PtâNi Subsurface Alloy Catalysts: An Improved Performance toward

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C: Surfaces, Interfaces, Porous Materials, and Catalysis

Pt-Ni Subsurface Alloy Catalysts: An Improved Performance Towards CH Dissociation 4

Sudipta Roy, Seenivasan Hariharan, and Ashwani Kumar Tiwari J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b01705 • Publication Date (Web): 30 Apr 2018 Downloaded from http://pubs.acs.org on May 2, 2018

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The Journal of Physical Chemistry

Pt-Ni subsurface alloy catalysts: An improved performance towards CH4 dissociation Sudipta Roy, Seenivasan Hariharan, and Ashwani K. Tiwari∗ Department of Chemical Sciences, Indian Institute of Science Education and Research, Kolkata, Mohanpur 741246, India E-mail: [email protected]

∗ To

whom correspondence should be addressed

1

ACS Paragon Plus Environment

The Journal of Physical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Abstract Methane dissociative chemisorption is the rate-determining step (RDS) in the industrially important steam reforming and dry reforming reactions of methane. Widely used industrial catalysts containing Ni as the active metal faces the problem of carbon deposition and deactivation, whereas Pt surfaces with lower barrier are expensive to be used in the industrial scale. Using density functional theory (DFT) calculations, a series of surface and subsurface Ni-Pt bimetallic surfaces were studied to understand the synergistic catalytic activity of alloying elements towards facilitating methane dissociation and in resisting carbon formation. Addition of Ni to Pt(111) decreased activation energy barriers, whereas a linear increase in barrier was found when Pt is added to Ni(111) surface. Observed reactivity trends were explained using surface-based descriptors like work function, surface energy and d-band center and also using energy based descriptors namely, Bronsted-Evans-Polanyi (BEP) and transition state scaling (TSS) relationships. Changes in barrier heights and locations of the barrier with lattice atom motion were calculated to include the effect of surface temperature on dissociation probabilities. Dissociation probabilities thus calculated at different surface temperatures using semiclassical methods showed that reactivity increased with surface temperature on all surface alloys. Overall, two surfaces viz., Ni9/Pt(111) and sub-Pt9/Ni(111), showed improved behavior towards CH4 dissociation, irrespective of the composition of underlying layers. C2 formation on these two alloys also showed higher barriers compared to pure NI(111) surface. However, considering all aspects like the energy barriers to CH4 dissociation, and CH dissociation, carbon adsorption energy, and the cost, the subsurface alloy, sub-Pt9/Ni(111) showed an enhanced overall performance as a reforming catalyst.

Introduction One of the major ingredients of natural gas, methane, plays a crucial role in hydrogen (H2 ) production in a large scale. Typical reactions that produce H2 gas from methane are steam reforming of methane (SRM), 1,2 dry (CO2 ) methane reforming (DRM), 3 partial oxidation of methane 4 etc. SRM is the primary process in the production of synthesis gas (CO + H2 ) or H2 gas industrially, 2


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on a large scale and always couples with another important reaction called the water gas shift reaction. 5,6 In these reactions, the primary requirement is dissociative chemisorption (DC) of molecular CH4 over metal catalysts. 7–9 DC of methane proceeds via physisorption of gaseous methane on the metal surface, followed by dehydrogenation of four hydrogen atoms, one by one. Among these dehydrogenation steps, the first dehydrogenation, i.e., CH4 → CH3 + H is kinetically most significant and considered to be the rate limiting step. For both SRM and DRM, Ni-based catalysts are primarily used in industries, due to the low cost and high reactivity. 10 However, formation of coke on these surfaces leading to catalyst deactivation has been a serious bottleneck for the past several years. 11,12 Owing to the greater tunability in reactivity and flexibility in choice of composition, bimetallic catalysts are subjected to extensive scrutiny in the present day literature pertaining to surface science and heterogeneous catalysis. 13–22 In this line, modification of Ni catalysts with small amount of noble metals has been demonstrated to be a promising approach to design reactive and coke resistant catalysts for methane reforming. 23,24 Inclusion of noble metals to Ni catalysts, in addition to stabilizing and promoting the reducibility of Ni, helps modify the ensemble size of Ni, block step sites and to alter the surface electronic properties of the Ni catalysts. 25 A classical case of this scenario has been presented for Au incorporated Ni surface alloys which was active for steam reforming and more resistant towards carbon formation. 26 Although addition of Au to Ni increased the barrier for CH4 dissociation, it lowered the ability of C adsorption, thereby reducing coke formation. Similarly, increasing metallic dispersion of Ni in different transition metals, such as Ag, 3 Au, 6 Pt, 27 Cu, 28 Ru, 29 Rh, 30 and Pd 31 is shown to be effective in reducing coke formation. Among the above transition metals, Pt is more effective for coke resistance, which is verified both experimentally 27,32,33 and theoretically. 34,35 In addition, Pt(111) shows lower activation energy barrier (0.928 eV) compared to Ni(111) (1.065 eV), 36 which shows that Pt(111) is more reactive for methane dissociation than Ni(111). 37 However, the cost of platinum prohibits its usage in its pure form as a catalyst in SRM and related processes, for industrial purposes. This remains the motivation behind the search for a catalyst which combines the desirable properties

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of both Pt and Ni, in right proportion, resulting in a more effective catalyst for reaction involving methane dissociative chemisorption and resisting coke formation. Although, numerous experimental 38–43 and theoretical 44–48 studies have been performed to understand the atomistic details of the mechanism of DC of methane on various catalytically relevant monometallic surfaces, only limited number of studies are reported for methane DC on Pt-Ni bimetallic alloys. On the experimental front, activity tests on alumina supported Pt-Ni catalysts found that these catalysts were less sensitive to coke deposition and more stable under CO2 reforming conditions. 27,32,49–51 Enhancement in the catalytic activity, selectivity and catalyst stability of these bimetallic catalysts is attributed to the interaction between Pt-Ni metallic centers. It was reported that carbon formed during the reaction is less strongly bound to Ni particles interacting with Pt, leading to easier gasification of CO. It was also shown that the alloy surface enriched with Pt with small crystallite size possesses higher reactivity and low production of carbonaceous materials upon dry reforming of methane. 52 Similarly, Ni-Pt binary nanoparticles encapsulated in hollow silicates were shown to enhance CO2 reforming and coke resistance. 53 Overall, the addition of Pt is found to be beneficial for dry reforming of methane by facilitating CH4 dissociation and inhibiting coke formation. However, the mechanistic details still remain unclear. On the theoretical front, density functional theory (DFT) has been widely used to study the reaction mechanism of CH4 dissociation on Ni-Pt bimetallic surfaces. A comparative DFT study of CH4 dissociation on Ni(111) and NiPt(111) surfaces showed that CH4 and CH3 dissociation reactions are easily realized on NiPt(111) compared to Ni(111). 54 It was also reported that, CH → C + H is the rate-limiting step on NiPt(111). In another study, it has been found that, with Pt as an doped metal with Ni, as a catalyst, the activation energy is increased remarkably for the last step of the dehydrogenation of methane, i.e., CH → C + H. 35 On a stepped Ni surface, it was found that substituting the subsurface atoms with other elements can dramatically change the reaction mechanism of methane decomposition. 55 Out of all the 3d, 4d and 5d metals substituted, substitution with Pt on the step site showed the weakest carbon adsorption. The enhanced catalytic activity of bimetallic surfaces are, in general, attributed to ensemble ef-

