Generalized Surface Coordination Number as an Activity Descriptor

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Article

Generalized Surface Coordination Number as an Activity Descriptor for CO Reduction on Cu Surfaces 2

Zhonglong Zhao, Zhengzheng Chen, Xu Zhang, and Gang Lu J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.6b10155 • Publication Date (Web): 18 Nov 2016 Downloaded from http://pubs.acs.org on November 21, 2016

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The Journal of Physical Chemistry

Generalized Surface Coordination Number as an Activity Descriptor for CO2 Reduction on Cu Surfaces Zhonglong Zhao, Zhengzheng Chen, Xu Zhang, and Gang Lu* Department of Physics and Astronomy, California State University, Northridge, California, 91330, United States ABSTRACT: Surface engineering has proved effective in enhancing activities of CO2 reduction reaction (CO2RR) on Cu. However, predictive guidance is necessary for the surface engineering to reach its full potentials. We propose that generalized coordination number (GCN) can be used as a descriptor to characterize CO2RR on Cu surfaces. A set of linear scaling relations between the binding energy of CO2RR intermediates and GCN is established to construct a volcano-type coordination-activity plot, and from which we can derive the theoretical overpotential limit on Cu surfaces. We predict that dimerized (111) surface yields the lowest possible overpotential on Cu for CO2RR to methane, and surface engineering by creating adatoms could lower CO2RR overpotentials and simultaneously suppress the competing hydrogen evolution reaction.

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1. INTRODUCTION The electrochemical reduction of CO2 into fuels and useful chemicals has drawn significant interest over past decades. This process could potentially be employed to produce carbon neutral fuels from renewable sources, providing an effective way to mitigate our pressing energy and environmental problems.1-3 Numerous metal and metal-based electrocatalysts, such as Cu,4-5 Pt,6 Au,7 Au/Cu bimetallic nanoparticles,8 and intermetallic compounds,9 have been found active for CO2RR. Among them, Cu and its alloys are the only metals that are capable of producing significant quantities of hydrocarbons from CO2, but they do so inefficiently with high overpotentials, close to 1 V.4-5, 10 In addition, Cu has a poor selectivity – more than 16 different CO2RR products have been identified.11 To remedy these problems, surface engineering has been widely explored and proved valuable in Cu.12-20 For example, Tang et al.12 revealed that nanoparticle covered and sputtered Cu surfaces exhibited higher Faradaic efficiencies for C2H4 and CH4 formation compared with electropolished surfaces, thanks to the existence of low-coordinated surface sites. Sen et al.13 reported that nanostructured surfaces with cavities could be formed in Cu foams, facilitating CO2RR to formic acid and other higher-order hydrocarbons. Ren et al.19 found that agglomerates of Cu nanocrystals with a high density of surface defects showed exceedingly high activities for CO2 reduction to n-propanol. Despite the encouraging progress, predictive guidance to improve CO2RR activities on Cu remains unknown, and there is no clear correlation between surface geometry and catalytic activities. As a result, surface engineering depends largely on trial and error and appears serendipitous more often than not. In this paper, we propose a descriptor for CO2RR based on generalized coordination number (GCN) on Cu surfaces. By means of density functional theory (DFT) calculations, we establish linear scaling relations between the GCN and


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binding energy of CO2RR intermediates, from which we can construct a volcano plot connecting CO2RR activity (via the overpotentials) to the GCN. Hence, the GCN can provide the guidance for surface engineering on Cu. In particular, we can assess theoretical overpotential limit on Cu and predict surface structures that would approach such limit. 2. COMPUTATIONAL DETAILS DFT calculations are performed using the Vienna ab initio simulation package (VASP).21 The revised

Perdew-Burke-Ernzerhof

(RPBE)

functional

within

the

generalized

gradient

approximation22-23 and the projector-augmented wave pseudopotential24 are used in the calculations. A plane-wave cutoff energy of 400 eV is employed in the calculations. K-points are sampled with a 3×3×1 Monkhorst-Pack mesh.25 All atomic geometries are fully optimized until the force on each atom is less than 0.02 eV Å-1. The surface slab models contain at least four Cu layers with the bottom layer fixed to the bulk geometry and a large enough periodic cell to minimize possible lateral interactions. To avoid interactions between periodic images, a vacuum layer of no less than 17 Å is used for all calculations. The equilibrium lattice parameter of Cu is taken as 3.615 Å to construct the slab models. The binding energy of the intermediates is defined as:

