Understanding Trends in the Electrocatalytic Activity of Metals and

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Understanding Trends in the Electrocatalytic Activity of Metals and Enzymes for CO2 Reduction to CO Heine A. Hansen, Joel B. Varley, Andrew A. Peterson,† and Jens K. Nørskov* SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States S Supporting Information *

ABSTRACT: We develop a model based on density functional theory calculations to describe trends in catalytic activity for CO2 electroreduction to CO in terms of the adsorption energy of the reaction intermediates, CO and COOH. The model is applied to metal surfaces as well as the active site in the CODH enzymes and shows that the strong scaling between adsorbed CO and adsorbed COOH on metal surfaces is responsible for the persistent overpotential. The active site of the CODH enzyme is not subject to these scaling relations and optimizes the relative binding energies of these adsorbates, allowing for an essentially reversible process with a low overpotential.

SECTION: Surfaces, Interfaces, Porous Materials, and Catalysis

A

reduction potential and provides a map of catalytic activity as a function of the bond energies of the intermediates, COOH and CO, in the catalytically active site. We explain why none of the elemental metals are very good catalysts in aqueous solution, why Cu, Ag, and Au are the best, and why the CODH enzyme works considerably better. We start by considering the CO2 to CO reduction on a metal surface. Previous DFT calculations of CO2 reduction on Cu surfaces have suggested that the stepped surfaces are most active9 and that CO is produced through the adsorbed intermediates COOH* and CO*.10 Similar intermediates have been proposed for the electroreduction of CO2 on Au in neutral aqueous solution.3,11 We consider the following reaction mechanism

n efficient and selective process for ambient temperature electrochemical reduction of CO2 could allow production of fuels from a range of renewable energy sources. The reduction of CO2 to CO can be viewed as a first step in such a process,1 and even for this simple two-electron reduction reaction, there is, at present, no electrode catalyst that is sufficiently efficient and selective.2 The noble metals are the best; gold catalysts in aqueous solution, for instance, have a high selectivity toward CO but an overpotential of more than 0.3 V at a current density of 0.2 mA/cm2.3 Homogeneous catalysts have shown high selectivity; however, the most active examples are unstable and lose activity under prolonged reaction conditions.1,4 While reductions in the overpotential may be achieved using different solvents, such as ionic liquids,5 there is still an urgent need to identify catalysts with lower overpotentials. Such catalysts exist in nature. The Ni-CODH enzymes catalyze CO2 reduction to CO with a turnover frequency of 95 s−1 at 20 °C.6 Immobilized on an electrode, the enzyme ChCODH I interconverts CO and CO2 essentially at current densities of 0.05 mA cm−2 within a 0.15 V overpotential window.7 It would be extremely interesting if stable arrays of the enzymes could be made, thus providing a high current density per electrode surface area.8 Equally interesting is the fact that the enzyme results show that an efficient catalyst actually exists. If we could understand why it is so efficient, perhaps we could use the insight to suggest inorganic analogues with a higher density of active sites. In the present Letter, we develop a model of the electrochemical CO2 to CO reduction process, which is applicable to both metals and the enzyme. The model is based on extensive density functional theory (DFT) calculations of reaction path free energies as a function of the © XXXX American Chemical Society

CO2 (g) + * + H+(aq) + e− ↔ COOH*

(1)

COOH* + H+(aq) + e− ↔ CO* + H 2O(l)

(2)

CO* ↔ CO(g) + *

(3)

where * denotes a free step site. Electroreduction of CO2 may result in a wide range of products. We have neglected the formation of formate as on most materials, it is formed with high selectivity only at a high overpotential.2 Formate and CO are produced in comparable amounts on Cu;12 however, this does not significantly affect the trends in the overpotential where the relevant scale is logarithmic for the partial current. The reduction of CO may lead to formation of hydrocarbons Received: December 19, 2012 Accepted: January 9, 2013

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⎛ ΔG #(U 0) + βe(U − U 0) ⎞ i i i ki = A exp⎜⎜ − ⎟⎟ kBT ⎝ ⎠

on Cu;10,13 however, because this only happens at significant rates at overpotentials of around 1 V, this has also been neglected in the present study. Figure 1 shows the calculated free energy diagram for CO2 reduction through this scheme on Au(211) and Pt(211), based

