First-Principles Insight into Electrocatalytic Reduction of CO2 to CH4

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C: Surfaces, Interfaces, Porous Materials, and Catalysis

First Principles Insight into Electrocatalytic Reduction of CO to CH on a Copper Nanoparticle 2

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Huilong Dong, Youyong Li, and De-en Jiang J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b01928 • Publication Date (Web): 11 May 2018 Downloaded from http://pubs.acs.org on May 12, 2018

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First Principles Insight into Electrocatalytic Reduction of CO2 to CH4 on a Copper Nanoparticle

Huilong Dong,*,†,‡ Youyong Li,*,† and De-en Jiang*,‡



Institute of Functional Nano & Soft Materials (FUNSOM), Soochow University,

Suzhou, Jiangsu 215123, China ‡

Department of Chemistry, University of California, Riverside, California 92521,

United States

Corresponding Authors * E-mail: [email protected]; [email protected]; [email protected]

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ABSTRACT Copper has been extensively studied for electrocatalytic CO2 reduction reaction (CO2RR) due to its unique capability to produce hydrocarbons at high overpotentials. Although CO2RR on crystallographic Cu surfaces such as Cu(211) and Cu(111) has been investigated by many, the detailed mechanistic understanding of CO2RR on small Cu nanoparticles (NP) is still lacking. In this work, we use Cu79 as a representative NP and compare with Cu(211) and Cu(111) for reduction of CO2 to CH4 by first principles calculations. The computed free energy profiles show that the Cu79 NP exhibits less negative onset potential for the formation of CO than both Cu(211) and Cu(111) but more negative onset potential for the formation of CH4 than Cu(211). These onset potential trends for CO and CH4 formations on Cu79 NP, Cu(211), and Cu(111) are correlated with adsorption energetics of the key reaction intermediates including COOH, CO, CHO. The insight may help improve the performance of Cu NPs for CO2RR to CH4.

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INTRODUCTION The electrochemical reduction of CO2 into value-added hydrocarbons or alcohols is a promising way to produce useful fuels and renewable energy sources.1-3 Although great efforts have been devoted to the screening of efficient electrocatalysts,4-9 copper is still the only transition metal found to exhibit capability of reducing CO2 to alcohols and hydrocarbons at reasonable faradaic efficiencies.10-12 Based on the experimental observation of Hori et al.,13-15 more and more theoretical investigations have been performed to understand why Cu excels over other metal electrodes for the CO2 reduction reaction (CO2RR).8-9, 11, 16-19 The efficient catalysis on the protonation of adsorbed CO to adsorbed CHO has been pointed out as the origin of the unique capability of Cu surface in reduction of CO2.8 Among different low-Miller-index surfaces, the Cu(211) surface is revealed as the most active one, with most of the hydrocarbon formation taking place on the stepped sites.16-17 Comparing with the well-studied Cu surfaces, the mechanisms of electrocatalytic CO2RR on Cu nanoparticles (NPs) are much less investigated. The very small Cu nanoclusters (such as Cu29 and Cu4)20-21 were predicted to be able to reduce CO2 to methanol in thermal catalysis with considerably low activation energies from density functional theory (DFT) calculations. A theoretical study of electrochemical CO2RR found that a defective graphene support could significantly improve CO2 conversion with lower limiting potential than the isolated Cu55 NP.22 Several experimental investigations have examined Cu NPs of different sizes.23-25 Particularly, Reske et al.24 prepared the size-controlled Cu NPs within the range of 2−15 nm and analyzed their catalytic activity and selectivity for CO2 electroreduction. For Cu NPs below 5 nm, they found a dramatic increase in the catalytic activity and selectivity for CO. However, the mechanism is unclear. Despite the many studies of Cu surfaces and NPs for electrocatalytic CO2RR, an in-depth computational investigation of the mechanism on the Cu NPs in comparison with that on the Cu surfaces is missing. This comparison is especially desirable given the rich sites on a NP surface such as corners and edges. In this work, we use the Cu79 NP as a model structure to elucidate the microscopic mechanism of CO2RR and ACS Paragon Plus Environment

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compare it with the common Cu surfaces. This work will pave the way for further studying the Cu NPs as electrocatalysts for CO2RR and for improving their catalytic performance through surface modification or composition modulation.