EB[C x H y O z ] = E[C x H y O z ] − Eslab − xEC − yEH − zEO

(1)

where E[CxHyOz] and Eslab denote the energy of the total system and the clean slab, respectively. EC, EH, and EO are referenced to the energy of graphene, gaseous hydrogen (H2), and the difference between H2O and H2, respectively. 3. RESULTS AND DISCUSSION It is well known that the activity of a surface site depends on, among other things, its coordination number (cn), i.e., the number of its nearest neighbors. However, the coordination


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number is not a good descriptor for chemical reactions in general, and CO2RR in particular. For example, the active sites on Pt nanoparticles of different sizes have the same coordination number (cn = 9), but their binding energy to OH* could vary by 0.5 eV.26 The top sites on Cu (110) and (211) step edges both have cn = 7 as shown in Figure 1c, d, but their activity for CO2RR could differ significantly. Recently, a breakthrough26-27 has been made to generalize the coordination number to include the contributions from the second nearest neighbor as follows: ni

cn( j ) j =1 cnmax

GCN(i ) = ∑

(2)

where j is the first nearest neighbors of an active site i, and cn(j) is the coordination number of site j. cnmax is the maximum cn in the bulk. By combining the first and second nearest neighbors of an active site, the generalized coordinate number (GCN) contains more information about the local structure, thus can capture the “structure sensitivity” more accurately. Indeed, the GCN has proved as a good descriptor for oxygen reduction reaction (ORR) on Pt nanoparticles.26 Here, we extend the idea of GCN to CO2RR on Cu surfaces. More specifically, we examine ten distinctive surface structures to cover a wide range of surface features and GCN values. As shown in Figure 1, these include: (111) and (100) facets; (110), (211) and (711) step edges; kinks on (211) step edge; adatoms on (111) and (100) facets; a cavity on (111) facet. The cavity is produced by removing seven adjacent surface atoms, and the active site is at the bottom of the cavity. The active site on each surface is highlighted in cyan color in Figure 1, and based on which the binding energy will be calculated. The GCNs for these active sites are summarized in Table S1.


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Figure 1. Catalog of the surface sites considered in this work: (a) (111) facet, (b) (100) facet, (c) (110) step edge, (d) (211) step edge, (e) (711) step edge, (f) kinks on (211) step edge, (g) a dimer on (111) facet, (h) a trimer on (111) facet, (i) a tetramer on (100) facet, and (j) cavity on (111) facet. Sphere in the cyan color represents the active site; the magenta and gray spheres correspond to the 1st and 2nd nearest neighbors, respectively. In this work, we focus on CO2 reduction to CH4, although other products can be examined similarly. The reaction pathways from CO2 to CH4 on Cu have been established by Peterson et al.28-29 and are summarized below: H*

H*

H*

H*

H*

H*

H*

H*

CO 2 → COOH * → CO* → CHO* → CH 2 O* → OCH 3 * → O*+CH 4 → OH* → H 2 O

(3)

There are seven adsorbed intermediate species denoted by *. Along each elementary step, a proton-electron pair is transferred from one intermediate to the next until the final product of H2O is produced. The binding energies of the seven intermediates on each of the ten active sites are calculated by DFT, and plotted as a function of GCN for each site. As shown in Figure 2, linear scaling relations between the binding energy and the GCN for each intermediate are evident. The linearity is particularly strong for those intermediates (COOH*, CO*, CHO*, and


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CH2O*) that bond with the active sites through a carbon atom. And some of these intermediates turn out to be responsible for overpotential dominating steps. Based on these scaling relations, the binding energy, EB, of a given intermediate can be expressed as a linear function of GCN. For example, for the elementary step CO* → CHO*, we have:

EB [CO] = 0.114GCN + 0.250 EB [CHO] = 0.181GCN + 0.420

(4)

Following the established computational procedure,28-29 the free energy (G) of the intermediate can be derived from its binding energy by adding a few correction terms, involving zero-point energy (ZPE), heat capacity (CP), entropy (-TS), and solvation free energy (Gsol): G[CO] = EB [CO] + ZPE + ∫ CP dT − TS+Gsol G[CHO] = EB [CHO] + ZPE + ∫ CP dT − TS+Gsol

(5)

The free energies for other intermediates can be obtained in the same manner. According to the computational hydrogen electrode (CHE) model,30 the limiting potential (UL) for the reaction step CO* → CHO* is defined as the change of the free energies between CHO* and CO*, in addition to the chemical potential of a proton-electron pair µ[H+ + e-], calculated as half of the chemical potential of gas-phase H2 at 0 V: UL = −

G[CHO] − G[CO] − 0.5µ[H 2(g) ](U = 0 VRHE ) e

(6)

