ )

(1)

E is the incident energy, Eb is the barrier

height (without zero-point energy corrections). This P(E;Q) is the dissociation probability at given E and Q. The dissociation probability calculated using this corrected potential is Boltzmann averaged over all possible values of Q for different substrate temperatures, T (100, 300, and 500 K in this case) using the lattice distortion energy calculated by DFT. Assuming that the metal atom of mass M moves harmonically with a frequency Ω, the reaction probability at a given surface temperature, T and energy becomes, C


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Figure 1. Construction of Cu-based surface and subsurface alloys from a pure Cu(111) metal (host) surface by replacing top layer atoms one-by-one by a Ni (guest) metal atom (top and side views). Ni-based surface and subsurface alloys were also constructed in a similar manner. ∞

Pr(E ; T ) =

∫−∞ eb(E−E +βQ ) b

M Ω2 −M Ω2Q 2 /2kT e dQ 2πkT

Cu(111) surface, one by one, until a monolayer coverage of the guest atom (Cu and Ni respectively) is attained. Ni/Cu(111) bimetallic surfaces constructed by replacing Cu by Ni on Cu(111) surface and Cu/Ni(111) bimetallic surface is obtained in a similar fashion. Subsurface alloys are obtained by replacing the second layer (from the top) of the host metal completely by the guest metal atoms, i.e., Cu by Ni and vice versa as shown in Figure 1. Overall, for each base surface (Ni(111) or Cu(111)) we have constructed four surface alloys with different surface compositions and one subsurface alloy with one monolayer coverage of alloying element. Conventional nomenclature for the sites on close-packed fcc(111) surfaces viz., top, fcc (hollow), hcp (hollow) and brg (bridge) are used throughout the paper.

(2)

Dissociation probabilities, Pr(E,T), thus obtained are further improved by including the mechanical coupling, α, by averaging over the lattice atom momentum P, as described earlier49 by using the following form. S(E ; T ) =

∫ dEcm

Ms′ 4πkTμT Ecm

⎡ M ′ ⎛ 2Ecm − exp⎢ − s ⎜⎜ ⎢ 2kT ⎝ μT ⎣

2E M

⎞2 ⎤ ⎟⎟ ⎥Pr(E ; T ) ⎥ ⎠⎦

(3)

3. RESULTS AND DISCUSSION Surface properties have long been a first step toward descriptors in heterogeneous catalysis. In this study, several surface properties were calculated to characterize the bimetallic surface alloys. These properties will further be used to explain the trends in adsorption and dissociation energies of H2O on these surface alloys. The properties and their implications are explained below. 3.1. Surface ‘Energy’ and Work Function Calculations. Surface energy (SE) is defined as the amount of energy required to cleave an infinite crystal into two parts, i.e. the energy required to form a new surface. It is calculated as shown in eq 6:

The coordinates Z and Q are transformed to a relative coordinate Z′ = Z − αQ and a corresponding center-of-mass coordinate. The reduced mass corresponding to the relative collision coordinate, Z′ is μT =

Ms′M M , where Ms′ = 2s Ms′ + M α

(4)

The integral over P0 was converted to an integral over the center-of-mass collision energy, Ecm, as shown below. Ecm =

2 P ⎞ 1 ⎛ 2E μT ⎜ −α 0⎟ 2 ⎝ M Ms ⎠

(5)

In this equation, the expression in parentheses is the relative water−metal atom collision velocity for a given incident energy E, and metal atom momentum, P0. 2.3. Bimetallic Surface Construction. Since surface composition and electronic structure dictate and determine reactivity of single crystal surfaces, “bimetallic surface alloys” with various compositions were constructed. Since there is a huge difference between the terms bimetallic surface alloys and bimetallic alloy surfaces, we prefer to use “bimetallic surface alloys” instead of ‘bimetallic alloys surfaces’ or any other term. Two types of alloys viz., Ni-based and Cu-based, were constructed by replacing the surface atoms of Ni(111) and

Esurf =

1 (Eslab − Natoms × Ebulk ) 2

(6)

Here, Eslab is the total energy of the slab, N is the number of total atoms, and Ebulk is the energy per atom in the bulk. Each slab contains two symmetric surfaces and hence the total energy is divided by a factor of 2 in the above equation. In general, it is known that smaller the surface energy is, easier is to form a surface, i.e., the surface with smaller surface energy is stable. Therefore, a larger value of surface energy will lead to an unstable surface which is expected to be reactive and is important in catalytic surface science. D


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Table 1. Surface Energy and Work Function Values of the Cu- and Ni-Based Surface Alloys and the H, OH, and H2O Adsorption and H−OH Coadsorption Energies on These Bimetallic Surface Alloys system

surface energy (eV/atom)

work function (eV)

Eads(H) (eV)

Eads(OH) (eV)