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fect, ligand effect, and to the interplay between electronic and geometric effects. 34,56–58 Although, many surface based descriptors like surface energy, work function, d-band center etc., were proposed to explain the reactivity of bimetallic catalysts, none were found to be universal i.e., could explain the reactivity of all molecules on all combination of metals. Among the surface based descriptors, d-band center theory has been robust enough to capture the contribution of aforementioned effects in the reactivity of bimetallic alloy surfaces but is far from complete. 59 On the other hand, energy based descriptors like the Bronsted-Evans-Polanyi (BEP) and transition state scaling (TSS) relationships performed well for reactions on bimetallic catalysts. 60 Due to the limited atomistic level understanding, lack of accurate (universal) descriptors to describe the activity of bimetallic catalysts, and to understand the effects of surface temperature on reactivity of bimetallic surface alloys, herein, we study methane dissociative chemisorption on various Pt-Ni bimetallic surface alloys. Objectives of this work are as follows: (i) to find and propose the optimum composition of the Ni-Pt surface alloy which reduces the energy barrier of the very first step of methane dissociation i.e., CH4 → CH3 +H, and reduces coke formation, (ii) to correlate the reactivity change with surface based descriptors using first principles methods. The optimization of alloy surfaces will be carried out considering the advantages and limitations of Ni and Pt monometallic surfaces towards methane dissociative chemisorption. In addition, we study the effect of surface temperature on reactivity and compare them with the results obtained on mono metallic surfaces and on rigid surfaces. Herein, we have used DFT to calculate adsorption energies, energy barriers, etc., and semiclassical methods coupled with ‘sudden model’ 36,61,62 to calculate dissociation probabilities at elevated temperatures for methane DC on all bimetallic surface alloys.

Computational Methods All total energy calculations were performed by using DFT based Vienna ab-initio simulation package (VASP). 63–66 Non local exchange-correlation effects are treated using plane wave basis set and Perdew-Burke-Ernzerhof (PBE) 67,68 exchange-correlation functional within generalized

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gradient approximation (GGA). Recent studies pertaining to high dimensional potential energy surfaces (HD-PES) have shown that the conventional PBE or RPBE functional do not predict accurate barrier heights for methane dissociative chemisorption. Alternatively, a newly developed specific reaction parameter (SRP) functional including the treatment of dispersion has proven to be more reliable. 46,69 Although SRP functional provides highly accurate barriers for methane dissociative chemisorption, using these functionals may not qualitatively change the conclusion of this work. Interaction between the ionic cores and electrons are expressed by fully non local optimized projector augmented wave (PAW) 70,71 potentials. Spin polarized calculations have been performed with the plane wave expansion truncated at 400 eV. Metal surfaces were modelled as asymmetric slab supercell model with periodic boundary conditions. Ni(111), Pt(111) and all the other bimetallic surfaces and sub-surfaces consist of four layers within 3 × 3 unit cell. A large vacuum space, corresponding to almost six layers (approx. 18 Å) have been used to avoid any interaction between a surface and its repeated image along the z-direction. Equilibrium lattice constants for Ni and Pt, 3.52 Å and 3.97 Å, respectively, found from the bulk geometry optimization in VASP are used for all the calculations. For bimetallic surface alloys, the lattice constants of the host metal were used. 3 × 3 × 1 Γ centred grid of k-points were used for structure optimization. All the atoms were allowed to relax during optimization and the calculations are considered to be converged when the forces on all atoms are smaller than 0.01 eV/Å. Climbing image nudged elastic band (CI-NEB) method 72 has been used for identifying the transition state geometries. for which the converging criteria is when all the forces are less than 0.05 eV/Å. Adsorption energy was calculated using the expression, Eads = E(adsorbate+sur f ace) − [Eadsorbate + Esur f ace ], where Eads , E(adsorbate+sur f ace) , Eadsorbate and Esur f ace are the adsorption energy, energies of the adsorbed systems, metal slab and the molecule in the gas phase respectively. During calculations of adsorption energies of H, CH3 or CH4 and reaction paths all the metals atoms were kept frozen. However, for different molecules on metal surfaces, inclusion of lattice atom motion in calculations has been shown to change the activation energy barrier and increase reaction probability with higher surface temperature. 45 A simple, successful and physically mean-

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ingful model known as ‘sudden model’ 36,61,62 is used to include the effect of lattice motion. In this model, two linear parameters, α (mechanical coupling) and β (electronic coupling), which are defined by ∆Ebarrier = −β ∆Q and ∆Zbarrier = α∆Q are calculated. Here, ∆Ebarrier and ∆Zbarrier

Figure 1: Construction of Pt-based subsurface alloys from a pure Pt(111) metal (host) surface by replacing top layer atoms by Ni (guest) metal atom (SIDE and TOP views). From (a) to (h) the surfaces are Bare Pt(111), Ni1/Pt(111), Ni3/Pt_side(111), Ni3/Pt_middle(111), Ni6/Pt(111) and Ni8/Pt(111), Ni9/Pt(111) and Sub-Ni9/Pt(111) respectively. are change in barrier height and change in location of transition state, respectively, with change in lattice atom position from its equilibrium position (Q = 0). Q is the lattice degree of freedom perpendicular to surface which is chosen to vary a maximum of 0.2 Å both upwards and downwards from its equilibrium position (Q = 0). Further details of the sudden model is provided in Section S1 of Supplementary Information and can also be found elsewhere. 73,74 Assuming that the metal atom of mass M moves harmonically with a frequency Ω at a given surface temperature T , for a given incident energy E, the temperature dependent reaction probability becomes, s Z ∞

Pr (E; T ) =

eb(E−Eb +β Q)

−∞

! MΩ2 MΩ2 Q2 exp − dQ 2πkT 2kT

(1)

2π , ω15 is the imaginary frequency obtained during transition state calculations. h¯ |ω15 | Reaction probability, Pr (E; T ), thus obtained is dependent only on the electronic coupling parame-

Where, b =

ter β . This is further improved by including, α i.e., mechanical coupling, by averaging over lattice atom momentum using the following form

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s

Z

S(E; T ) =

dEcm

" Ms0 M0 exp − s 4πkT µT Ecm 2kT

s

2Ecm − µT

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r

2E M

!2 # Pr (E; T )

(2)

Here, Ecm stands for center-of-mass energy of the incoming molecule and Z and Q coordinates are transformed to a relative coordinate Z 0 = Z −αQ and a corresponding center-of-mass coordinate, 75 Ms0 M , where thus reduced mass corresponding to the relative collision coordinate Z 0 is µT = (Ms0 + M) Ms Ms0 = 2 . α For this study, two types of bimetallic surface alloys, viz., Ni-based and Pt-based with various surface compositions and therefore different electronic structure were constructed. Ni-based alloys were constructed by replacing surface Ni atoms by Pt atoms and Pt-based alloys were constructed by replacing surface Pt atoms by Ni atoms resulting in total 7 Ni-based and 7 Pt-based surface alloys (including a sub-surface alloy in each case) as shown in Figure 1. Further details on the construction, atom replacement and the nomenclature of the sites can be found in Section S2 of Supplementary Information .