COMPUTATIONAL METHOD Spin-polarized DFT calculations were carried out by the Vienna ab initio simulation package (VASP).26-27 The ion-electron interaction was described by the projected augmented wave (PAW)28 method. Electron exchange-correlation was represented by the Perdew-Burke-Ernzerhof (PBE) functional.29 A cutoff energy of 400 eV was employed for the plane-wave basis set, which has been tested to ensure convergence of the total energy. The Grimme’s method (DFT-D3)30 was included for the van der Waals’ interaction during surface adsorption. The convergence threshold for structural optimization was set as 0.03 eV/Å in force. Partial atomic charges were obtained using the Bader charge analysis.31 The Cu79 NP was constructed by cutting from the bulk Cu and placed in a 40×40×40 Å3 cubic cell, large enough to minimize the interaction from periodical images. For adsorption on the Cu79 NP, only the Gamma-point was adopted for sampling the Brillouin zone. The Cu(111) and Cu(211) surfaces were modelled with a slab of four atomic layers and a vacuum layer of about 20 Å along the z-axis; their Brillouin zones were sampled by a 5×5×1 Monkhorst–Pack k-point mesh.32 The explicit salvation effect reflects the contribution of solvation to the free energies and is thus essential in determining the mechanism of CO2 electro-chemical reduction and has been widely adopted in previous theoretical investigations.16, 18, 33-36 Here we adopt the solvation energy values as reported by Calle-Vallejo and Koper,33 which estimates the energies of some adsorption intermediates stabilized by the water layer covered on the surface. That is, -0.38 eV for all the OH-contained groups (*R-OH, where R is the hydrocarbon chain), -0.10 eV for CO* and CHO*, and -0.50 eV for OH*. Considering the similar binding characteristics of Cu79 NP in binding of intermediates with Cu(211)/Cu(111) surfaces, we also use the same solvation energy values for reaction intermediates on Cu79 NP. Similar treatment for explicit salvation ACS Paragon Plus Environment

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effect on curved surface was also reported by other work.37 We then computed the Gibbs free energy for each reaction step as G =  + ZPE − T∆S +  +  , where Etotal is the total energy, ZPE is the 

zero-point-energy for the adsorbed species ( = ∑ ℏ), and ∆S is the difference  in entropy. T was set as 18.5 ℃ to permit comparison with the experimental results.14 GpH was calculated as kT×pH×ln10, where pH is at 0. For liquid-phase products, an additional free-energy correction was included (-0.09 eV for H2O and -0.12 eV for HCOOH).38 Adsorption energy (Eads) is used to evaluate the binding strength of surface adsorbate:  =  + ∗ − ∗ , where X, *, and X* represents the adsorbate, substrate, and the adsorption system, respectively. By this definition, more positive Eads means stronger binding. To evaluate the applied potential needed to effect the reactions, reversible hydrogen electrode (RHE) is used as the reference. According to the computational hydrogen electrode (CHE) model,39 the chemical potential of a proton–electron pair at 0 V (vs RHE) is defined equal to half of the chemical potential of molecular hydrogen at all temperatures and 1.01×105 Pa.

RESULTS AND DISCUSSION Structure of the Cu79 NP. The Cu79 NP is about 1.1 nm in diameter (Figure 1), close to the smallest Cu NP used for CO2 reduction in experiments (d = 1.9 nm).24 The presence of different surface sites on Cu79 NP makes it a good model for studying the microscopic mechanism of CO2 reduction. The optimized Cu79 NP exhibits Pm-3m symmetry with 4 layers of atoms (Figure 1a). The surface of Cu79 NP is composed of eight (111) facets and six (100) facets (Figure 1b). There are three types of surface Cu atoms: 24 (111) facet atoms (black circles in Figure 1c), 24 corner atoms (blue circles in Figure 1c), and 12 edge atoms (green circles in Figure 1c). We found from the Bader charge analysis that the facet atoms carry positive charge (+0.03 |e|) while the other surface atoms have negative charges, especially the corner atoms (-0.07 |e|).

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Figure 1. (a) Structure of Cu79 NP; different color indicates atoms in different layers. (b) The polyhedron structure of Cu79 NP with the (111) and (100) facets marked. (c) Different types of Cu atoms on Cu79 NP with their Bader charges: C, corner sites; E, edge sites; F: (111) facet sites.