Eads(H2O) (eV)

Eads(H + OH) (eV)

Cu(111) Ni1_Cu(111) Ni2_Cu(111) Ni3_Cu(111) Ni4_Cu(111) sub-Ni4_Cu(111) Ni(111) Cu1_Ni(111) Cu2_Ni(111) Cu3_Ni(111) Cu4_Ni(111) sub-Cu4_Ni(111)

1.72 1.80 1.95 2.12 2.26 1.77 2.55 2.50 2.41 2.30 2.17 2.62

4.71 4.70 4.75 4.88 5.01 4.59 5.23 4.74 4.80 4.96 5.05 5.17

−2.72 −2.59 −2.81 −2.26 −2.00 −2.45 −2.83 −1.62 −2.64 −2.47 −2.51 −2.86

−3.20 −3.16 −3.35 −3.49 −3.43 −3.09 −3.36 −3.24 −3.04 −2.93 −2.95 −3.22

−0.12 −0.17 −0.17 −0.13 −0.18 −0.10 −0.16 −0.10 −0.10 −0.10 −0.08 −0.09

−4.74 −4.93 −5.07 −5.47 −5.51 −4.67 −5.26 −5.08 −4.94 −4.68 −4.45 −5.22

Work function (WF), is defined as the minimum energy needed to remove an electron from the bulk of the material through surface to a point outside the material, i.e., vacuum. It can be expressed as follows:

φ = Evacuum − EFermi

(7)

where Evacuum is the electronic potential calculated in the vacuum region (where it remains constant), and EFermi denotes the Fermi energy of the slab. From the definition, it follows that a system with larger work function and small surface energy is more stable. Calculated values of surface energies and work function for various Cu/Ni bimetallic surface alloys are presented in Table 1 and the plots of corresponding values for various Cu/Ni bimetallic surface alloys are given in Figure 2, parts a and b. For Ni-based systems, replacing Ni by Cu decreases surface energy (SE) and the lowest surface energy is calculated for Cu4_Ni(111) indicating that this surface is stable and should have low reactivity. The reverse is true when replacing Cu by Ni in Cu(111). In both the cases, the surface energies of subsurface alloys are slightly higher than the parent metal surfaces. Overall, the surface energies for Ni-based bimetallic surfaces decrease with the introduction of Cu suggesting decrease in reactivity. On the other hand, an increasing trend in SE was calculated for Cu-based bimetallic surfaces on sequential replacement of Cu by Ni, indicating an increase in reactivity. Moreover, in both surfaces, the increase or decrease in the SE’s shows a near-linear behavior. Work function values were calculated using DFT and also using the empirical formula proposed using experimental results by Takasu et al.59 for Cu−Ni alloys. DFT values showed that for Ni-based surface alloys, work function decreases appreciably when one of the Ni atoms is replaced by Cu. Further increase in the number of Cu atoms, however, increased the work function values. For Cu-based surface alloys, for more than two Ni atoms, there is a linear increase in the work function values with the increase in the number of Ni atoms. The work function values for pure Cu(111) and Ni1_Cu(111) and Cu1_Ni(111) were almost similar. In both the cases, the subsurface alloys showed lower values of work function than their pure metal counterparts. On the other hand, work function values calculated using the empirical formula, which is formulated based on the percent composition of Ni in the surface alloy predicts a linear decrease with increasing Cu concentration in Ni(111) surfaces and a linear increase with increasing Ni in Cu(111) surfaces. Though the DFT values show good agreement with the predicted values for Cu-based

Figure 2. (a and b). Plots of trends in surface energies and work function for different Cu/Ni-based surface alloys systems. Pure A corresponds to pure Cu(111) or Ni(111) surface and A can either be Cu or Ni. In Ni-based alloys (solid squares), A is Ni(111) and B is Cu while in Cu-based surface alloys (solid triangles) the reverse holds true. BxA (x = 1, 2, 3 and 4) correspond to four surface alloys having different adatom concentration. Solid lines correspond to the data obtained from DFT while the broken lines correspond to the values calculated using the empirical formula obtained from ref 59,

alloys, the formula fails to capture the trend for the Ni-based alloys. The failure of the formula in predicting the work E


