Article pubs.acs.org/JPCC
Computational Discovery of Nickel-Based Catalysts for CO2 Reduction to Formic Acid Zhonglong Zhao, Zhengzheng Chen, and Gang Lu* Department of Physics and Astronomy, California State University Northridge, Northridge, California 91330, United States S Supporting Information *
ABSTRACT: Electrochemical reduction of CO2 into chemical fuels is crucial to clean energy production and environment remediation. First-principles calculations are performed to elucidate reaction mechanism of CO2 reduction to formic acid on Ni-based catalysts. The origin of CO poisoning is examined and a novel design strategy is proposed to eliminate CO poisoning. Three design criteria are derived based on which computational screening is performed to identify several Ni-based near-surface-alloys (NSAs) with both high selectivity and reactivity. The effect of elastic strain on CO2 reduction is studied on these NSAs. We predict that Ni/Ti, Cu/Ni, and strained Cu/Ni NSAs could lead to highly selective and efficient production of formic acid.
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INTRODUCTION Electrochemical reduction of CO2 into chemical fuels, such as hydrocarbons, using renewable energy sources (solar, hydro, and wind) represents a promising route to mitigate our dependence on fossil fuels and to ease the threat of global warming.1−4 However, despite intense research in recent years, the discovery of efficient, selective and stable catalysts for CO2 reduction (CO2RR) still eludes us. For example, although Cu is regarded as the best monometallic catalyst, capable of producing significant quantities of hydrocarbons, it does so inefficiently with a high overpotential (∼1 V) and a poor selectivity (16 major and minor products).5−7 Formic acid (HCOOH) is one of the main products of CO2RR, and with only two proton−electron pairs in the reaction, it is also one of the simplest products. Despite its simplicity, formic acid has been found as an important fuel in fuel cells,8 a promising feedstock for fine chemicals,9 a preservative and antibacterial agent,10 and a suitable material for hydrogen storage.11 Hence it is of broad scientific and technological importance to develop catalysts that can efficiently and selectively reduce CO2 to useful products such as formic acid at low overpotentials.12−22 There are two competing reaction pathways for CO2RR to formic acid (HCOOH):13,18 H + + e−
H + + e−
H + + e−
CO2 ⎯⎯⎯⎯⎯⎯→ HCOO* ⎯⎯⎯⎯⎯⎯→ HCOOH
(3)
Because of its strong binding to the metal surface, CO*, once formed, can block active sites and hinder the reaction to HCOOH. To remove CO* from the surface, a high voltage would have to be applied, which may but not always produce hydrogen as the main product. The CO poisoning has been observed by Hori et al.23 and Kuhl et al.6 where the Faradaic yields of H2 on Ni, Pt, and Fe electrodes can reach 90%, and only 2% of the hydrocarbons are produced at an applied potential of ∼1 V vs. RHE. To alleviate CO poisoning on the transition metals, research effort has been devoted to weakening CO affinity to the surface.14,17 For example, Min et al.14 demonstrated that with a short oxidative treatment to the poisoned Pd surface, formate production can be reactivated. However, such treatment has to be performed repeatedly or the poisoning will return. Guided by theoretical predictions, Klinkova et al.17 synthesized Pd nanoparticles with high-index facets which could weaken the CO binding affinity and in turn enhance the catalytic activity. However, CO poisoning persisted and periodic surface treatments were required for a long-term performance of the catalyst. In this work, we propose an alternative strategy which deactivates the first pathway involving carboxyl. If carboxyl is no longer produced, the competing CO production (pathway 3) is no longer possible, thus CO poisoning is completely eliminated. By means of first-principles calculations, we show that this strategy can be realized in practice by modulating the free energies of the key intermediates (COOH* and HCOO*).
(1)
(2)
In the first pathway, carboxyl (COOH*, where * indicates adsorbed species) is the intermediate and in the second pathway, formate (HCOO*) is the intermediate. Among the factors that adversely affect the activity and the selectivity of the catalysts, CO poisoning stands out, particularly on transition metals, such as Fe, Co, Ni, Pd, and Pt.6,14,23,24 The poisoning © 2017 American Chemical Society
H + + e−
CO2 ⎯⎯⎯⎯⎯⎯→ COOH* ⎯⎯⎯⎯⎯⎯→ CO* + H 2O → CO
H + + e−
CO2 ⎯⎯⎯⎯⎯⎯→ COOH* ⎯⎯⎯⎯⎯⎯→ HCOOH H + + e−
results from the following reaction (pathway 3) that shares the same intermediate of carboxyl as in pathway 1:13
Received: July 13, 2017 Revised: August 21, 2017 Published: September 7, 2017 20865
DOI: 10.1021/acs.jpcc.7b06895 J. Phys. Chem. C 2017, 121, 20865−20870
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The Journal of Physical Chemistry C
Figure 1. (a) Reaction pathways for CO2 reduction to formic acid (HCOOH). (b) The free energy diagram for CO2 reduction to HCOOH on Ni (111) surface at 0 V vs. RHE. Relevant free energy differences (ΔG1, ΔG2, and ΔG3) are labeled. The same color scheme is used for parts a and b.