The coordination numbers (CN) of surface metal atoms have been considered as a vital factor in determining the binding of surface adsorbates.24 Based on the CN of the surface Cu atoms, we divided the surface sites of Cu79 NP into low CN zone (the E and C atoms) and high CN zone (the F atoms). The former can be compared with the edge sites of the Cu(211) surface, while the latter with the Cu(111) surface, as shown in Figure 2. Below we will first examine CO2RR to CH4 on Cu79 NP and then compare the reaction energetics with that on Cu(211) and Cu(111).

Figure 2. Comparison of surface sites on (a) Cu(211) surface, (b) Cu79 NP, and (c) Cu(111) according to the coordination number (CN). Green circles denote the low CN sites on Cu(211) and Cu79; blue circles denote the high-CN facet sites on Cu(111) and Cu79.

Adsorption of reaction intermediates on the Cu79 NP. Previous theoretical studies of electrocatalytic reduction of CO2 to C1 products on Cu surfaces have identified important intermediates and products, including CO, HCOOH, HCHO, CH3OH, CH4 and H2O.8-9, 16-17 So we first examined their adsorption on the different sites of the ACS Paragon Plus Environment

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Cu79 NP surface. The most stable adsorption configurations are shown in Figure 3, together with the corresponding adsorption energies (Eads). One can see that HCOOH, HCHO, and CH3OH prefer to adsorb at the corner atoms, while CO2 and CH4 prefer to weakly adsorb on the center of the (111) facet. CO strongly adsorbs on a hollow site next to the periphery of the (111)/(100) edge. Eads results show that CO adsorption is strongest, followed by HCHO and CH3OH. It is easy to see that the low-CN sites (corner and edges) are highly active for binding of the main intermediates. Additionally, the adsorption of CO, HCHO and CH3OH on Cu(211) and Cu(111) is also listed as comparison in Table 1.

Figure 3. The most stable adsorption configurations on Cu79 for (a) CO2, (b) CO, (c) HCOOH, (d) HCHO, (e) CH3OH, (f) CH4 and (g) H2O. Corresponding adsorption energies (Eads) are also given.

Table 1. Adsorption energies (Eads, in eV) of CO, HCOOH, HCHO, and CH3OH on Cu79, Cu (211), and Cu (111).

Cu79

Eads (CO)

Eads (HCHO)

Eads (CH3OH)

1.39

0.85

0.71

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Cu (211)

1.23

0.76

0.72

Cu (111)

0.98

0.34

0.61

CO2 reduction reaction on the Cu79 NP. From adsorption energetics, we next investigated the mechanisms of reduction of CO2 to CH4 on the Cu79 NP. Figure 4a shows the possible reaction pathways. Previous theoretical studies by Nørskov et al. have suggested that CHOH* and CH* should be included in the most likely pathway of CO2 to CH4 on copper surface from the proton−electron transfer barriers,11, 36 thus the reaction pathway can be summarized as CO2+* → COOH* → CO*+H2O → CHO* → CHOH* → CH*+H2O → CH2* → CH3* → *+ CH4 (* denotes an active site) at high negative potential. Here we assumed that the Cu NPs share the same dominant reaction pathway, and the free energy profiles for this likely pathway and another major competing one via the HCOO* intermediate are shown in Figure 4. One can see that although HCOO* is energetically more favorable than COOH* for the first step of CO2 RR via proton reduction, the subsequent step via COOH* (COOH*→CO*) is more favorable than via HCOO* (HCOO*→HCOOH*). In other words, we predict from the free-energy profiles that CO is the main product over HCOOH for two-electron reduction of CO2 on the Cu79 NP. Moreover, Figure 4 shows that further reduction of CO most likely proceeds via a CHO* intermediate which is 0.86 eV uphill in free energy, instead of a COH* intermediate which is over 1.10 eV uphill.

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Figure 4. Free energy profiles (∆G) of major pathways of CO2 reduction to CH4 on Cu79 NP. The black line shows the most likely reaction pathway. The total free energy of [*+CO2+8(H++e-)] is set as the energy reference.

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Figure 5. Free energy diagrams of the most likely reaction pathway on (a) Cu (211), (b) Cu79, and (c) Cu (111), under different potentials (black lines, zero potential; blue lines, onset potential for CO formation; magenta lines, onset potential for CH4 formation. For all the profiles, the corresponding total free energy of [*+CO2+8(H++e-)] is set as the energy reference.