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Fermi level with a calculated d-band center of −1.54 eV. Replacing one of the surface Ni atoms by Cu lowered the population near Ef compared to pure Ni(111) with a d-band center of −1.66 eV from −1.54 eV. Subsequent replacements of Ni by Cu lead to the shift of the maximum of the DOS plot to lower energies compared to Ef resulting in further decrease in the d-band center values for Cu4_Ni(111) to −2.47 eV suggesting a decrease in reactivity with increase in the Cu content in Ni-based surface alloys. Subsurface alloy showed even lower value of d-band center compared to the surface alloys. In Cu-based alloys, substituting Ni for Cu resulted in increase in the population of states near the Ef and also an increase in d-band center values from −2.47 eV for Cu(111) to −1.05 eV for Ni4_Cu(111) surface alloy suggesting an increase in reactivity with increasing Ni content on the surface. Interestingly, the d-band center value for sub-Ni4_Cu(111) surface lies in between the values obtained for Ni2_Cu(111) and Ni3_Cu(111) which is different from that observed for Cubased alloys. 3.3. H2O, H, and OH Adsorption and H + OH Coadsorption. As the gas molecules approach the surface, the primary process which would occur under the influence of the potential of the metal surface is adsorption (weak or strong) before it dissociates. Variation of adsorption energies with substitution of Cu/Ni on Ni(111)/Cu(111) is shown presented in Table 1 and in Figure 4. Adsorption of molecular H2O was studied and selected to be the initial state, while the coadsorption of H and OH on the metal surfaces in their most stable sites was chosen to be the final state. Adsorption of the dissociation products, H and OH studied individually to chose the possible coadsorption sites. H2O Adsorption. Adsorption of water molecule in the gas phase was studied on the pure metal and the surface alloys on a fixed site to understand the influence of the neighboring atoms on the site under study. Water adsorbed on the top sites on pristine surfaces and surface alloys while the adsorption energies varied with number and type of neighboring atoms. It is to be noted that H2O adsorption energies calculated using slab supercell models for the metal surfaces might not be accurate without taking van der Waals forces into account. However, the trend in the adsorption energies will not be affected significantly. On Ni-based surfaces, water adsorption is stronger on pristine Ni(111) surface (0.16 eV) compared to the surface and subsurface alloys. Substitution of first Cu on Ni(111) rendered the adsorption weaker by ∼0.06 eV. Further substitution with Cu atoms did not modify H2O adsorption energies until Cu3_Ni(111) (0.10 eV) whereas the adsorption energy slightly lowered for Cu4_Ni(111) (0.08 eV). Subsurface-Cu4_Ni(111) and Overlayer Cu system showed similar energies for water adsorption suggesting that complete substitution of Ni by Cu either on the overlayer or in the subsurface layer weakens H2O adsorption. On the other hand, substitution of Ni on Cu(111) surface lead to stabilization of H2O on these surfaces except on Ni3_Cu(111). H2O adsorption on substituted Ni top sites on Cu(111) surfaces were stronger and similar in energy compared to pure Ni(111) surfaces while the H2O adsorption on substituted Cu top sites on Ni(111) surfaces were weaker and similar in energy compared to pure Cu(111). However, in both cases the neighboring atoms did not play a significant role in H2O adsorption on surface alloys. On subsurface alloys, the effects of Ni in subsurface layer and Cu in subsurface layers had a similar effect on H2O adsorption.

function values can be attributed to two reasons: (i) the formula takes into consideration only the surface concentration of the alloyed Ni irrespective of the bulk composition, and (ii) the empirical formula was proposed using the values obtained from sparse measurements. It is also suspected that the alloys used in the above measurements predominantly contained Cu in the bulk. Calculated surface energy and work function values suggest that the introduction of Ni in Cu(111) surfaces might result in increase reactivity while the inclusion of Cu in Ni(111) surfaces may lead to decrease in reactivity. 3.2. Density of States (DOS). Alloying increases the possible bonding sites for adsorbate and changes the electronic structure of the system. Within the premise of d-band center model,20 metals can be alloyed to tune the position of the dband center. According to earlier calculations, in most cases, upshift of d-bands reduces barrier to the dissociation whereas downshift results increase in the barrier height. In this study, the d-band center were calculated from the DOS plots. The corresponding density of states plots and d-band center values Ni-based and Cu-based surface alloys is shown in Figure 3. For Ni(111), the surface states are more populated close to the

Figure 3. Plots of density of states (DOS) for different (a) Cu-based and (b) Ni-based surface alloys with the d-band center values given on each plot. F


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Figure 4. Plots of H, OH, and H2O adsorption and H + OH coadsorption energies on different Cu/Ni surface alloys. The nomenclature of the systems in the x-axis is the same as in Figure 2.