(7)

where ΔG#i (U0i ) is the activation free energy at the reversible potential U0i of step i, A is a pre-exponential factor, and β is a symmetry factor, which, for simplicity, we set to be 0.5. The reversible potential for step i is given by Ui0 = −

ΔGi e

(8)

where ΔGi is the reaction free energy at 0 V (against the same reference electrode; here, RHE) calculated using the computational hydrogen electrode (see the Supporting Information for further details). The equilibrium constants for the electrochemical steps are potential- and material-dependent through ⎛ e(U − U 0) ⎞ i ⎟ K i = exp⎜ − k T ⎝ ⎠ B

Figure 1. Free energy diagrams for CO2 electroreduction to CO on Au(211) and Pt(211) at the reversible potential, U0, for CO evolution and at a 0.35 V overpotential.

As a first approximation, we take the barrier for proton transfer at the equilibrium potential, ΔG#i (U0i ), to be materialindependent, such that all variations in the electrochemical rate constants between materials enter through material-dependent reversible potentials for steps 1 and 2. This allows us to introduce an effective pre-exponential factor, A′ = A exp(ΔG#i (U0i )/(kBT)), such that

on the computational hydrogen electrode model.14 On Au(211), CO2 activation through COOH formation is associated with a high increase in free energy at the reversible potential (where the free energies of the initial and final states are the same), while the standard free energy of CO desorption is close to 0. Increasing the magnitude of the overpotential (lowering the potential) makes COOH formation easier, resulting in increased CO production. On Pt(211), on the other hand, COOH is very stable, and CO2 activation will be exergonic. Here, desorption of CO is associated with a large change in free energy; because this is a nonelectrochemical step, increasing the overpotential does not affect the free energy change except indirectly through changes in coverages. The calculated free energy diagrams suggest that improved CO evolution activity could be obtained by finding a catalyst where the binding of COOH is stronger than that on Au(211) or when the binding of CO is weaker than that on Pt(211). To address the trends in CO evolution more accurately, a kinetic model is required in order treat the different time scales associated with coupled proton−electron transfer and CO desorption. We apply a simple phenomenological model to bring out the trends. The net reaction rates for reactions 1−3 are written as r1 = k1θ∗pCO2 −

k1 θCOOH K1

(4)

r2 = k 2θCOOH −

k2 θCO K2

(5)

r3 = k 3θCO −

k3 θ∗p K3 CO

(9)

⎛ βe(U − U 0) ⎞ i ⎟ ki = A′ exp⎜ − kBT ⎝ ⎠

(10)

The pre-exponential factor A′ is obtained by fitting to experiments for CO2 reduction on gold (where the electrochemical step is rate-limiting; see Figure 1), assuming that a typical sample has ∼5% steps.16 The latter assumption gives a relation between the partial current density of CO, jCO, and the turnover frequency, TOF (rate per site per second), of jCO= 22.2 μC·cm−2 · TOF. The model uses the CO pressure near the catalyst as an input parameter. An upper limit for the CO pressure is 1 atm, where CO bubbles are formed spontaneously, although the pressure could be lower if products were removed quickly from the interface. At pCO2 = pCO = 1 atm, the experimental current density at low overpotential on gold is reproduced with A′ = 3.6 × 104 s−1. If the CO pressure is reduced to pCO = 10−6 atm, A′ = 1.4 × 104 s−1 fits experiments well. The weak dependence of the fitted A′ on pCO is caused by the weak CO binding on gold. In the following, we employ the value of A′ = 3.6 × 104 s−1. In either case, the model yields a Tafel slope of about 120 mV/dec and a reaction order of 1 with respect CO 2 pressure,3,11 as included in Figures S2−S3 of the Supporting Information. Note that A′ is assumed to be identical for the two electrochemical steps. For the nonelectrochemical CO desorption step, we use a rate constant given by

(6)

⎛ E ⎞ k 3 = ν exp⎜ − CO ⎟ ⎝ kBT ⎠

where {ki} are forward rate constants that include the proton concentration in the double layer for steps 1 and 2. {Ki} are equilibrium constants such that ki/Ki is the rate constant for the backward reaction. p and θ denote the pressure and surface coverage, respectively. For the electrochemical steps, the rate constants may be written as15

(11) −1

where ECO is the CO binding energy and ν = 10 s is a typical pre-exponential factor for CO desorption. This preexponential factor is chosen because a Redhead analysis assuming this factor yields a CO desorption energy of 0.61 13