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RESULTS AND DISCUSSION In this work, we choose Ni as a representative of transition metal catalysts to illustrate our design strategy for CO2RR to formic acid. Figure 1a depicts the reaction pathways for HCOOH production on Ni (111) surface. The reaction pathway consisted of COOH* (HCOO*) as the intermediate is shown in black (blue) color, and labeled as route 1 (route 2) in the figure. In addition, the undesirable pathway to CO poisoning (route 3) and two branched routes to COHOH* and H2COO* are also included in Figure 1a. Although the intermediates COHOH* and H2COO* can be further reduced to hydrocarbons,13,18,41 the corresponding overpotentials are much higher, thus not examined here. The further reduction of CO* is not considered here because the Faradaic yields of its reduced products on Ni are less than 2% as reported in experiment.6 Figure 1b displays the free energy diagram for HCOOH production on Ni (111) surface at 0 V vs. RHE from firstprinciples calculations. The limiting potential required to activate each reaction step can be derived as UL = −ΔG/e according to the computational hydrogen electrode (CHE) model40 where ΔG represents the free energy difference between the two adjacent reaction steps. The calculation of the free energy can be found in Supporting Information. The most negative UL along each pathway is defined as its overpotential. Clearly, on Ni (111)surface, route 1 (black) is activated while route 2 (blue) is deactivated because the overpotential of route 1 (−ΔG1/e = −0.16 V) is less negative than that (−ΔG3/e = −0.33 V) of route 2. However, for route 1, the intermediate COOH* is reduced to CO* and H2O instead of HCOOH, owing to a large free energy drop of the former. Since CO* is strongly bound to the Ni (111) surface, its desorption would require a very high energy input (Figure 1b). Hence, the Ni surface is poisoned by CO*, and no formic acid can be produced. These results are consistent with the experimental finding that no significant amount of hydrocarbons can be detected on pure Ni electrode even at an elevated potential above 1 V.6,23 Since route 1 leads to CO poisoning, one turns to route 2 for a possible solution. Evidently, route 2 has one crucial advantage: there are no viable byproducts in this route because the only competing reaction HCOO* → H2COO* would require a very high limiting potential of 1.5 V. Thus, if route 1 is deactivated and route 2 is activated, CO poisoning would be
Following a computational screening, we predict several inexpensive Ni-based near-surface alloys (NSAs) to be more active and selective than the best performing metal catalysts for the production of formic acid. We should point out that several Ni-based catalysts have been proposed as catalysts for CO2 reduction to other products than formic acid, for example, Ni− Ga alloys for the production of methane, ethylene, and ethane,25 Ni−In alloys for CO production,26 atomic Ni on defective graphene support for methanol production,27 and atomic Ni on metal−organic frameworks support for CO production.28
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COMPUTATIONAL DETAILS
The Ni (111) surface and related NSAs were simulated with four atomic layers and a 3 × 3 in-plane supercell. A thicker sixlayer slab was also used and found to yield converged results as the four-layer model (Figure S1). The adjacent slabs were separated by a 17 Å vacuum in the normal direction of the surface. The top three atomic layers were allowed to relax while the bottom layer was fixed. The equilibrium lattice parameter of Ni was calculated as 3.526 Å. The spin-polarized DFT calculations were performed using Vienna ab initio simulation package (VASP).29 The ion-electron interaction was described by the projector-augmented wave method.30 The revised Perdew−Burke−Ernzerhof (RPBE) functional was used for the exchange-correlation potential.31,32 RPBE+U (U = 1 eV) method33 was employed to minimize the self-interaction error and yielded the magnetic moment of Ni as 0.66 μB, same as the experimental value.34,35 A plane-wave energy cutoff of 400 eV was used for all calculations and the Brillouin-zone was sampled with a 3 × 3 × 1 k-mesh according to the Monkhorst−Pack scheme.36 Ab initio MD simulations were performed using NVT (Number of particles, Volume, Temperature) ensemble37−39 and the Brillouin zone integration was restricted to the Γ point. The computational hydrogen electrode (CHE) model40 was used to calculate the free energy diagrams. In the CHE model, the chemical potential of a proton−electron pair is defined in equilibrium with half of that of gaseous H2 at U = 0 V, 101325 Pa, any pH values and temperatures. The chemical potential is shifted by − eU (e is the elementary positive charge) when an external potential U is applied to the system. Details about the free energy calculations can be found in the Supporting Information. 20866
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Figure 2. Free energy change between the reaction steps (ΔG1, CO2 → COOH*; ΔG2, CO2 → HCOO*; ΔG3, HCOO* → HCOOH) on (a) Nibased NSAs, Cu (211) and Ni (111) surfaces, and (c) strained Cu*/Ni as a function of the free energy of HCOO*. The NSAs above zero meet the two selectivity criteria as indicated by solid symbols. The corresponding volcano plots via route 2 are shown in parts b and d. Schematics for the overlayer (M*/Ni) and the subsurface (Ni/M) NSAs are shown in the insets of part b. Blue and gray spheres denote the M atoms and Ni, respectively.