Results and discussion Surface properties: Work function, surface energy and d-band center calculations Surface properties such as work function, surface energy and d-band center were calculated to understand the catalytic activity of Pt-Ni bimetallic surface alloys towards CH4 dissociative chemisorption. These properties are then used to explain the trends in adsorption and dissociation energies of CH4 and also to explain trends in activation energy for CH4 dissociative chemisorption on the surface alloys. Work function is defined as the amount of energy required to remove an electron from surface of a given metal to a point outside the material i.e., the vacuum. Whereas, surface energy is defined as the amount of energy needed to cleave an infinite crystal into two parts, i.e., energy required to form a new surface. Formula to calculate work function and surface energy are pro8


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5.6 Ni-based

(a)

Pt-based

Work function (eV)

5.4

5.2

5.0

4.8

4.6

4.4

4.2 Sub-B9A

Pure A

B1A

B3A_S

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B6A

B8A

B9A

Systems

9

Ni-based

(b)

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Surface energy (eV/atom)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


8 7 6 5 4 3 Sub-B9A

Pure A

B1A

B3A_S

B3A_M

B6A

B8A

B9A

Systems

Figure 2: Plots of trends in surface energies and work function for different Ni or Pt-based alloy systems. A can either be Ni(111) or Pt(111), i.e. Pure A can either be pure Ni(111) or pure Pt(111). For Pt-based alloys (solid circles), A is Pt and B is Ni while for Ni-based alloys (solid squares) the reverse is true. BnA (n=1,3,6,8 and 9) corresponds to eight surface alloys with different guest metal concentrations. Letters S and M in the two configurations corresponding to three atom substituted surface alloys refer to replacement of ‘side’ and ‘middle’ atoms. 9 ACS Paragon Plus Environment


vided in the Supporting Information at page S3. Plots showing work function and surface energy for various Pt-Ni surface alloys are given in Figure 2a and 2b, respectively (values in Table S6). On Ni-based surface alloys, work function for Pt substituted alloys are higher compared to that calculated on pure Ni(111) surface, with the sub-surface alloy showing the highest value. On the other hand, the work function values decreased with increasing Ni content in the Pt-based surface alloys wherein the surface alloy with highest concentration of Ni showed lowest work function. For Ni based surface alloys, a significant jump in the work function values was observed when the Pt concentration increases from 3 to 6 atoms, while similar jump was observed when the concentration of Ni increased from 6 to 8 atoms, on Pt-based alloys. Beyond this concentration, in both systems, work function values changed little, until complete surface coverage of alloying element is achieved. A slow decrease in surface energy with increasing Pt content was calculated for Ni-based systems, up to 6 Pt atoms. Further increase in Pt resulted in increase in surface energy with Pt9/Ni(111) showing the largest value among surface alloys. However, it is to be noted that the sub-surface alloy showed the highest value among all the Ni-based alloys. A steady increase in surface energies with increasing Pt content was observed for the Pt-based surface alloys, reaching a maximum value for Ni9/Pt(111). It is interesting to note that for Ni- and Pt-based surface alloys with similar amount of alloying element, the surface energies lie within 0.5 eV/atom for most of the systems, with Ni alloyed Pt-surface alloys showing higher energies compared to Pt-based alloys. In addition, both Ni9/Pt(111) and Pt9/Ni(111) showed similar surface energies indicating similar reactivity. Generally, metal surfaces with small work function and large surface energy values are considered to be more reactive. While, in general, higher surface energy can be related to higher reactivity, it also means that the surface can be unstable at under actual reaction condition. Therefore, one needs to be careful when the choice of the catalyst is made solely based on the surface energies. Along these lines, from work function calculations, it can be predicted that among Ni-based alloys, pure Ni(111) should be the most reactive, whereas among Pt-based alloys, Ni9/Pt(111)

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should be more reactive. Similarly, comparing surface energies, both Pt9/Ni(111) and Ni9/Pt(111) are predicted to be highly reactive while sub-surface Pt9/Ni(111) cannot be excluded.

Figure 3: Plots of density of states for different (a) Ni-based and (b) Pt-based alloys, with the corresponding d-band center values given in each plot. An important parameter that reflects the changes in electronic structure induced by alloying, besides work function and surface energy, is the d-band center. 59 d-band center is a parameter that correlates with the extent of filling of the antibonding (d-σ )∗ molecular orbitals between surface d-states and the adsorbate valence states. The strength of the bond resulting from such interaction is given by the energy of antibonding states relative to Fermi level. Higher energy of d-states rel-

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ative to Fermi level (empty antibonding states) facilitate the formation of stronger bond whereas, lower energy of d-states (filled antibonding states) indicate formation of weaker bond with the metal surface. The shift in the d-band center values from pure Ni(111) and Pt(111) surfaces due to alloying is calculated from density of states (DOS) plots (Figure. 3a and 3b). For pure Ni(111) surface, states are more populated near the Fermi level, with the d-band centered at -1.53 eV. Substitution of Ni by one Pt atom lowered the population near the Fermi level and d-band center’s energy decreases to -1.64 eV. As we increase the concentration of Pt on Ni, the population gradually shifts from Fermi level to the lower energy side, resulting in further decrease of d-band center energy values with d-band center located at -2.14 eV for Pt9/Ni(111). However, d-band center value is highest for sub-surface Pt9/Ni(111) alloy (-1.28 eV) among all Pt substituted Ni alloys, indicating this sub-surface alloy can be the most reactive for dissociative chemisorption of methane. In case of Pt-based alloy systems, increasing Ni concentration on the surface, shifts the maxima of the DOS plot gradually towards the Fermi level thereby shifting the d-band center towards the positive side with the highest value of (-1.37 eV) for Ni9/Pt(111). This trend indicates an increase in reactivity with the increasing concentration of Ni on the surface of Pt-based surface alloys. For subsurface-Ni9/Pt(111) system, d-band center is lowest compared to any of the Ni on Pt surface alloys, indicating that this could be the least reactive surface alloy for CH4 dissociative chemisorption among the alloys studied.