Comparison of CO2RR on Cu79 and Cu surfaces. One of the main goals of this work is to compare Cu NP and Cu surfaces for CO2RR. Figure 5 shows the ACS Paragon Plus Environment

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comparison of the free-energy profiles among Cu(211), Cu(111), and Cu79 NP. Two elementary steps (CO2+*→COOH* and CO*→CHO*) are considered as the potential limiting steps.9 According to our results, the onset potentials of CO and CH4 formation are -0.39 V and -0.70 V, respectively, on Cu(211) (Figure 5a). Previous experimental investigations on electrochemical reduction of CO2 at Cu electrode14 found an onset potential of about -0.4 V for CO evolution and an onset potential of about -0.8 V for CH4 production, while previous simulations16 found that Cu(211) surface has -0.41 V onset potential for CO formation and -0.74 V for CH4 formation. Our results for Cu(211) are consistent with both previous experiment and simulations. Compared with the Cu(211) surface, the Cu79 NP (Figure 5b) shows less negative onset potential for CO formation (-0.34 V) but more negative onset potential for CH4 formation (-0.86 V). In contrast, the Cu(111) surface (Figure 5c) requires more negative potentials to produce CO and CH4 than Cu(211) and Cu79 do. In short, Cu79 NP is predicted to be more active for CO production but less active for CH4 production than Cu(211). This is consistent with the experimental observation that on the small Cu NPs (with diameter less than 5 nm), the CO selectivity is significantly higher than that on Cu surfaces.24 It should be pointed out that though Cu79 NP has better selectivity for CH4 formation than Cu(111), there is no conflict with the fact that Cu foil can produce more CH4 than Cu NP experimentally. There are several reasons that might explain this point. First, Cu foil can expose several various facets that have different activities. As have been reported, the Cu(211) surface is more active than Cu(111) with lower onset potential for both CO and CH4 formation.16, 40 Second, we have explored only the initial steps of CO2 reduction on the Cu NPs; more complicated pathways need to be explored (especially the formation of C2 products), in order to directly compare with the experimental data. Third, there are still controversies regarding the reduction mechanisms, e.g., the role of the bicarbonate ion,41 so more complicated pathways may need to be taken into account in the computational modeling to fully address the experimental conditions.

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Figure 6. The most stable adsorption configurations of key adsorbates (COOH, CO, and CHO) on Cu79, Cu(211), and Cu (111), with their corresponding Eads.

Adsorption energy trend. To elucidate the relationship between adsorption performance and onset potential, the adsorption configurations of the key intermediates (COOH, CO and CHO) on Cu79 NP, Cu(211), and Cu(111) are compared in Figure 6. The adsorption of CHO on Cu79 NP and Cu (211) shows similar geometry, with the C-O bond binding side-on a Cu-Cu edge, leading to very close Eads (2.39 eV and 2.36 eV). In contrast, CHO has to bind on top of a single Cu atom on Cu(111) due to steric effect, resulting weaker adsorption. The other key difference among Cu79 NP, Cu(211), and Cu(111) is that COOH and CO adsorptions are strongest on Cu79 NP. For the onset potential of CO formation, we find that the adsorption energy of COOH plays the vital role. There exists a linear correlation (Figure 7a) between Eads (COOH) and onset potential of CO formation because the formation of COOH* is the potential-limiting step for formation of CO* (Figure 4b). Meanwhile, onset potential of CH4 formation is found to be correlated with the adsorption energy difference between adsorbed CHO and CO, as shown in Figure 7b. In other words, enlarging the Eads difference between CHO and CO could facilitate CH4 formation. This is reasonable in that CO  CHO step is the potential-limiting step for CH4 formation ACS Paragon Plus Environment

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(Figure 4).

Figure 7. (a) The linear relationship between onset potential of CO formation and Eads (COOH); (b) the linear relationship between onset potential of CH4 formation and [Eads (CHO) - Eads (CO)] with different substrates.