The relative stability of M*/Ni and Ni/M NSAs can be evaluated based on segregation energy (Eseg), defined as the energy difference between NSAs with an M atom substituting for a Ni atom in the subsurface and the surface.44 If Eseg is negative, the M atom would prefer to segregate to the surface (M*/Ni); conversely, it would prefer to segregate to the subsurface (Ni/M). Based on Eseg, we can narrow down Nibased NSAs which are energetically stable (Table S1). Furthermore, it has been suggested that the presence of strongly adsorbed species could destabilize the NSA surface.42 Hence, we perform additional screening by fully relaxing the atomic geometries of the NSAs with HCOO* and COOH* on the surfaces. We have thus identified six stable Ni-based NSAs (Ni/Ti, Ni/V, Ni/Cr, Ni/Co, Cu*/Ni, and Ni/Mo) which show no substantial surface reconstruction. Lastly, we carry out ab initio molecular dynamics (MD) simulations at 300 K to examine dynamical stability of these six NSAs with HCOO* on the surfaces. We find that the NSAs remain stable during the MD simulations, as evidenced by negligible changes in the radial distribution functions (Figure S2). After establishing the thermodynamic stability of the NSAs, we proceed to examine their selectivity and activity. As shown in Figure 2a, we find that Ni/Cr, Ni/Mo, Ni/Ti, and Cu*/Ni meet the selectivity criteria as their corresponding data points are above zero. The remaining alloys satisfy only one of the two criteria. The overpotentials of the NSAs are displayed in Figure 2b. Among the four NSAs meeting the selectivity criteria, Cu*/Ni and Ni/ Ti have the lowest overpotentials; thus, they are predicted as the most promising catalysts for the production of formic acid. In particular, Cu*/Ni is the most selective catalyst with the maximum free energy differences, while Ni/Ti is the most active catalyst with the lowest overpotential.
eliminated and formic acid would be the only product. More specifically, we require that the first step in route 1, i.e., the formation of COOH* be turned off, while both steps in route 2 must be turned on. To satisfy both requirements, we must have ΔG1 − ΔG2 > 0
(4)
ΔG1 − ΔG3 > 0
(5)
Catalysts satisfying both conditions (selectivity criteria) are predicted to produce formic acid without CO poisoning. Now that route 2 is activated, the next step is to minimize its overpotential. This can be achieved by meeting the following condition (activity criterion):
ΔG2 = ΔG3
(6)
This equation is derived by noting that the overpotential is the larger of ΔG2 and ΔG3. The three criteria provide a guidance to computationally screen Ni-based catalysts for HCOOH production with a low overpotential and a high selectivity. In the following, we focus on Ni-based NSAs that meet the selectivity and the activity criteria. A total of 27 alloy elements M (M = Sc, Ti, V, Cr, Mn, Fe, Co, Cu, Zn, Y, Zr, Nb, Mo, Tc, Ru, Rh, Pd, Ag, Cd, Hf, Ta, W, Re, Os, Ir, Pt, Au) have been considered in this work. A monolayer of M is introduced either to the surface layer (M*/Ni) or the subsurface layer (Ni/M) on Ni (111) surface. We note that bimetallic NSAs composed of diverse metal elements have been previously synthesized. For example, electrodeposition of Cu on Pt (111) could yield both Cu*/Pt and Pt/Cu NSAs depending on annealing temperature.42 Similarly, electrodeposition of Au on polycrystalline W produced Au*/W NSAs with controllable Au layers.43 Hence our design strategy can be realized in practice. 20867
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Figure 3. Free energy diagrams for CO2 electroreduction to HCOOH on (a) Ni/Ti, (b) Cu*/Ni, and (c) strained (εXY = +3%) Cu*/Ni NSAs at 0 V vs. RHE.