Equations 4-6 enable the limiting potential UL to be expressed as a function of GCN for the elementary step CO* → CHO*, i.e., UL(CO* → CHO*) = –0.067GCN – 0.416. In the same way, we can obtain the linear expressions between UL and GCN for other seven elementary steps towards CH4 production. The assembly of these linear plots is shown in Figure 3. The distances between the equilibrium UL = 0 line and the most negative UL lines represent the overpotentials (highlighted in gray), which are the minimum potentials required to guarantee all reaction steps


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to be exothermic. The three most negative UL lines outline the so-called volcano plot: (1) the desorption of OH* with GCN < 3.1 (line 1); (2) the protonation of CO* to form CHO* with 3.1 ≤ GCN < 8.4 (line 2); and (3) the reduction of CO2 to COOH* with GCN ≥ 8.4 (line 3). From this volcano plot, we conclude that the protonation of CO* to CHO* (line 2) is the overpotential determining step, consistent with previous reports.20, 29 The intersection between the line (1) and (2) at GCN=3.1 defines the volcano top, which represents the lowest possible overpotential for CO2 → CH4 on Cu surfaces. This is the theoretical overpotential limit, assuming that the linear scaling relations are valid for all Cu surfaces. In other words, the unknown surface structure(s) with GCN = 3.1 would be the ultimate goal of surface engineering in Cu, and other modifications of Cu surfaces would likely lead to higher overpotentials. This theoretical limit is predicted as 0.62 V, which is 16% lower than the lowest overpotential known to Cu surfaces i.e., 0.74 V on (211) stepped surface.28-29 As a comparison, the overpotential on Cu (111) and (100) facets was found as 0.89 and 0.81V, respectively.20 Hence, there is still some room (~0.12 V), albeit not much, to further lower the overpotential on Cu via surface engineering. On a positive note, we find that the linear scaling relations are no longer valid on strained surfaces (Figure S1), implying that straining Cu surfaces may offer a potential route to beat the theoretical limit, pushing the overpotential below 0.62 V. For instance, recent DFT calculations predicted that the overpotential of stretched penta-twinned Cu nanowires could reach 0.51 V.31 Moreover, one can combine surface engineering with chemical modifications, such as alloying, ligand stabilization, addition of promoters, etc. to further reduce the overpotential.32


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Figure 2. Binding energy of the reaction intermediates for CH4 production as a function of GCN (symbols). The linear scaling relations between GCN and binding energy are shown.


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Figure 3. The limiting potentials (UL) as a function of GCN for each elementary step. The corresponding surface site for each GCN is labeled on the volcano plot. Since the overpotential decreases with decreasing GCN, the goal of Cu surface engineering would be to lower GCN until the theoretical limit is reached at GCN = 3.1. Among the surface sites considered here, the adatoms such as 2AD@111, 3AD@111, and 4AD@100 are the most promising ones. In particular, we predict that dimerized (111) surface (2AD@111) would have the lowest overpotential, near the volcano top. The overpotential for CH4 production on 2AD@111, 3AD@111, and 4AD@100 is predicted as –0.61V, –0.65 V, and –0.71 V, respectively. These values are comparable to those found in some of the most active CO2RR catalysts, such as W/Au near-surface alloy (0.63 V) and Cu55 nanoparticle on defective graphene (0.68 V).33-34 We note that adatoms are usually not thermodynamically stable and tend to aggregate into close-packed surfaces.35 Nevertheless, recent studies have shown that the use of surface adhesive ligands can effectively increase the stability of the adatoms and prevent their aggregation.36-39 For example, both melamine and tris(phenylthio)benzene molecular network were found to stabilize single Au adatoms and small Au clusters on Au (111) surface.36-37 We hope the present work could inspire similar experimental explorations to stabilize adatoms on Cu for CO2RR. Peterson et al.29 recently demonstrated that the binding energy of CO could also be used as a descriptor to construct volcano plots for different transition metals, and found Cu near the top of the volcano for CO2 reduction to CH4. Peterson’s work focused on the comparison among different metals, while ours is aimed at the comparison among different surfaces of the material identified by Peterson. Although the binding energy of CO and the GCN can both be used as descriptors, the latter could be assessed easily without DFT calculations. Given the


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success of GCN as descriptors for both ORR and CO2RR, we believe that it can also be extended to other reactions.

Figure 4. The free energy diagram for CH4 production on the active sites of (111), (211), and 2AD@111 with an applied voltage at -0.96, -0.72, and -0.62 V vs. RHE, respectively. All reaction steps become exothermic under the applied voltages. The adsorption geometries on 2AD@111 are shown in the insets. The validity of the volcano plot and the resultant conclusions rely on the linearity of the scaling relations, particularly for the overpotential determining step (line 2). We next calculate the free energy diagrams for CO2 → CH4 on Cu (111) surface, (211) stepped surface, and 2AD@111 (Figure 4), and compare the directly computed overpotentials to what were extracted from the volcano plot. The comparisons between the computed and extracted overpotentials for all considered surfaces can be found in Table S2. We find that the directly computed (extracted) overpotential on (111), (211) and 2AD@111 is 0.96 V (0.95 V), 0.72 V (0.78 V), and 0.62 V


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(0.61 V), respectively. Others have also calculated the overpotential on Cu (211) as 0.74 – 0.75 V.28, 31 These excellent agreements provide strong support to the main conclusions.