Adsorption on nanoparticles with different sizes. Besides Cu79, we also calculated the adsorption energies of key intermediates (CO* and CHO*) on other nanoparticles with different sizes for comparison. The calculation results in Table 2 show that for Cu55~Cu147, the [Eads (CHO) - Eads (CO)] value gradually increases with the size increases. As shown in Figure 8, it is clear that from Cu55, Cu79 to Cu147 there exists a size dependence in catalytic activity, with gradually increasing onset potential of CO and decreasing onset potential of hydrocarbons. The free energy diagrams indicate that Cu79 has little difference in catalytic activity comparing with the Cu147. Considering the rich active sites on the surface of Cu79, the moderate size, as well as much less computational cost than Cu147, we believe that Cu79 could act as a good representative for ultra-small Cu NPs in catalyzing CO2RR. The Cu38 is totally different from the larger NPs. Though it has a very large [Eads (CHO) - Eads (CO)], the Cu38 shows a higher selectivity to HCOOH rather than CO due to the lower ∆G (HCOOH*) than ∆G (CO*) (see Figure 8), thus is unfavorable for formation of hydrocarbons.

Table 2. The Eads (eV) of CO and CHO on different Cu NPs, together with the corresponding [Eads (CHO) - Eads (CO)] values. The onset potentials for formation of CO (ηCO) and CH4 (ηCH4)

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are also listed (unit in V). Eads (CHO) Eads (CO) Eads (CHO) - Eads (CO)

ηCO

ηCH4

-

-

Cu38

2.47

0.83

1.64

Cu55

2.36

1.38

0.98

0.33 0.94

Cu79

2.39

1.39

1.00

0.34 0.86

Cu147

2.54

1.49

1.05

0.36 0.83

Figure 8. The free energy diagrams of (a) Cu38, (b) Cu55 and (c) Cu147 in catalyzing CO2RR for the initial steps.

CONSLUSIONS In this work, we performed DFT calculations on mechanistic understanding of electrocatalytic reduction of CO2 into CH4 on Cu79 NP, which acts as a representative model for small Cu nanoparticles. The Cu79 NP shows stronger binding with the reaction intermediates than the Cu(111) and Cu(211) surface. Analyzing from the free energy diagrams, we found that the Cu79 NP possesses less negative onset potential for the formation of CO than both Cu(211) and Cu(111) but more negative onset potential for the formation of CH4 than Cu(211). The trend of the onset potentials are correlated with adsorption energetics of COOH, CO, and CHO. This work shows that small Cu NP tends to produce CO and that a strategy to improve CH4 formation on Cu NP is to increase the adsorption energy difference between CO and CHO.

ACKNOWLEDGMENTS This work is supported by the Ministry of Science and Technology of China (Grants No. 2017YFA0204802 and 2017YFB0701601), the National Natural Science

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Foundation of China (Grants No. 51761145013, 21673149 and 21703145), China Postdoctoral Science Foundation (Grant No. 2017M611892), and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). H.D. acknowledges the financial support from Collaborative Innovation Center of Suzhou Nano Science and Technology. D.J. is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division.