strength and the d-band center has also been observed in other metal catalysts.50,58 The overpotentials for route 2 on Ni/Ti and strained Cu*/Ni are calculated as −0.15 and −0.14 V, respectively. These NSAs are predicted to be more active than some of the most efficient catalysts for HCOOH production, including partially oxidized and atomically thin Co layers (−0.24 V),16 Fe carbonyl cluster (−0.23 ∼ − 0.44 V),15 Pd nanoparticles (NPs) with high-index facets (−0.20 V),17 and Pd NPs dispersed on a carbon support (−0.20 V).14 Finally, we examine hydrogen evolution reaction (HER) on these NSAs. A superb catalyst for CO2RR should possess a high overpotential for HER to minimize the consumption of protons and electrons. Hence, the catalyst should have either a very strong or very weak binding to H*. Between the two, the weak binding of H* is more desirable so that H* will not poison the surface.59 As shown in Figure 4, we find that the predicted NSAs exhibit weak binding to H* (or large positive free energy), leading to suppressed HER. More specifically, Ni/Ti and Cu*/Ni are predicted to have the most negative overpotentials for HER (−0.08 and −0.12 V). In comparison, the HER overpotential on Cu (211) surfaces is only −0.03 V. However, we note that the overpotentials for HER on the proposed NSAs are slightly (∼0.08 V) less negative than those for HCOOH production, which means that HER is a still major competing reaction. The weak H* binding on the proposed NSA surfaces can also be understood from the downshift of the d-band center as mentioned above. A previous work by Liu et al.60 showed that the overpotential for HER on small metal clusters could be increased by employing a defective graphene support which modified the electronic structure of the active sites.
It is well-known that elastic strains can influence adsorbate binding energy on a catalyst surface, thus change its catalytic activity.45−47 Recently, there is a surge of interest to optimize the performance of metal catalysts by tuning the strain on the catalyst surface.48−57 The elastic strain can be applied to the catalysts directly via mechanical loading48,49 or indirectly via lattice mismatch in core/shell nanostructures (e.g., nanoparticles and nanoplates).51−57 Although CO2RR on the core/shell nanostructures is beyond the scope of this work, the analogy between NSAs and multimetallic core/shell nanostructures prompts us to examine how strain may modulate the selectivity and the reactivity of the NSAs. To this end, biaxial tensile and compressive strains, εXY, are applied to Cu*/Ni surface in ⟨110⟩ and ⟨211⟩ directions. As shown in Figure 2d, we find that +3% biaxial tensile strain leads to the lowest overpotential, while the selectivity drops slightly (Figure 2c). Hence, the biaxial tensile strain is beneficial to Cu*/Ni catalyst. Since it is generally believed that the catalysts on the opposite legs of the volcano plot tend to have opposite responses to strain, we speculate that Ni/Mo may become more active under appropriate compressive strains. In Figure 3, we summarize the free energy diagrams for the production of formic acid on strain-free Ni/Ti and Cu*/Ni surfaces, as well as strained (εXY = +3%) Cu*/Ni surface. Clearly, route 2 is now strongly preferred, and route 1 is effectively deactivated. As a result, CO poisoning is eliminated on the three surfaces. It is evident from Figure 3 that the deactivation of route 1 on the proposed NSAs is due to an increase of the COOH* free energy, which corresponds to a weakened adsorption on the surfaces. The weaker adsorption can be understood from a downshift of the d-band center in the local density of states (dxz, dyz, and dz2 components) of the surface atoms in the NSAs as compared to that in pure Ni (Figure S3). Note that this correlation between the adsorption 20868
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Figure 4. Free energy diagram for HER on various NSA surfaces at 0 V vs. RHE. The adsorption geometries are shown in the insets. The pink and gray spheres represent H and metals, respectively.
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CONCLUSIONS In summary, we have performed first-principles calculations to elucidate the reaction mechanism of CO2RR to formic acid on Ni-based catalysts. We revealed the origin of CO poisoning on the metal surface and proposed a strategy to eliminate CO poisoning by activating the HCOO* pathway and deactivating the competing COOH* pathway. Three design criteria were derived based on which computational screening was performed to identify the Ni-based NSAs with high selectivity and reactivity. The effect of elastic strain on CO2RR was examined on these NSAs. We predicted that Ni/Ti, Cu*/Ni, and strained Cu*/Ni surfaces could lead to highly selective and efficient production of formic acid. It is hoped that this work could inspire future discovery of superior catalysts for CO2RR.
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ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcc.7b06895. Detailed information regarding the free energy calculations, NSA segregation energies, and supporting figures (PDF)
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AUTHOR INFORMATION
Corresponding Author
*(G.L.) E-mail:
[email protected]. ORCID
Zhonglong Zhao: 0000-0002-2245-9045 Zhengzheng Chen: 0000-0002-4911-9649 Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS This work was supported by the Office of Naval Research (N00014-15-1-2092) and National Science Foundation (DMR1205734).
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DOI: 10.1021/acs.jpcc.7b06895 J. Phys. Chem. C 2017, 121, 20865−20870