CH4 , H, CH3 adsorption and H + CH3 coadsorption CH4 adsorption: Adsorption of CH4 on pure metal surfaces and surface alloys was studied on specific adsorption sites to understand the effect of surrounding atoms on the adsorption site under study. On all surfaces (pure and alloy), adsorption of methane was studied only on the top site because it is well established that methane adsorption takes place only on top site on many metal surfaces. 76,77 Adsorption energies for CH4 on various alloy surfaces are shown in Figure. 4a. Methane adsorption is found to be very weak on the surfaces studied with adsorption energies as low as -0.01 eV. In all cases, distance of the methane molecule over which it adsorbs is more than 12


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0.00

-2.0

Ni-based

CH

Pt-based

4

Adsorption

Ni-based

H Adsorption

Pt-based

-2.4

ads

(eV)

-0.01

E

E

ads

(eV)

-2.2

-2.6

-0.02 -2.8 (b)

(a)

-0.03

-3.0 Sub-B9A

Pure A

B1A

B3A_S B3A_M

B6A

B8A

B9A

Sub-B9A Pure A

-1.0

B1A

B3A_S

B3A_M

B6A

B8A

B9A

-2.8

Ni-based

CH

Pt-based

3

Adsorption

Ni-based

H+CH

3

Coadsorption

Pt-based

-1.2

-3.2

(eV)

-3.6

ads

-1.6

-1.8

-4.0

E

ads

(eV)

-1.4

E

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


-4.4 -2.0 -4.8

-2.2

(d)

(c)

-5.2

-2.4 Sub-B9A

Pure A

B1A

B3A_S B3A_M

B6A

B8A

Sub-B9A Pure A

B9A

B1A

B3A_S

B3A_M

B6A

B8A

B9A

Systems

Systems

Figure 4: Plots of H, CH3 , CH4 adsorption and H + CH3 coadsorption energies on different Ni/Pt surface alloys. The nomenclature of the systems in the x-axis is same as Figure 2. 3.61 Å, from which it can be concluded that methane only physisorbs on Ni-Pt surface alloys. However, for H and CH3 adsorption, many adsorption sites are possible on the surface alloys (Fig. 1). Only the results for the most stable sites are discussed in the manuscript. H adsorption: H adsorption calculations on both Ni- and Pt-based surface alloys showed that H is strongly adsorbed at the hollow sites i.e., either in f cc or in hcp site. Variation in adsorption energies of H on both Ni- and Pt-based alloy systems is shown in Figure 4b. In case of Nibased alloy surfaces, as we increase the concentration of Pt metal on the Ni surface, adsorption energy decreased. But for subsurface Pt9/Ni(111) system, it has the highest adsorption energy (-2.93 eV), even higher than that calculated on pure Ni surfaces (-2.8 eV). On the other hand, on Pt-based alloy surfaces, as evident from the adsorption energies, increasing substitution by 13



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Ni, favours H adsorption. Adsorption energy on Ni9/Pt(111) is the highest (-2.94 eV) while subsurface Ni9/Pt(111) showed lowest adsorption energy (-2.46 eV). In case of alloy systems, where there are more than one metal atoms on the surface, hollow sites i.e., f cc or hcp sites could be of different kinds. Like, e.g. in case of Pt3/Ni_side(111) alloy, f cc sites are of two kinds. One is created by three Ni atoms and the other is by two Pt atoms and one Ni atom. These two f cc sites are called as Ni3 site and Pt2Ni site. In case of bare Ni(111), H adsorbs strongly at the f cc site. In case of Ni-based alloys, it has been found that H adsorb strongly on the f cc site, that are formed by higher number of Ni atoms. Except for the case of Pt6/Ni(111), where H adsorb more strongly at Ni2Pt hcp site. In case of bare Pt(111) H adsorb strongly on top site. But when Ni is introduced to make alloy surfaces, it has been found that H adsorb strongly at the f cc site formed by higher number of Ni atoms in each case as the above. CH3 adsorption: Similar to H adsorption, on Ni-based surface alloys, adsorption energy of CH3 decreased with increasing substitution with Pt atom with sub-surface Pt9/Ni(111) and Pt9/Ni(111) exhibiting the highest and lowest adsorption energies, respectively, among Ni-based surface alloys. For Pt-based alloy systems the trend is opposite, except for the first substitution. Substitution of one Ni atom at the center of the surface decreases adsorption energy, which then starts increasing with increasing Ni concentration on the surface to reach the largest value (-2.25 eV) for Ni9/Pt(111) alloy surface. Subsurface Ni9/Pt(111) has the lowest adsorption energy value for CH3 (-1.53 eV). On Ni(111), CH3 adsorbed on f cc site and for bare Pt(111) it is adsorbed at the top site. In case of Ni-based alloy surfaces, CH3 adsorbed at the f cc sites same as that of H adsorption discussed above. Exception is found for Pt6/Ni(111) alloy, where CH3 adsorb on the top site of substituted Pt atom. In case of Pt-based alloys CH3 adsorb strongly at the f cc site formed by substituted Ni atoms in each case. H + CH3 coadsorption: Coadsorption of H and CH3 is treated as the final state during the transition state calculations of CH4 dissociative chemisorption. Trends in adsorption energy is similar for both CH3 adsorption and H + CH3 coadsorption, (Figure. 4c and 4d) Transition state calculations were performed using these most stable co-adsorbed sites as final states, whose energy

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values are listed in Table S1 of Supplementary Information. But two exceptions are there. This is due to the fact that in these two cases, using most stable coadsorbed state as final state for transition state calculation, did not lead to any proper transition state. One is for Pt1/Ni(111) system, where the most stable final state is for both CH3 and H are adsorbed on the hollow sites. Energy for this state is -4.51 eV. Whereas for transition state calculation, final state is CH3 adsorbed on top site of Pt and H is on hollow site. Same is the case for Ni3/Pt_middle(111) alloy. Here most stable coadsorbed state is CH3 on top site of a Pt atom and H is on hollow site. Energy for this coadsorbed state is -4.79 eV. But for transition state calculation, CH3 is on top site of a Ni atom and H is on the same hollow site as before. The energy difference between the most stable coadsorbed site and the one which is considered for TS calculation is quite significant (0.49 eV).

Activation energy Activation energies for CH4 dissociative chemisorption on Ni-based and Pt-based surface alloys obtained from transition state calculations using CI-NEB method are plotted in Figure 5. Activation energies and other important parameters calculated are enlisted in Table S7 of Supplementary Information. A linear increase in activation energy with increasing concentration of Pt is found for the Nibased surface alloys. On the other hand, no linear increase or decrease in activation energy with increasing Ni concentration on the surface was found on Pt-based surfaces. Geometry of transition state strongly depends on the alloyed metal atom. Images of initial, transition, and final states are provided in Fig. S2, S3 and S4 of Supplementary Information. On Ni-based surface alloys, activation energies for all surface alloys were higher than that calculated on Ni(111), whereas Ea values were lower than Pt(111) for Ni alloyed Pt surfaces. Among the sub-surface alloys, sub-Pt9/Ni(111) showed lower Ea compared to Ni(111) while sub-Ni9/Pt(111) showed higher Ea compared to Pt(111). In both cases, having three alloying atoms on the side showed lower barrier compared to having alloying element on the middle of the surfaces. Activation energy barriers calculated in this work agree well with the previous work that are available for methane dissociation 15



2.0 Ni-based Pt-based

1.8

a

(eV)

1.6

E

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1.4

1.2

1.0

0.8

0.6 Sub-B9A

Pure A

B1A

B3A_S

B3A_M

B6A

B8A

B9A

Systems

Figure 5: Change in activation energy barriers with composition of surface for different Ni- and Pt- based surface alloys. The labels on the x-axis are same as in Fig. 2.