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19. Akhade, S. A.; Luo, W.; Nie, X.; Asthagiri, A.; Janik, M. J., Theoretical Insight on Reactivity Trends in CO2 Electroreduction across Transition Metals. Catal. Sci. Technol. 2016, 6, 1042-1053. 20. Yang, Y.; Evans, J.; Rodriguez, J. A.; White, M. G.; Liu, P., Fundamental Studies of Methanol Synthesis from CO2 Hydrogenation on Cu(111), Cu Clusters, and Cu/ZnO(0001). Phys. Chem. Chem. Phys. 2010, 12, 9909-9917. 21. Liu, C.; Yang, B.; Tyo, E.; Seifert, S.; DeBartolo, J.; von Issendorff, B.; Zapol, P.; Vajda, S.; Curtiss, L. A., Carbon Dioxide Conversion to Methanol over Size-Selected Cu4 Clusters at Low Pressures. J. Am. Chem. Soc. 2015, 137, 8676-8679. 22. Lim, D.-H.; Jo, J. H.; Shin, D. Y.; Wilcox, J.; Ham, H. C.; Nam, S. W., Carbon Dioxide Conversion into Hydrocarbon Fuels on Defective Graphene-Supported Cu Nanoparticles from First Principles. Nanoscale 2014, 6, 5087-5092. 23. Baturina, O. A.; Lu, Q.; Padilla, M. A.; Xin, L.; Li, W.; Serov, A.; Artyushkova, K.; Atanassov, P.; Xu, F.; Epshteyn, A.; et al., CO2 Electroreduction to Hydrocarbons on Carbon-Supported Cu Nanoparticles. ACS Catal. 2014, 4, 3682-3695. 24. Reske, R.; Mistry, H.; Behafarid, F.; Roldan Cuenya, B.; Strasser, P., Particle Size Effects in the Catalytic Electroreduction of CO2 on Cu Nanoparticles. J. Am. Chem. Soc. 2014, 136, 6978-6986. 25. Li, Q.; Zhu, W.; Fu, J.; Zhang, H.; Wu, G.; Sun, S., Controlled Assembly of Cu Nanoparticles on Pyridinic-N Rich Graphene for Electrochemical Reduction of CO2 to Ethylene. Nano Energy 2016, 24, 1-9. 26. Kresse, G.; Furthmüller, J., Efficient Iterative Schemes for Ab Initio Total-Energy Calculations Using a Plane-Wave Basis Set. Phys. Rev. B 1996, 54, 11169-11186. 27. Kresse, G.; Joubert, D., From Ultrasoft Pseudopotentials to the Projector Augmented-Wave Method. Phys. Rev. B 1999, 59, 1758-1775. 28. Blöchl, P. E., Projector Augmented-Wave Method. Phys. Rev. B 1994, 50, 17953-17979. 29. Perdew, J. P.; Burke, K.; Ernzerhof, M., Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865-3868. 30. Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H., A Consistent and Accurate Ab Initio Parametrization of Density Functional Dispersion Correction (DFT-D) for the 94 Elements H-Pu. J. Chem. Phys. 2010, 132, 154104. 31. Henkelman, G.; Arnaldsson, A.; Jónsson, H., A Fast and Robust Algorithm for Bader Decomposition of Charge Density. Comput. Mater. Sci. 2006, 36, 354-360. 32. Monkhorst, H. J.; Pack, J. D., Special Points for Brillouin-Zone Integrations. Phys. Rev. B 1976, 13, 5188-5192. 33. Calle℃Vallejo, F.; Koper, M., Theoretical Considerations on the Electroreduction of CO to C2 Species on Cu (100) Electrodes. Angew. Chem. 2013, 125, 7423-7426. 34. Liu, S. P.; Zhao, M.; Gao, W.; Jiang, Q., Mechanistic Insights into the Unique Role of Copper in CO2 Electroreduction Reactions. ChemSusChem 2017, 10, 387-393. 35. Cheng, T.; Xiao, H.; Goddard III, W. A., Free-Energy Barriers and Reaction Mechanisms for the Electrochemical Reduction of CO on the Cu (100) Surface, Including Multiple Layers of Explicit Solvent at Ph 0. J. Phys. Chem. Lett. 2015, 6, 4767-4773. 36. Shi, C.; Chan, K.; Yoo, J. S.; Nørskov, J. K., Barriers of Electrochemical CO2 Reduction on Transition Metals. Org. Process Res. Dev. 2016, 20, 1424-1430. 37. Zhu, G.; Li, Y.; Zhu, H.; Su, H.; Chan, S. H.; Sun, Q., Curvature-Dependent Selectivity of CO2 Electrocatalytic Reduction on Cobalt Porphyrin Nanotubes. ACS Catal. 2016, 6, 6294-6301.

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38. Tang, Q.; Lee, Y.; Li, D.-Y.; Choi, W.; Liu, C.; Lee, D.; Jiang, D.-e., Lattice-Hydride Mechanism in Electrocatalytic CO2 Reduction by Structurally Precise Copper-Hydride Nanoclusters. J. Am. Chem. Soc. 2017, 139, 9728-9736. 39. Nørskov, J. K.; Rossmeisl, J.; Logadottir, A.; Lindqvist, L.; Kitchin, J. R.; Bligaard, T.; Jónsson, H., Origin of the Overpotential for Oxygen Reduction at a Fuel-Cell Cathode. J. Phys. Chem. B 2004, 108, 17886-17892. 40. Hori, Y.; Takahashi, I.; Koga, O.; Hoshi, N., Electrochemical Reduction of Carbon Dioxide at Various Series of Copper Single Crystal Electrodes. J. Mol. Catal. A-Chem. 2003, 199, 39-47. 41. Dunwell, M.; Lu, Q.; Heyes, J. M.; Rosen, J.; Chen, J. G.; Yan, Y.; Jiao, F.; Xu, B., The Central Role of Bicarbonate in the Electrochemical Reduction of Carbon Dioxide on Gold. J. Am. Chem. Soc. 2017, 139, 3774-3783.

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