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of adsorbed COOH (see Figure S1 (Supporting Information) for a free enegy diagram). However, CO evolution will always be severly limited by the rate of CO desorption, and including such a step in the kinetic model would not change the rate. As the model is not limited to metals, we assessed the activity of other known active catalysts, namely, the active sites of enzymes that interconvert CO2 and CO reversibly. The surface coverages of intermediates may in this case be understood as the fraction of enzymes with a given adsorbate under steadystate conditions. To this end, we have studied models of the C cluster in Ni− Fe containing CODH enzymes in Carboxydothermus hydrogenoformans (ChCODH II)19 and Methanosarcina barkeri (MbCODH).20 The catalytically active cluster and the surrounding ligands are largely conserved between the two enzymes.21 The model used for CODH is shown in Figure 3a.

eV from the (211) step in good agreement with our CO desorption energy of 0.62 eV.17 With the above approximations, the kinetic activity for CO evolution is determined by the adsorption energies of COOH (ΔECOOH) and CO (ΔECO), the overpotential, the difference between the applied potential and the equilibrium potential for the full reaction (η = U0tot − U), and the pressures of CO2 (pCO2) and CO (pCO). The activity at η = 0.35 V, pCO2 = pCO = 1 atm, is shown in Figure 2 as a function of ΔECOOH and ΔECO.

Figure 2. Kinetic volcano for CO evolution at a 0.35 V overpotential from the (211) step of transition metals. The transition metals fall along a trendline that does not pass over the top of the volcano. However, the noble metals are near the optimum along this trend line. The specific CO evolution current from ChCODH II and MbCODH enzyme models is comparable or better than that from the noble metals.

Figure 3. Models of the active site for CO2 activation. (a) Model of ChCODH including ligands with an inset showing the binding motif of COOH. Selected residues have been labeled. (b) The binding motif of COOH on Au(211). COOH is stabilized on CODH by additional bonding through the oxygen end of COOH compared to that for Au(211). Fe atoms are purple, Ni and Au atoms are golden, S atoms are yellow, H atoms are white, C atoms are black, O atoms are red, and N atoms are blue.

A number of relevant late transition metals have been included in the figure based on data from ref 14. In these data, the hydrogen bonds from the water above the surface have been included, as described in ref 10. The model describes the trends observed experimentally rather well.2 The noble metals Au, Ag, and Cu are the most active transition metals for CO evolution, with Au as the best. For Au and Ag, the rate is limited by CO2 activation because they weakly bind CO, if at all. On Pd, Ni, Pt, and Rh, CO2 activation and conversion to adsorbed CO is facile, and the rate is limited by the desorption of CO, caused by the strong binding. As seen in Figure 2, Cu is in the middle, binding both CO and COOH intermediately as compared to the other metals. On Cu, the model suggests an increased CO production rate when the CO pressure is lowered because that will result in a lower CO poisoning. This may explain the observation that stirring the electrolyte increases the efficiency for CO.2,18 Our model explains why no elemental metal has been found to be reversible for CO2 reduction to CO. As seen in Figure 2, all of the metals are found to be well off the maximum, the reason being that for the elemental metals, the CO and COOH adsorption energies are essentially linearly correlated. It is not possible to increase the bonding strength of COOH to the surface without also increasing the CO adsorption energy. CO and COOH primarily bind to the step site through the carbon atom, making the variation in adsorption energy of one of the species scale with that of the other when the metal is varied.14 We note that on reactive metals like Pt or Ni, CO2 dissociation may also take place directly without the formation

It contains a NiFe4S5 central cluster coordinated to cysteine residues and a histidine residue. A lysine and a histidine residue provide options for hydrogen bonding to CO and COOH and are possibly involved in proton transfers. An isoleucine residue, which has been proposed to destabilize CO, is also included in our calculations.21 The models of ChCODH II and MbCODH are based on the pdb structures 3b5219 and 3cf420, respectively, obtained from X-ray diffraction. However, we note that the structure of the active site(s) of Ni−Fe CODH is still controversial21,22 due to the presence of fractional occupations and the difficulties associated with identifying hydrogen atoms. Hydrogen atoms are initially added to the model using MolProbity.23 Additional hydrogen atoms are added to or removed from lysine, histidine, and cystine residues on the ChCODH model in order to investigate which hydrogenation states dominate near the reversible potential for CO evolution. We find that above −0.1 V versus RHE, one of the nitrogen atoms on the histidine residues (H93 and H261) is hydrogenated, the nitrogen atom on the lysine residue (K563) is doubly hydrogenated, and none of the sulfur atoms are hydrogenated. Below −0.1 V versus RHE, the lysine residue (K563) becomes triply hydrogenated, and below −0.26 V versus RHE, the cystine residue (C526) 390