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on bare Ni(111), bare Pt(111) 36 and Pt-Ni alloys, i.e. Ni-based alloy system for the step CH4 → CH3 + H. 35 Comparison of our results on Ni-based surface alloys with that of Niu et al., 35 on alloy surfaces revealed that there is a significant variation in activation energy barrier only when the composition of the surface (top layer) is varied and not when the composition of the other layers are varied. From these studies, it is understood that addition of Pt to Ni surface increases the barrier to CH4 dissociation while addition of Ni to Pt surface can be beneficial for CH4 dissociation by reducing the barrier. Descriptors help in predicting activation energy barriers bypassing DFT calculations. In the following section, the change in the activation energies for Ni-based and Pt-based surface alloys will be explained and understood in terms of three different surface based properties namely, work function, surface energy and d-band center and and two different energy based relationships, namely, Bronsted-Eyring-Polanyi (BEP) and transition state scaling (TSS) relationships as descriptors. The capabilities and limitations of these descriptors will be discussed in detail in the following sub section.

Work function vs. Activation energy Work function, an important qualitative descriptor of the reactivity is plotted against the activation energies for different surface alloys (Figure 6a and 6b.). Since subsurface alloys showed an opposite behavior compared to surface alloys, for both the alloy systems, these values were excluded from the plots. With increasing concentration of Pt on Ni(111), a linear correlation is found between work function and activation energies with the linear regression fit showing R2 value of 0.84. However, the fit to the Ea vs. work function plot for Pt-based surface alloys is not as linear as seen for Ni-based alloys (R2 = 0.39). Among Pt-based alloy surfaces Ni3/Pt_side (111) and Ni6/Pt(111) deviate more from the fitted line compared to bare Pt(111) and other alloys. Similarly, among Nibased surface alloys, Pt6/Ni(111) and Pt9/Ni(111) fall away from linearity. Among the subsurface alloys, sub-Pt9/Ni(111) with highest work function value (4.71 eV) falsifies the general prediction by exhibiting lowest barrier CH4 dissociation. This, however, requires validation by other descrip-

17



2.0

0.95

2 R =0.8345

2 R =0.3903

Pt9/Ni(111)

1.8

Ni6/Pt(111)

Bare Pt(111)

0.90

Pt3/Ni_middle(111)

0.85

E

a

1.4

E

a

(eV)

Pt6/Ni(111)

(eV)

Ni3/Pt_middle(111)

1.6

0.80

Pt3/Ni_side(111)

1.2 Pt1/Ni(111)

0.75

1.0 Bare_Ni(111)

(a)

Ni8/Pt(111)

4.40

4.45

4.50

4.55

4.60

4.9

4.65

5.0

5.1

1.50

5.3

5.4

2 R =0.8255

Sub-Ni9/Pt(111)

1.2

(eV)

Pt3/Ni_side(111)

1.0 Bare_Pt(111)

E

a

E

a

1.20

Ni6/Pt(111)

Pt1/Ni(111)

Ni3/Pt_middle(111)

1.05

0.8 Ni9/Pt(111)

Ni3/Pt_side(111) Bare_Ni(111)

Ni8/Pt(111)

(c) 0.90 5.1

5.2

5.3

5.4

5.5

5.6

5.7

5.8

3.6

4.5

5.4

2 R =0.8690

Pt9/Ni(111)

1.2

(eV)

Pt6/Ni(111)

1.6

Pt3/Ni6_middle(111)

a

1.4

1.0

E

a

(eV)

7.2

2 R =0.8305

Sub-Ni9/Pt(111)

1.8

1.2

Bare_Pt(111)

Ni6/Pt(111)

Pt1/Ni(111)

Ni3/Pt6_middle(111)

Pt3/Ni6_side(111)

0.8 Ni8/Pt(111)

Bare_Ni(111)

0.8 -2.2

6.3

Surface Energy (eV/atom) 1.4

1.0

(d)

0.6

Surface Energy (eV/atom)

2.0

5.5

1.4

2 R =0.8856

Pt3/Ni_middle(111)

(eV)

5.2

Work function (eV)

Work function (eV)

1.35

(b)

0.70

0.8 4.35

Ni3/Pt_side(111) Ni9/Pt(111)

E

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 18 of 41

Ni3/Pt6_side(111)

Sub-Pt9/Ni(111)

-2.0

-1.8

-1.6

-1.4

Ni9/Pt(111)

(e) -1.2

(f)

0.6 -2.8

d-band center (eV)

-2.4

-2.0

-1.6

-1.2

d-band center (eV)

Figure 6: Change in activation energy barriers with work function (a and b), surface energy (c and d) and d-band center (e and f) for different Ni-and Pt-based surface alloys.

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tors. Overall, work function seems to be a qualitative descriptor for Ni-and Pt-based surface alloys except for a few anomalies. However, the predictions from work function calculations should be verified and treated with care.

Surface energy vs. Activation energy Recently, surface energies were used to establish a volcano shaped correlation with experimental exchange current density in electrochemical reactions 78 and to distinguish between the reactivity of Cu-Ni nanocubes and Cu-Ni octahedra for aldehyde-alkene-amine coupling reaction. 79 Along these lines, plots of surface energy vs. Ea for the Ni- and Pt-based surface alloys were made (Figure 6c and 6d.) to establish a relationship between these two parameters. Linear regression coefficients (R2 ) obtained from fitting straight lines for Ni- and Pt-based surfaces are 0.89 and 0.83, respectively. For Ni-based alloys, only those points with activation energies less than 1.5 eV were chosen for fitting. Moreover, sub-Pt9/Ni(111) is not included during fitting of Ni-based alloys, as it shows significantly low activation energy, even lower than pristine Pt(111) and a very high surface energy (8.76 eV/Å), which is the highest among all the surface alloys. Inclusion of this point for fitting shows an exponential type relation between activation energy and surface energy. Excluding the mentioned anomalies, the linear fits to the surface energy vs. Ea plots show that activation energies can be qualitatively calculated using the fitted parameters to the surface energy vs. Ea plot. Although surface energies can perform better than work function in predicting Ea values for CH4 dissociation on Ni- and Pt-based surface alloys, few anomalies are observed in this case too. This further entails more efficient descriptors for this reaction on alloy surfaces.

d-band center vs. Activation energy One of the most promising descriptor that has been used widely in heterogeneous catalysis and presently being used in electrocatalysis is d-band center. 59 Previously, it was shown that d-band center can be used to understand and explain trends in reactivity of molecules interacting with pure metal surface, bimetallic alloy surfaces/surface alloys, metal surfaces under stress etc. 80 In this

19



case, the fits to the d-band center vs. activation energy plots for both Ni- and Pt-based surface alloys as shown in Figure 6e. and 6f. are very good considering the fact that no alloy is excluded as was previously with work function and surface energy. The R2 values were 0.87 and 0.83 for Ni- and Pt-based surface alloys, respectively. The plots, however, showed a decease in activation energy with increasing values of d-band center, agreeing with the predictions of d-band center and with most previous predictions. Among the three surface based reactivity descriptors, d-band center explains the change in reactivity very well. That said, it is important to note that it is not possible to completely understand the change in reactivity with a single surface based descriptor. This is at par with conclusion of the review by Khulbe et al. 81 that no simple relationship exist between catalytic activity and its electronic properties like percentage of d-character, workfunction etc., and thereby necessitates a search for a single/hybrid reactivity descriptors with good predicting capabilities.