H Adsorption. First Cu substitution leads to drastic decrease in adsorption energy of H on Ni-based alloys while the subsequent substitution leads to stronger adsorption compared to singly substituted surface but slightly weaker than pure Ni(111). On Cu-based surface alloys, H adsorption energy increased with Ni substitution up to Ni2_Cu(111) and decreased further until Ni4_Cu(111). Pristine Cu and Ni surfaces and subsurface alloys showed similar adsorption energies in both the cases. OH Adsorption. Increase in the concentration of Cu in Ni(111) surfaces decreases adsorption and almost reaches saturation at higher Cu content on the surfaces. On Cu(111) surfaces, increase in Ni substitution resulted in stabilization of OH, though there was a slight decrease in adsorption energy for Ni1_Cu(111) surface. In both cases, subsurface alloys adsorbed OH weaker than the pure metal surfaces. H + OH Coadsorption. H and OH were coadsorbed on the surfaces to identify the final state configurations for transition state calculations. H and OH in fcc hollow sites were found to be the most stable sites for H + OH coadsorption. Overall, on Ni-based surface alloys, the final state is less stabilized with the increasing Cu concentration on the surface, whereas, on Cubased surfaces increasing substitution of Ni resulted in stronger coadsorption of the dissociation fragments. 3.4. Activation Energy. Activation energies for different Cu-based and Ni-based alloy surfaces are plotted in Figure 5. For Ni-based surfaces, substitution of first Cu in the surface increased the activation energy for water dissociation. Introducing the second Cu atom decreases the activation

Figure 5. Change in the activation energy barriers for various Cu/Ni surface alloy systems. The nomenclature of the systems in the x-axis is the same as for Figure 2.

energy slightly while further increase in surface Cu concentration up to monolayer level increases the energy barrier for water dissociation. On the other hand, on Cu-based surfaces, replacing the first Cu atom by Ni decreases the barrier and a further decrease in activation energy is found when two Cu atoms were replaced by Ni. However, a sudden hump in the curve is calculated for three Ni atoms on the surface, while the Ni-monolayer covered Cu surface showed the lowest energy barrier among the Cu-based systems and also the lowest among G


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Figure 6. Plot of activation energy barriers vs. surface energies for various Cu/Ni surface alloy systems.

Fe(111)39 bimetallic surface alloys where in the surface compositions Pd2_Cu(100) and W2_Fe(111) surfaces showed lower barrier. These results indicate that the presence of 50% composition of each alloying element in a bimetallic surface alloys lead to decrease in activation energy for reaction. To explain the trend in the reactivity of these alloy surfaces and to indentify a descriptor, four different surface properties are used. The role of descriptors is to simplify the computational effort in predicting reactivity. With this aim, the following properties are tested as descriptors. They are (i) surface energy, (ii) work function, (iii) d-band center, and (iv) the force experienced by the atom on which the water molecule dissociates (also known as the electronic coupling parameter β as defined in the methods section). 3.4.1. Surface Energy vs Activation Energy, Ea. Although the concept of surface energy is comparatively old and the calculation of this parameter has become a routine, surface energy still remains as a qualitative descriptor of reactivity. Recent studies carried out on Cu−Ni nanocubes and octahedra for aldehyde-alkene-amine coupling reaction showed that the reactivity on Cu−Ni nanocubes were higher than that found on Cu−Ni octahedra.60 Higher reactivity of nanocubes was attributed to the presence of high surface energy (100) facets when compared to (111) facets found on octahedra with lower surface energies. In another study, a volcano-shaped correlation between the experimental exchange current density and the theoretical surface energies were plotted to identify the most reactive surface. This study supports the use of surface energy as a descriptor of catalytic activity.61 In this line, to understand the relation between the surface energy and reactivity, a plot of surface energy vs activation energy (Ea) for the Cu-based and Ni-based surface alloys are given in Figure 6, parts a and b, respectively. The plots were linearly fitted with a straight line to identify whether there exists any linear relationship between the surface energy and activation energy or not. The coefficients of regression (R2) obtained for both Cu- and Ni-based surface alloys are 0.62 and 0.73, respectively. Among the Cu-based surface alloys Ni1_Cu(111) and Ni2_Cu(111) were away from the fitted straight line when compared to Cu(111) and other surface alloys whereas among the Ni-based surface alloys, values for Ni(111) and Cu1_Ni(111) fall away from linearity. Deviation from linearity is clear while the fit is better for Nibased surface alloys compared to Cu-based surface alloys based on the R2 values. Usually, increase in surface energy results in