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CO evolution, there is a good chance that a very good CO evolution catalyst will also have low selectivity for hydrogen. We note that the present analysis has been restricted to ambient temperature. If the temperature could be increased, the requirement of a moderate CO adsorption energy becomes less stringent, and the chances to find good catalysts will be considerably larger.

binding to the Ni atom becomes hydrogenated (see Figure S4, Supporting Information). COOH and CO binding energies were calculated on the structure that is stable above −0.1 V versus RHE. In Figure 2, we have added the COOH and CO adsorption energy points for the ChCODH II and MbCODH structures. It can be observed that both active sites are considerably more favorable on the activity volcano than the metals; the active sites of the enzymes display a significant deviation from the scaling relation between the COOH and CO adsorption energies found for the metals. The main difference between the two model enzymes from a kinetic perspective is the weaker CO binding on MbCODH, presumably caused by a different position of the isoleucine residue, which is more effective in destabilizing CO. However, we find that the stabilization from hydrogen bonding ligands is important for CODH as well. Similarly, in a computational study of CO oxidation of ChCODH, Xie and Cao found stabilization by the hydrogen bonding network to be important.24 We note that hydrogen bonding plays a similarly important role for the metal surfaces. Here, the hydrogen bonding comes from the water environment. The interconversion of CO and CO2 in an atmosphere with 0.5 atm of CO and CO2 is compared for Au(211) and ChCODH in Figure 4. The turnover frequency per site is

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METHODS Electronic structure calculations are performed using density functional theory (DFT) with the RPBE exchange correlation functional.26 All calculations of the metal surfaces are derived from ref 14. Calculations for the enzymes are carried out using the atomic simulation environment27 and the GPAW DFT code.28,29 The ionic cores are treated within the projector augmented wave method,30 and wave functions are represented on a real space grid with a grid spacing of 0.18 Å. One-electron states are occupied following a Fermi−Dirac distribution with a width of kBT = 0.05 eV, and total energies are extrapolated to kBT = 0. Nonperiodic simulation boxes with sizes of 25 × 25 × 25 Å have been used. We tested all 25 permutations of local up−down spin configurations on the metal ions of CODH in order to identify the lowest-energy spin state. Geometries are optimized until the maximum force on any atom being relaxed is less than 0.05 eV/Å. Further details are given in the Supporting Information.

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ASSOCIATED CONTENT

S Supporting Information *

Details on the computational models. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Present Address †

A.A.P.: School of Engineering, Brown University, Providence, RI 02912.

Figure 4. Turnover as a function of the applied potential for for Au(211) and ChCODH in 0.5 atm of CO and CO2, as calculated with the model in this work. On ChCODH, the turnover changes sharply through the equilibrium potential, suggesting a reversible interconversion of CO2 and CO, while a significant overpotential is required on Au(211).

Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest.

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nearly reversible for our CODH model, although our comparison does not consider that the surface density of enzymes probably will be lower than the step density of a typical gold sample. Our analysis shows that an essential design feature of a good catalyst for CO2 reduction is that the catalyst is able to stabilize COOH without stabilizing CO by a similar amount. On a metal surface with a single type of active site, this is not possible because these metals follow the scaling relation evident in Figure 2. In the enzyme, this problem is solved by having two functional sites, one that bonds the C end of CO and COOH and another element that can stabilize the O group in COOH, as shown in Figure 3a. Apart from reducing CO2 at a high rate, a good catalyst for CO2 reduction must also be selective, that is, to not use the electrons to form hydrogen. The noble metals are rather poor catalysts for hydrogen evolution.25 Because the reversible potential for hydrogen evolution is 0.1 V above the potential for

ACKNOWLEDGMENTS This work was supported by the Air Force Office of Scientific Research through the MURI program under AFOSR Award No. FA9550-10-1-0572 (H.A.H. and A.A.P.) and by the Global Climate and Energy Project (GCEP) at Stanford University (J.B.V.).

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