Bronsted-Eyring-Polanyi (BEP) and Transition state scaling (TSS) relationships Discussion in the above section brought to fore the insufficiency for surface based descriptors to explain reactivity completely in surface alloys. As a result, we now rely upon energy based descriptors to elucidate change in reactivity in Ni-Pt surface alloys. Linear energy relations have been very useful in the understanding of catalytic relations, theoretically, by providing a quick estimate of reaction barriers of large number of systems, thereby reducing computational effort for a ) DFT calculations. 82 BEP is one such linear relationship that correlates activation energy (∆Ediss a with reaction energy (∆Ediss ). ∆Ediss is the energy difference between EIS , the energy of initial

state (CH4 adosrbed), and ET S , the energy of the transition state whereas reaction energy ∆Ediss is defined as ∆Ediss = EFS − EIS , where EFS is the energy of final state (H and CH3 coadsorbed). Transition state scaling (TSS) relation, is another alternative linear relation, that correlates ET S with final state energy with respect to methane, Ediss . Ediss is defined as Ediss = EFS − (ECH4 + Ebare ). Herein, the usefulness of these two relationships have been investigated for CH4 dissociative chemisorption over bimetallic surface alloys. The straight lines fitted to the plots of both BEP

20


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2.0

2.0

R

2 = 0.74

R

1.8

1.8

1.6

1.6

2 = 0.93

Pt9/Ni(111)

Pt6/Ni(111)

(eV) TS

1.2

E

Bare_Pt(111) Ni6/Pt(111)

1.0

0.8

Ni8/Pt(111)

0.6 -0.50

-0.25

0.00

Pt3/Ni_middle(111) Pt1/Ni(111)

1.2

Bare_Ni(111)

1.0

Ni3/Pt_middle(111)

Ni9/Pt(111)

Pt3/Ni_side(111)

1.4

E

TS

(eV)

Sub-Ni9/Pt(111)

1.4

0.25

0.50

0.8

(a)

Ni3/Pt_side(111)

0.75

Sub-Pt9Ni(111)

(b)

0.6

1.00

-0.3

0.0

0.3

E (eV) diss

0.6

0.9

1.2

1.5

E (eV) diss

2.0

2.0

R

2 = 0.74

R

1.8

1.8

1.6

1.6

Pt9/Ni(111)

2 = 0.92

diss

(eV)

Sub-Ni9/Pt(111)

1.4

0.8

Pt3/Ni_middle(111) Pt1/Ni(111)

1.2

E

Bare_Pt(111) Ni6/Pt(111)

1.0

Pt3/Ni_side(111)

1.4

a

1.2

a

diss

(eV)

Pt6/Ni(111)

E

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1.0

0.6 -0.50

Ni8/Pt(111)

-0.25

Bare_Ni(111)

Ni3/Pt_middle(111)

Ni9/Pt(111)

0.00

(c)

Ni3/Pt_side(111)

0.25

0.50

0.8

0.75

Sub-Pt9Ni(111)

(d)

0.6

1.00

-0.3

0.0

E (eV) diss

0.3

0.6

0.9

1.2

1.5

E (eV) diss

Figure 7: Plots of BEP and TSS relationship showing the near relationship between the barrier heights and the reaction energies for various Ni-Pt surface alloy systems. and TSS relationships for both Ni- and Pt-based surface alloys as shown in Figure 7 show a linear correlation between the two calculated parameters. With both BEP and TSS relationships, the fit was better (R2 = 0.92) for Ni-based surface alloys, compared to that on Pt-based surface alloys with R2 = 0.74. Our BEP relationship results are consistent with earlier study of methane dissociation on Ni(111) and NiPt(111). 35 A comparison between the actual activation barriers and the ones calculates using these relationships are given in Table S8 of Supplementary Information. Although linear relationships are able to predict well the activation energy barriers for Ni-based surface alloys (near linear increase in Ea with increasing Pt concentration), these relationships are not so efficient in predicting the activation barriers of Pt-based surface alloys (with no trend in change in Ea values with changing Ni composition). These linear relationships are able to predict better the 21



activation energies for the systems showing linear increase or decrease in the activation energies, while it falters for systems with no particular trend in Ea with changing composition. Failure in predicting the activation energies for Pt-based system leads to the understanding that the fit to the data depends heavily on the data set. However, it is believed that using Ea values from increased number of surface alloys with different surface compositions, and with different initial and final state configurations will supply more data to the fit and eventually help in better prediction of Ea values using these linear relationships. Since not one of the above descriptors, individually, could capture completely the changes in activation energies with changing surface composition of both Ni- or Pt-based surface alloys, a search for hybrid descriptors which uses both surface, and energy related parameters as inputs is deemed necessary. Using various surface alloy compositions, surface parameters, energy parameters etc., as input parameters, machine learning algorithms will be a promising route towards prediction of activation energies for any unknown bimetallic surface alloys/alloy surfaces, with improved accuracy.

Effect of Surface Temperature on Dissociation Probabilities Semiclassical tunneling (dissociation) probabilities of CH4 on all the Ni- and Pt-based alloy surfaces and subsurface alloys were plotted at 0K, 90K, 475K and 1200K temperatures (Figure S10 and S11 of Supplementary Information). These surface temperatures were chosen since results from quantum dynamics calculations and molecular beam experiments were available. 74 However, surface reactions may occur at higher temperatures at which tunneling is not important. Using equations 1 and 2, the rigid surface probabilities were modified for lattice motion by including both mechanical (α) and electronic (β ) coupling parameters (Figure S5-S8 in Supplementary Information). Changes in activation energy barriers and location of the barrier at different values of lattice atom coordinates is given in Table S9 of Supplementary Information. Dissociation probabilities for CH4 over Pt- and Ni-based alloy surfaces for different incident energies calculated at 90 K, plotted in Figure 8a and 8b, is chosen as an illustrative example to understand and explain the effect of surface temperature on reactivity, Individually, electronic coupling parameter (β ), accounting for 22


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0

10

Pt9/Ni(111)

Ni based surface alloys at 90K

Pt6/Ni(111) Pt3/Ni_side(111)

-1

10

Pt3/Ni_middle(111)

Dissociation Probability

Pt1/Ni(111) Bare Ni(111)

-2

10

Sub-Pt9/Ni(111)

-3

10

-4

10

-5

10

(a) -6

10

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

Incident Energy (eV)

0

10

Sub-Ni9/Pt(111)

Pt based surface alloys at 90K

Ni6/Pt(111) Bare Pt(111)

-1

10

Ni3/Pt_middle(111) Ni3/Pt_side(111)