all the bimetallic surface alloys studied. In both cases, the activation energy barrier on subsurface alloys is slightly higher than the pure metal surfaces and the subsequent increase in Cu or Ni concentration on the surface does not lead to a linear increase or decrease in the activation energy values. Interestingly, monolayer Cu covered Ni surfaces showed barrier larger than that calculated on the pure Cu(111) surface whereas monolayer Ni-covered Cu surfaces showed a barrier smaller than that for the pure Ni(111) surface. Overall, the lowest barrier for water dissociation was calculated on Ni4_Cu(111) surface while Ni2_Cu(111) surface shows only a slightly higher barrier. These results clarify that the subsurface alloys are not electronically modified enough to show an appreciable change in the barrier heights and hence these alloys can be safely ruled out from the list of contenders for a promising catalyst for water dissociation. On Ni(111) surface, H2O dissociates on the top site of the Ni atom while on Cu(111) surfaces H2O dissociation takes place slightly away from the top site (not exactly on the top site) as shown in Figure S1a for both Cu- and Ni-based surface alloys. On the surface alloys, the dissociation of H2O on the Ni atoms on Cu(111)-based surfaces is not strongly influenced by the nature of underlying Cu atoms, and the reaction takes place to a good approximation, on the top site as in pure Ni(111). On the other hand, although the reaction occurs on the Cu atoms on Ni(111)-based alloy surfaces, again the influence of Ni is not predominant and the reaction occurs away from the top site as observed on Cu(111) surface. From these observations, it is clear that the alloyed atoms and not the atoms of underlying metal surface have a significant effect on the dissociating geometry of H2O at transition state. Activation energy barriers computed in this study agrees well with the DFT study on water dissociation on Cu-based Cu−Ni surface and subsurface alloys.6 However, an almost similar difference of 0.14 ± 0.02 eV was found between the values of the present and the earlier study. This difference is attributed to the usage of 2 × 2 supercell in this work which is known to underestimate the activation energies when compared to 3 × 3 supercell in the earlier one. The results qualitatively agree well with each other. It is worth noting that within the same system the surface alloys with 2 Cu atoms and 2 Ni atoms either on Cu(111) or Ni(111) showed lower barrier compared to other surface compositions (except for Ni4_Cu(111)). Similar observations were also reported for H2O dissociation on Pd−Cu(100)38 and W− H


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Figure 7. Plot of activation energy barriers vs work function for various Cu/Ni surface alloy systems.

Figure 8. Plot of activation energy barriers vs. d-band center for various Cu/Ni surface alloy systems.

relationship between the activation energies and work function (Figure 7). Parts a and b of Figure 7 correspond to the work function values calculated from DFT and parts c and d of Figure 7 correspond to the work function values calculated using an empirical formula proposed earlier59 for Ni−Cu alloy systems. Larger the work function; lesser is the reactivity. A linear fit to the work function (DFT) vs activation energy plot for Ni-based surface alloys was poor with R2 = 0.03 (Figure 7a) while the fit for Cu-based surface alloys (Figure 7b) was better (R2 = 0.58) and agrees qualitatively with the expected trend.

increase in reactivity. Herein, since reactivity is directly related to the activation energy barrier, these values were plotted against the surface energy values. Although there is a qualitative trend in the decrease in activation energies with increasing surface energies, the relationship, however, is not linear. This deviation from linearity suggests that the there is a complex interplay between the alloying element and the underlying surface in determining reactivity. 3.4.2. Work Function vs Ea. Plots similar to the ones described in the previous section were made to establish a I


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Table 2. Transition State Geometries and Energies for H2O Dissociation on Various Cu- and Ni-Based Bimetallic Surface Alloysa system

Ea (eV)

rO−H (Å)

θHOH (deg)

Z (Å)

Er (eV)

Fn (eV/Å)


1.14 0.87 0.67 0.73 0.61 1.20 0.72 1.02 0.94 1.01 1.24 0.77

1.68 1.58 1.53 1.57 1.53 1.69 1.56 1.66 1.64 1.67 1.68 1.52

123.0 124.7 125.0 124.0 126.0 123.5 124.8 123.2 126.2 125.3 123.4 125.1

1.92 1.94 1.92 1.90 1.88 1.92 1.92 1.86 1.90 1.92 1.94 1.89

0.26 0.08 −0.07 −0.47 −0.50 0.33 −0.26 −0.08 −0.06 0.33 0.55 −0.21

0.367 0.737 0.488 0.595 0.516 0.383 0.673 0.443 0.445 0.535 0.372 0.550

a Here, Ea (eV) is the activation energy barrier, rO−H (Å) is the bond distance of the dissociating O−H bond at the transition state, θHOH (deg) is the H−OH angle at the transition state, Z (Å) is the distance between the center-of-mass of the water molecule and the surface, Er (eV/Å) is the reaction energy, and Fn (eV/Å) is the force experienced by the atom on which H2O dissociates.

Figure 9. Plot of activation energy barriers vs. electronic coupling parameter (β) for various Cu/Ni surface alloy systems.

alloys were excluded in the fitting procedure. Overall, the fits were good for the surface alloys and showed that the increase in d-band center resulted in decrease in activation energies explaining the reactivity trend calculated in this study. However, the deviation observed for Ni2_Cu(111) and Cu1_Ni(111) in their respective plots could not be explained. Similar plots obtained for flat and stepped transition metal surfaces also could not explain the correlation between d-band center and activation energies.63 3.4.4. Electronic Coupling Parameter vs Ea. The descriptors used so far were used previously to explain reactivity of various metal surfaces in the literature. While the d-band center theory was very successful in explaining the change in reactivity in the past and is widely used, surface energy and work function were less successful and not widely used. However, the results discussed in the above three sections show that surface energy and d-band center can capture the trend in reactivity qualitatively, while work function fails as a descriptor. Therefore, herein we have attempted to introduce new reactivity descriptor known as the electronic coupling parameter (β) as described in section 2. This parameter is nothing but the force (Fn from Table 2) experienced by the atom on which H2O dissociates. A plot of Fn vs Ea is shown