Figure 5. The HER free energy diagram on the surface sites at 0 V vs. RHE. The relevant atomic structures for HER on 2AD@111 are shown as insets. Lastly, we examine hydrogen evolution reaction (HER), which is a key side reaction that competes with CO2RR. Thus an ideal active site for CO2RR should suppress HER by either bonding very weakly or very strongly to H* – the former making H adsorption difficult while the latter rendering H2 formation difficult.28-29, 33 In Figure 5, we display the free energy diagram for HER on Cu surfaces considered here. We find that the binding energy of H* is not monotonic with respect to GCN, in contrast to CO2RR. 4AD@100 and 3AD@111 exhibit the highest limiting potential for * → H* and H* → H2, reflecting the weakest and strongest binding of H, respectively, among all the active sites. These results suggest that engineered Cu surfaces covered with adatoms such as 4AD@100 and 3AD@111could suppress HER, leading to both high activity and selectivity toward CH4 production.


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4. CONCLUSIONS In summary, we propose that the generalized coordination number could be used as an activity descriptor for CO2RR on Cu surfaces. A set of linear scaling relations between the binding energy of the CO2RR intermediates and the GCN on various surface sites such as cavity, step edges, kinks, and adatoms, has been established. Based on these scaling relations, we construct the activity – GCN volcano plot, from which we can derive the theoretical overpotential limit on Cu surfaces. We show that the surface engineering alone cannot lower the overpotential more than 0.12 V beyond what is on Cu (211) surface. We predict that the dimerized (111) surface could yield the lowest possible overpotential on Cu for CO2 reduction to methane. The predicted overpotentials from the volcano plot agree well to those determined from the direct DFT calculations. We reveal that surface engineering by creating adatoms such as 4AD@100 and 3AD@111 could lower the overpotentials for CO2RR and simultaneously suppress the competing HER. We believe that strain engineering could overcome the theoretical overpotential limit, and when combined with the chemical modifications, may revolutionize the development of metal catalysts for CO2RR.

ASSOCIATED CONTENT Supporting Information. GCN data (Table S1), the comparisons between the computed and extracted overpotentials (Table S2), and strain effects on the overpotentials (Figure S1).

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected]


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Notes The authors declare no competing financial interests.

ACKNOWLEDGMENT This work was supported by the Army Research Office through the grant W911NF-11-1-0353.

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Silly, F.; Shaw, A. Q.; Castell, M. R.; Briggs, G. A. D.; Mura, M.; Martsinovich, N.;

Kantorovich, L. Melamine structures on the Au(111) surface. J. Phys. Chem. C 2008, 112, 11476-11480.


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TOC Graphic


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Figure 1. Catalog of the surface sites considered in this work: (a) (111) facet, (b) (100) facet, (c) (110) step edge, (d) (211) step edge, (e) (711) step edge, (f) kinks on (211) step edge, (g) a dimer on (111) facet, (h) a trimer on (111) facet, (i) a tetramer on (100) facet, and (j) cavity on (111) facet. Sphere in the cyan color represents the active site; the magenta and gray spheres correspond to the 1st and 2nd nearest neighbors, respectively. 60x30mm (300 x 300 DPI)


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Figure 2. Binding energy of the reaction intermediates for CH4 production as a function of GCN (symbols). The linear scaling relations between GCN and binding energy are shown. 94x75mm (300 x 300 DPI)



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Figure 3. The limiting potentials (UL) as a function of GCN for each elementary step. The corresponding surface site for each GCN is labeled on the volcano plot. 66x53mm (300 x 300 DPI)


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Figure 4. The free energy diagram for CH4 production on the active sites of (111), (211), and 2AD@111 with an applied voltage at -0.96, -0.72, and -0.62 V vs. RHE, respectively. All reaction steps become exothermic under the applied voltages. The adsorption geometries on 2AD@111 are shown in the insets. 65x51mm (300 x 300 DPI)



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Figure 5. The HER free energy diagram on the surface sites at 0 V vs. RHE. The relevant atomic structures for HER on 2AD@111 are shown as insets. 70x60mm (300 x 300 DPI)


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Generalized Surface Coordination Number as an Activity Descriptor

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