Dissociation Probability

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Ni8/Pt(111)

-2

10

Ni9/Pt(111)

-3

10

-4

10

-5

10

(b) -6

10

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

Incident Energy (eV)

Figure 8: Dissociation probabilities of CH4 on (a) Ni-based and (b) Pt-based bimetallic surface alloys at 90K. change in activation energy with the motion of lattice atom, increases dissociation probabilities at all incident energies. On the other hand, mechanical coupling parameter (α), explaining the recoil effect during the approach of CH4 molecule, contributes to increase in dissociation probabilities at all energies except at high incident energies. Differences in contribution from these two parameters on dissociation probabilities is illustrated for (Ni8/Pt(111)) at a particular temperature (Figure S9 of Supplementary Information), as an example. Among the Ni-based alloys, as shown in Figure 8a, the subsurface alloy substituted with nine Pt atoms, sub-Pt9/Ni(111), showed the highest reactivity at 90 K, followed by the unalloyed Ni(111) 23



surface. Among the surface alloys, the reactivity trend follows the trend seen with the activation energy barriers. Excepting both Pt3/Ni(111) alloys (side and middle), decrease in dissociation probabilities with increasing activation energies which increased as a result of increasing alloying Pt concentration on the surface was calculated. These two alloys i.e., Pt3/Ni_middle(111) and Pt3/Ni_side(111), showed similar reactivity irrespective of the position of the alloying element, although these two surfaces showed a difference in activation energy barrier of 0.11 eV. This similarity is due to the synergistic effects of both mechanical (α) and electronic coupling (β ) parameters. Pt3/Ni_side(111) with a lower barrier (1.33 eV) when corrected with β =1.25 eV/Å, the reactivity curve is shifted to lower energies compared to the shift produced by β = 1.17 eV/Å calculated for Pt3/Ni_middle(111). However, the reactivity curve of Pt3/Ni_side(111) with slightly higher α value (0.24) is shifted to the right side more than that is seen for Pt3/Ni_middle(111) with α=0.15. Although the reactivity of these two alloys are similar, they differ in reactivity by at least one order of magnitude, at lower energies, which is apparent with increase in temperature to 1200 K (Figure S10). Lower reactivity calculated for Pt6/Ni(111) and Pt9/Ni(111) is attributed to its higher activation energies. Similarly, for the Pt-based alloys, the sub-surface Ni9/Pt(111) surface showed least reactivity due to it exhibiting higher activation barrier of 1.37 eV. With comparable activation energies, reactivity of all surface alloys and unalloyed Pt(111) surface fall within a small energy range of 0.22 eV (Figure 8b). Peculiar shape of the curves corresponding to Ni3/Pt_middle(111), Ni6/Pt(111) and Ni9/Pt(111) is due to higher β values ( 1.08 eV/Å) compared to other surface alloys with beta values approximately in the range 0.93-0.98 eV/Å. With higher β values, reactivity tends to increase at lower energy ranges (Fig. S11) leading to a bent curve compared to alloys with lower β values. Overall, inclusion of surface temperature increases reactivity of all the surface alloys studied. Some of the pathways become more effective at higher substrate temperature, thereby increasing dissociation probability at lower incident energy due to an increased molecule-lattice atom coupling. In other words, these pathways have lower effective barrier for dissociation at higher

24


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temperatures. It is important to note that in some cases, although the barriers are similar, depending on the extent of coupling of the incoming CH4 molecule with the lattice atom, the reactivity may differ. So, with the help of this simple yet physically meaningful ‘sudden model’, that use only data computed at TS, the effect of lattice motion in CH4 dissociative chemisorption on various Ni- and Pt-based surface alloys have been illustrated. This further emphasizes the need for inclusion of surface temperature effect while modelling gas-surface reactions to achieve a near realistic description of industrially important reactions.

Carbon formation and resistance 1.8 1.5

Ni111

TS4

Pt111 Ni9/Pt(111) TS2

Sub-Pt9/Ni(111)

1.2

Energy (eV)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


TS1

0.9 0.6 TS3

0.3 0.0 -0.3 -0.6 -0.9 CH

4

CH

3

+ H

CH

2

+ H

CH + H

C + H

Figure 9: Comparison of activation energy barriers and reaction energies of all steps of CH4 dissociation for the chosen two Ni-Pt surface alloys with that of pure Ni(111) and Pt(111). In addition to studying the surface alloys that facilitate CH4 dissociative chemisorption, the initial and rate-determining step of SRM and DRM reactions, on Ni- and Pt-based surfaces, re25



sistance to carbon formation was also studied on selected alloys. Two alloys, one in each alloy system, i.e., sub-Pt9/Ni(111) and Ni9/Pt(111) with activation barriers of 0.84 and 0.71 eV, respectively, for CH4 dissociation were chosen to study their resistance to carbon formation compared to that on Ni(111) and Pt(111) surfaces. Comparison of activation energy barriers and reaction energies of all steps of CH4 dissociation for the chosen two Ni-Pt surface alloys with that of pure Ni(111) and Pt(111) is plotted in Figure 9 and the values used to plot are provided in Table S12 of Supplementary Information. These two alloys, interestingly, having Ni on the top layer and Pt in the second layer improve catalytic performance, by reducing the energy barrier, irrespective of the third and fourth layers. Work function values and d-band center of these two alloys are similar and the surface energies are higher than all other alloys. For the first and second steps of CH4 dissociation, i.e., CH4 → CH3 + H and CH3 → CH2 + H, apparently, sub-Pt9/Ni(111) showed higher barrier to dissociation compared to Ni9/Pt(111). However, for the third step, CH2 → CH + H, subPt9/Ni(111) showed barrier 0.11 eV lower than Ni9/Pt(111). In the carbon formation step (final step), sub-Pt9/Ni(111) exhibits considerably higher barrier ( 0.47 eV) to dissociation than that is calculated on Ni9/Pt(111). In addition, the carbon adsorption energy (Table S13 of Supplementary Information) on Ni9/Pt(111) is 0.73 eV more stable and the overall reaction is more exothermic than on sub-Pt9/Ni(111). The trend in the activation energies for individual steps agree with previous results obtained for different kinds of Ni-Pt alloy surfaces. 34,35,54 Our results also agree with the fact that the addition of Pt enhances the resistance to carbon formation as proposed by Fan et al., 34 and Zhang et al. 54 Formation of C2 dimer from two atomic C atoms is the first step for carbon nucleation on any surface and the barrier heights for C2 formation is directly indicative for carbon resistance property. 83–85 In addition to calculations on CH4 dehydrogenation steps, we have performed calculations for C2 formation, a crucial step in elucidating the resistance to carbon formation on any surface, on both Sub-Pt9/Ni(111) and Ni9/Pt(111) alloy systems. It was found that barrier heights for C2 formation is as high as 1.49 eV for sub-Pt9/Ni(111) and 1.67 eV for Ni9/Pt(111). In both cases, activation energy barriers are significantly higher than the ones reported on bare Ni(111)

26


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(0.88 eV). 83,84 Adsorption energies of C2 dimer are -7.02 and -7.48 eV on Sub-Pt9/Ni(111) and Ni9/Pt(111), respectively. Comparison of reaction energies and activation energy barrier for C2 dimer formation for Ni9/Pt(111) and Sub-Pt9/Ni(111) are shown in Figure 10. Although C2 formation has lower barrier and the reaction is exothermic for Sub-Pt9/Ni(111) compared to Ni9/Pt(111), the energy barriers on both these surfaces are considerably higher ( 1.7-1.9 times) when compared to that on pure Ni(111). Therefore, it can be understood that C2 formation on these two surface alloys is less likely possible and hence, within this context, it is safe to claim that both the surface alloys are coke resistant.