Surprisingly, a linear fit to the plots of work function (calculated from the formula) vs activation energy (Figure 7, parts c and d) was good with R2 values of 0.77 and 0.80 for Nibased and Cu-based surface alloys, respectively. A simple empirical relation, based on experiments, predicting a decrease in work function values with increase in Cu concentration on Ni surfaces and the vice versa when Ni concentration increases on Cu surfaces could explain the trends in reactivity for Cu- and Ni-based surface alloys compared to the DFT calculated work function values. Increase in work function is expected to lower the activation energy. However, work function values calculated using both DFT and empirical formula predict a wrong trend in reactivity. These predictions suggest that work function of alloys is not a good descriptor for reactivity. 3.4.3. d-Band Center vs Ea. One of the most promising descriptor used widely for predicting the reactivity trend on metal surfaces using DFT calculations is the d-band center.20 It was previously shown that the d-band center can capture and explain the trends in reactivity of molecules interacting with pure metal surfaces, metal surfaces under stress, bimetallic alloys surfaces, etc.62 Pursuing this, we have plotted d-band center vs activation energy for both Cu- and Ni-based surface alloys in Figure 8, parts a and b. In this plot, the subsurface J


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Figure 10. Plots of Bronsted−Evans−Polanyi (BEP) and transition state scaling (TSS) relationships showing the near linear relation between the barrier heights and the reaction energies for various Cu/Ni surface alloy systems.

Table 3. Energies Used for Transition State Scaling (TSS) and Bronsted−Evans−Polanyi (BEP) Scaling Relationshipsa

a

systems

ETS (eV)

EDiss (eV)

ΔEaDiss (eV)

ΔEDiss (eV)

ΔEaAssn (eV)


1.14 0.87 0.67 0.73 0.61 1.20 0.72 1.02 0.94 1.01 1.24 0.77

0.26 0.08 −0.07 −0.47 −0.50 0.33 −0.26 0.08 0.06 0.33 0.55 −0.21

1.26 1.04 0.84 0.85 0.79 1.31 0.89 1.12 1.04 1.12 1.32 0.86

0.38 0.25 0.11 −0.34 −0.32 0.44 −0.10 0.03 0.16 0.43 0.63 −0.13

0.88 0.79 0.74 1.21 1.11 0.87 0.99 1.09 0.88 0.69 0.69 0.99

The definitions of various quantities are given in section 3.5 in the text.

(Figure 9, parts a and b). A linear fit shows that there is poor correlation of Fn values with the Ea values for Cu-based surface alloys (R2 = 0.10). On the other hand, this relation holds comparatively well for the Ni-based surface alloys (R2 = 0.72). Increase in the force on which the dissociation occurs decreases the barrier to reaction. This force goes to zero when the surface lattice atoms are allowed to relax during the transition state calculations resulting in the puckering of the lattice atom at transition state. In other words, this plot relates the extent to which the surface atom is puckered to the change the barrier heights (Tables S2 and S3). The results on Ni-based surface alloys qualitatively suggest that the increase in the puckering of the surface atoms decreases the activation energy for

dissociation. From these results, it is clearly understood that a strong electronic effect governs reactivity of surface alloys. However, the change in reactivity could not be pinned down to a single (simple) surface based descriptor thereby highlighting the need for a sophisticated surface-based descriptor. Our calculations strongly support the conclusion of the review by Khulbe and Mann36 that no simple relationship was found to exist between the catalytic activity and its electronic properties like work function, percent d-character, DOS at the Fermi level etc. 3.5. Transition State Scaling (TSS) and Bronsted− Evans−Polanyi (BEP) Relationships. Discussion presented in the above section, brought to light the insufficiency of the K


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The Journal of Physical Chemistry C surface based descriptors in explaining reactivity in surface alloys. As a result, we now resort to energy based descriptors to elucidate the change in reactivity calculated in the Cu−Ni surface alloys. Linear energy relations are useful for understanding theoretically the catalytic reactions and helps to reduce the computational effort for performing DFT calculations on large number of systems by providing a quick estimate of reaction barriers. BEP relationship is one of the traditional linear energy relationships which correlates activation energy (ΔEadiss) with reaction energy (ΔEdiss). The reaction energy is defined as ΔEdiss = EFS − EIS, where EFS and EIS are the energies of final (H and OH coadsorbed) state and initial (H2O adsorbed) state and ΔEadiss is the energy difference between EIS and ETS (energy at the transition state). Another alternative form of BEP relation correlates the ETS with EFS which is referred to as a transition state scaling (TSS) relation. The remarkable characteristic of this TSS relationship as shown by the authors of the paper64 is that it is universal for a large number of reactions and can be depicted by a single linear relationship. We have investigated the usefulness of these relationships in our case, i.e., H2O dissociation over different bimetallic surface alloys. As we have two kinds of bimetallic surface alloys, we have shown the correlation by TSS and BEP relationships over these two different bimetallic surface alloys individually. Parts a and b of Figure 10 show TSS relationships for the reaction over all Cu-based and Ni-based bimetallic surface alloys, respectively. Both plots were fitted with straight lines, and using the slope (m) and the intercept (c) values, we have calculated ETS values which are provided in Table 3. The universality of TSS relation is also holds for our systems, and these values can provide a rapid estimate of activation barrier; however, the nature of these two plots is not the same. Plots for Cu-based bimetallic surface alloys show deviation from linearity which gives rise to slightly v-shaped distribution whereas for the Ni-based bimetallic surface alloys, the catalytic reaction shows perfect linear relation but the reason behind this deviation is not clear enough. Parts c and d of Figure 10 show the BEP relationship, i.e., the relation between activation energy and reaction energy for H2O dissociation over Cu-based and Ni-based bimetallic surface alloys, respectively. Natures of these plots are also similar to the TSS plots which imply that the BEP relationship is also universal for H2O dissociation reactions. These types of linear relationships can be further used to calculate the energy barriers for large number of similar systems by simply using the final state and reaction energies and bypassing the transition state calculations. Our results for BEP relationships are consistent with the earlier studies on water dissociation on various transition metal surfaces65 and on bimetallic surfaces27,35 and also with the results for methanol dissociation on bimetallic surfaces.27 3.6. Surface Temperature Effect: Dissociation Probabilities. Semiclassical dissociation (tunneling) probabilities for H2O on different Ni- and Cu-based surface alloys were calculated for different incident energies, and they are plotted in Figure 11, parts a and b. These dissociation probabilities are corrected for lattice motion by including the effects of both the electronic (β) and mechanical coupling (α) parameters (Figures S2−S5 in the Supporting Information). The electronic coupling parameter, β values are higher on Ni atoms because at transition state, dissociation of H2O molecules occurs mostly on the top site. Whereas, on Cu atoms the transition state H2O dissociates away from the top site. The probability values are

Figure 11. Dissociation probabilities for H2O on (a) Ni-based and (b) Cu-based Ni−Cu bimetallic surface alloys at 300 K. Rigid surface reaction probabilities are calculated within semiclassical approximation and the effect of lattice motion is included using the sudden model.

cut off at the incident energy corresponding to the barrier height because these calculated values are tunneling probability which occurs only below the barrier. The individual effects of electronic and mechanical coupling parameters on tunneling probabilities for a certain surface (Cu2_Ni(111)) are illustrated (Figure S6 of Supporting Information). Individually, the electronic coupling parameter, which accounts for the change in barrier heights with lattice atom motion leads to increase in probabilities at all incident energies. On the other hand, the mechanical coupling, which explains the recoil effects due to incoming H2O molecule, decreases the reaction probabilities at higher incident energies. Overall, due to an increased lattice coupling, some of the pathways have lower effective barriers and thus become more reactive at higher substrate temperatures i.e., higher dissociation probabilities are obtained for lower incident energies. It is to be noted that though this model is approximate, using only data computed for the TS, it illustrates how the lattice effects can give an effective barrier height lower than the values obtained from a rigid surface DFT calculation. Dissociation probabilities for H2O on Ni- and Cu-based surface alloys at 0, 100, 300, and 500 K for various Cu- and Nibased surface alloys are plotted (Figure S7 and S8 of Supporting Information). In all cases, the dissociation L


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experienced by the atom on which water dissociates. But this descriptor completely failed in the case of Cu-based surface alloys. Reaction energy based transition state scaling (TSS) and Bronsted−Evans−Polanyi (BEP) relations were calculated for these surface alloys and found that the activation energy barriers calculated from these relations are in good agreement with the values calculated from DFT proving the universality of these relations. Our calculations found that the energy based descriptors were superior compared to the surface based reactivity descriptors for H2O dissociation on Ni−Cu surface alloys. Surface temperature effects were introduced by including the electronic (β) and mechanical (α) coupling parameters using the “sudden model”. Plots of dissociation probabilities vs incident energy revealed that on all surfaces (surface alloys and subsurface alloys), an increase in surface temperature increases reactivity. Overall, the presence of Ni in Cu(111) surfaces decreased the activation energy barriers for reaction while the presence of Cu in Ni(111) resulted in increase in reaction energy barriers. Among the surface studied, Ni4_Cu(111) showed the lowest barrier for H2O dissociation followed by Ni2_Cu(111). Barrier energies calculated on Nix_Cu(111), where x = 1−4, were lesser than the barrier energies calculated on Cux_Ni(111), where x = 1−4, surfaces. However, factor governing the reactivity of these surface alloys could not be pinned down to a specific electronic effect which necessitates further exploration for descriptors. Nonetheless, based on energetics, among the Cu−Ni surfaces, both monolayer and 0.5 monolayer coverage of Ni on Cu(111) surfaces are beneficial in decreasing the barrier for H2O dissociation and can be regarded as potential candidates for a low-temperature water gas shift reaction. Further kinetic calculations will be required to suggest a good catalyst for this reaction.