1.8 1.6

TS

Sub-Pt9/Ni(111) Ni9/Pt(111)

1.4 1.2 Energy (eV)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1.0 0.8 0.6 0.4 0.2 0.0 -0.2

C

C + C

2

Figure 10: Comparison of activation energy barriers and reaction energies of C2 dimer formation reaction on Ni9/Pt(111) and Sub-Pt9/Ni(111) surfaces. While the performance of both Ni9/Pt(111) and Sub-Pt9/Ni(111) is similar for C2 formation, considering the other factors, i.e., activation energies to dissociation, carbon adsorption energy, overall exothermicity of the reaction, Ni9/Pt(111) can easily be ruled out as a potential candidate 27



for CH4 dissociation that can also resist carbon formation. On the contrary, sub-Pt9/Ni(111) shows lower barrier to CH4 dissociation, higher barrier for CH dissociation as well as C2 dimer formation and the overall energy of the reaction is endothermic. Based on this, it is suggested that Ni(111) based sub-surface alloy with nine Ni atoms replaced by Pt, sub-Pt9/Ni(111), can be an efficient catalyst for SRM and DRM reactions. Additionally, since Ni(111) is used as the base metal with just one layer replaced by Pt, sub-Pt9/Ni(111) offers an advantage of being a cost effective catalyst. While most of the previous reports 34,35,54 concentrated on surface alloys, this study is the first one to show that effectiveness of Pt-Ni sub-surface alloys towards CH4 dissociative chemisorption. In a similar context, the usefulness of sub-surface alloys also known as near surface alloys (NSA) were studied extensively for H2 dissociative chemisorption on metal surfaces. 86 With the development of number of software packages and computational power, first principles density functional theory (DFT) based methods are widely used in the prediction of industrial catalysis for a many industrially relevant reactions. Although successful in many instances, DFT has its own limitations. DFT can be applied to large systems modelled as clusters and also for periodic systems like metal surfaces with ease as opposed to the wave function based methods due to its speed and applicability. However, the accuracy of these calculations have always been under scrutiny. Atomistic details unravelled by DFT, when not accurate, may lead to errors in the calculated rates in KMC simulations that is widely used to simulate actual reaction conditions. It has been mentioned earlier that the first principles methods miss the link between fundamental thermochemistry and kinetics at the microscopic and the macroscopic scale that is realized in chemical reactor conditions. 87 In addition, it was also noted that the energetics calculated by DFT codes need to carefully assessed and cautiously accepted 88 before being incorporated into KMC simulations. Uncertainty analysis 89 of the calculated values are also necessary in order to achieve accuracy when using the DFT values in KMC simulations. Nevertheless, presently, DFT is the most accessible tool to model atomistic details of heterogeneous catalytic reactions. Recent efforts put in to the development of accurate DFT functionals and the employment of machine learning algorithms, hopefully will result in accurate calculation of energetics and increase the predictive

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power of DFT calculations.

Conclusions Methane dissociative chemisorption was studied on different Ni- and Pt-based surface and subsurface alloys with varying concentrations of alloying elements (Ni and Pt). Changes in surface properties, such as surface energy, work function and density of states, caused due to alloying, were also calculated and compared. For Ni based alloys, surface energy increases with increasing Pt content, while work function decreased for low concentrations of Pt and increased for high surface concentrations of Pt. For Pt-based alloys, surface energy decreased and work function increased with increasing concentration of Ni. A downshift in d-band center was calculated for Ni-based alloys while increasing Ni concentration in Pt-based alloys resulted in upshift of d-band center values. A linear increase in activation energies with increasing Pt concentration was calculated for Ni-based alloys. However, for Pt-based alloys with Ni as the alloying element, although there was an overall decreasing in activation energy barrier, no linearity in the decrease was observed. Usage of surface parameters as reactivity descriptors was quite successful in the case of Nibased alloys exhibiting a linear increasing in barrier with increasing Pt content. For Pt-based alloys, work function failed in capturing the activation energy trend, while surface energy and d-band center values performed well. Among the surface parameters, d-band center can be relied upon as a descriptor when predicting trends in activation energies for CH4 dissociation on large number of alloy systems. Energy based descriptors, on the other hand, were successful in predicting activation energy barrier for Ni-based systems and were partially successful in the case of Pt-based alloys, again due to the non linear change in activation energy barriers. This non-uniformity among the surface descriptors in explaining the reactivity trends in surface alloys reiterates the fact that there exists no simple relation between the surface parameter/property and reactivity of alloy surfaces/surface alloys. This lacuna can be rectified by using these surface parameters and energy relationships within a machine learning algorithm as features while predicting activation energies

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and reactivity of a large number of alloy systems. Surface temperature effects, included using a ‘sudden model’ predicted an increase in reactivity of all surface alloys. However, the nature and extent of increase strongly depend on the extent to which the barrier is modified and the extent of recoil of surface atoms as described by electronic (β ) and mechanical coupling (α) parameters, respectively. Calculation of energy barriers and reaction energies for the subsequent steps of CH4 dissociation on selected systems revealed that sub-Pt9/Ni(111) surface can be considered a potential candidate owing to (i) reduced barrier for CH4 dissociation, (ii) higher barrier to CH dissociation, (iii) lower carbon adsorption energy, (iv) overall endothermic nature of the reaction, and above all (v) its cost effectiveness. Finally, thinking beyond the conventional bimetallic catalysts involving transition metal-noble metal combination, very recent reports on dissolution of active catalysts for methane (Ni, Pt, Pd), in inactive low-melting temperature metals (In, Ga, Sn, Pb), 90 for pyrolysis of methane to produce stable molten metal alloy catalysts ("single atom" catalysts) are promising for the future and worth further investigations.

Notes The authors declare no competing financial interest.

Acknowledgement S.R. thanks Council for Scientific and Industrial Research (CSIR), India, for his fellowship under Grant No. 09/921(0126)/2015-EMR-I. H.S. and A.K.T. sincerely acknowledge Science and Engineering Research Board (SERB), New Delhi, India, for funding through Project No. EMR/2015/001337.

Supporting Information Available This material is available free of charge via the Internet at http://pubs.acs.org. 30


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An improved methane reforming catalyst – Sub-Pt9/Ni(111) Lower barrier for CH4 dissociation Higher barrier for CH dissociation Low adsorption energy for carbon Overall endothermic reaction Cost effective

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PtâNi Subsurface Alloy Catalysts: An Improved Performance toward

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