probabilities increased with increasing temperatures as observed in the earlier studies.66,67 Therefore, the temperature of 300 K was chosen to explain the trend in reactivity for H2O dissociation with the inclusion of surface temperature effect (Figure 11). Among the Ni-based alloys, pristine Ni(111) surface shows the highest reactivity followed by subCu4_Ni(111) suggesting that the substitution of subsurface Ni atoms by Cu does not help in dissociation of H2O when compared to pure Ni(111). Similar observation was found when Cu atoms were present in the subsurface layer of the Pt(111) surface.26 It is worth noting that Pt and Ni belong to the same group of the periodic table and the effect of Cu in the subsurface layer of these two metal (111) surfaces have a similar effect. Among the Ni-based bimetallic surface alloys, Cu2_Ni(111) exhibited the highest reactivity. Cu1_Ni(111) and Cu3_Ni(111) surface showed similar reactivity suggesting that reactivity has little dependence on the nature of neighboring atoms. However, surface alloy with all four surface Ni atoms replaced by Cu showed the lowest reactivity among the Ni-based surface alloys. On contrast to Ni(111) and sub_Cu4_Ni(111), Cu(111) and sub_Ni4_Cu(111) were the least reactive among the Cu-based surface alloys. The reactivity trend exhibited by Cu-based surface alloys is as follows: Ni4_Cu(111) > Ni2_Cu(111) > Ni3_Cu(111) > Ni1_Cu(111). Substitution of Cu by Ni in Cu(111) surface proved to be beneficial in decreasing the barrier for H2O dissociation. Compared to Cu-based surface alloys, Cu4_Ni(111) surface is even less reactive than pristine Cu(111) and also sub-Ni4_Cu(111). Furthermore, this surface exhibited the lowest reactivity among all the surfaces studied. From these results few aspects are apparent: (i) substituting Cu by Ni on a Cu(111) surface shows lower barrier and higher reactivity for H2O dissociation compared to substituting Ni by Cu on Ni(111), (ii) 100% coverage of Ni or a full monolayer coverage of Ni shows a lower barrier for H2O dissociation compared to so far reported 50% Ni coverage on both Ni(111) and Cu(111) surfaces suggesting that Ni need not be sparsely distributed30 for the H2O dissociation to take place From the above discussion, it is concluded that alloying Ni in Cu surfaces is more beneficial in H2O dissociation compared to alloying Cu in Ni surfaces.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcc.7b04637. Change in barrier heights with lattice atom motion, comparison between the barrier energy values calculated by DFT and the ones predicted by TSS and BEP relations, initial, transition, and final state geometries, plots used to calculate mechanical coupling (α) and electronic coupling (β) parameters, and the effect of surface temperature on the reactivity of individual systems (PDF)

4. CONCLUSIONS Water dissociation on various Cu- and Ni-based surface alloys with varying concentration of the alloying metals (Ni and Cu) was studied using DFT calculations. Change in surface properties such as surface energies, work function, and density of states induced by alloying metal atoms were calculated. Inclusion of Ni into Cu(111) lattice affected the surface properties positively and suggested a linear increase in reactivity with increasing Ni atoms. On the other hand, these properties suggested a decrease in reactivity with the increase in Cu atoms in the Ni(111) lattice. However, activation energies calculated from the transition state calculations did not show a linear increase or decrease in reactivity on any of the studied series of surface alloys. Although the surface-based descriptors were able to describe the variation in reactivity qualitatively, they were quantitatively insufficient. In addition to the usual descriptors, a new descriptor, which is quantified by the force on atom on which H2O dissociates or the electronic coupling parameter in the “sudden model”, is also used to explain the trend in reactivity. For Ni-based surface alloys, this descriptor predicted a decrease in activation energy with increasing force

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (A.K.T). ORCID

Ashwani K. Tiwari: 0000-0002-7083-7709 Author Contributions §

These authors contributed equally to this work.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS H.S. and A.K.T. sincerely acknowledge the Science and Engineering Research Board (SERB), New Delhi, India, for funding through Project No. EMR/2015/001337. M


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