ACS Publications. Most Trusted. Most Cited. Most Read
My Activity
CONTENT TYPES

Figure 1Loading Img

Active and Selective Ensembles in Oxide-Derived Copper Catalysts for CO2 Reduction

Cite this: ACS Energy Lett. 2020, 5, 10, 3176–3184
Publication Date (Web):September 22, 2020
https://doi.org/10.1021/acsenergylett.0c01777

Copyright © 2020 American Chemical Society. This publication is licensed under these Terms of Use.

  • Open Access

Article Views

8642

Altmetric

-

Citations

LEARN ABOUT THESE METRICS
PDF (4 MB)
Supporting Info (1)»

Abstract

Copper catalysts are unique in CO2 reduction as they allow the formation of C2+ products. Depending on the catalysts’ synthesis, product distribution varies significantly: while Cu nanoparticles produce mainly methane and hydrogen, oxide-derived copper leads to ethylene and ethanol. Here, by means of ab initio molecular dynamics on oxygen-depleted models, we identified the ensembles controlling catalytic performance. Upon reconstruction and irrespective of the starting structure, recurrent patterns defined by their coordination and charges appear: metallic Cu0, polarized Cuδ+, and oxidic Cu+. These species combine to form 14 ensembles. Among them, 4-(6-)coordinated Cu adatoms and Cu3δ+O3 are responsible for tethering CO2, while metastable near-surface oxygens in fcc-(111) or (100)-like Cu domains promote C–C bond formation via glyoxylate species, thus triggering selective C2+ production at low onset potentials. Our work provides guidelines for modeling complex structural rearrangements under CO2 reduction conditions and devising new synthetic protocols toward an enhanced catalytic performance.

CO2 reduction (CO2R) has emerged as a suitable way to store renewable energy as chemical bonds. (1−3) Copper has a unique ability to promote C–C coupling toward C2+ products, (4) which are among the most sought-after chemicals. (5) Under reaction conditions, most copper-based catalysts reconstruct because of reaction intermediates and surface polarization caused by the applied electric potential. (6−9) As a consequence, the sample’s history affects the activity, selectivity, and stability of the catalyst (6,10,11) (Table S1). In particular, polycrystalline Cu generates mainly CO, HCOOH, HCOO, H2, and CH4 at potentials more reductive than −0.8 V vs RHE, (12−15) while (110) and (111) steps nearby (100) terraces are selective toward C2+ products. (12) Instead, oxide-derived Cu catalysts (OD-Cu) show a higher overall activity for producing ethylene, (15−23) ethanol, (17)n-propanol, (17,24)n-butanol, (25) and traces of acetate and ethane, (17,26) at lower overpotentials than copper nanoparticles. (14,27−29)

To understand and control the key properties of OD-Cu upon reconstruction is crucial to rationally design more active and selective catalysts. It is generally thought that reconstruction boosts activity by increasing the electrochemically active surface area. (2,7,20,30) Regarding selectivity, CO dimerization is considered the crucial selectivity switch toward C2+ products. (2,31,32) Several features have been deemed responsible to promote that step, such as low coordinated Cu sites, (11,14,18,33) grain boundaries, (6,17,34) defects, (6,7) open facets, (6,27,35) surface roughness, (7,20) high surface pH, (35−37) cation effects, (2,32) and polarized Cuδ+ sites induced by residual oxygen. (6,15,20,22,23,38,39) However, the specific ensembles which control the selectivity to each product have not yet been identified.

The existence of residual oxygen on OD-Cu catalysts has been strongly debated in the literature, as its presence depends on the history of the material. Thermodynamically, copper oxide is expected to get fully reduced at neutral and alkaline pH for electric potentials lower than −0.1 V vs RHE (Figure S1). However, near-surface oxygen can be trapped kinetically (40) by oxidizing deeply the Cu sample before reduction (41) and by applying high cathodic potentials immediately after oxidation. (23,42) Near-surface oxygen atoms can also be restored by applying pulsed electrolysis (6,30) and by including a co-oxidant. (43) In contrast, materials obtained by shallow air oxidization of mono- or polycrystalline Cu get reduced beyond oxygen detection limits at CO2 reduction conditions. (44,45) Preoxidation of polycrystalline Cu by mild anodic potentials also results in a low concentration of oxygen sites. (28) When present, residual oxygen atoms do not belong to bulk phases of copper oxide (46) but rather prefer grain boundaries (28) where Cu atoms have an oxidation state intermediate between Cu0 and Cu+. (30,39,47) Both residual oxygen and grain boundaries promote C2+ products. (34,39) Density functional theory (DFT) models have found that residual oxygen is stable and enhances CO adsorption in highly disordered structures, (48) but not at interstitial sites of crystalline Cu. (49,50) For crystalline phases, DFT simulations have rationalized the selectivities observed for (111), (100), and stepped Cu surfaces toward C1–C2 products as a function of CO and H energy descriptors. (3,51) Besides, linear scaling relationships between surface site reactivity and coordination numbers are commonly employed to assess the properties of metals and oxides, in particular for disordered environments. (52,53) However, theoretical models still need to be adapted to the dynamic view of catalytic interfaces, such as OD-Cu under CO2 reduction conditions. (54)

As DFT-based modeling has focused on rather ideal structures, here we have envisaged an alternative way to understand the reactivity of OD-Cu. Starting from pristine oxides, we have removed oxygen atoms to create oxygen-depleted structures and allow reconstruction upon ab initio molecular dynamics. Although several crude approximations have been introduced (see below), we have identified new structural patterns that completely modify our understanding of these materials. In this way, we investigated roughness, coordination, oxidation states, and spectroscopic fingerprints for these structures, showing 14 recurrent ensembles with three chemical species: Cu0, Cuδ+, and Cu+. The ensembles characterized by mild polarization are responsible for OD-Cu enhanced activity and C2+ selectivity via a newly identifiedglyoxylate-like intermediate, Table S2.

OD-Cu catalysts are typically synthesized via oxidation of Cu foils or by electrochemical reduction of copper oxides. (17,45) To mimic changes in OD-Cu morphology under reaction conditions, we built structural models to represent both reduction of Cu2O (red-Cu2O) and oxidation of Cu (oxi-Cu) (Figure 1a,b).

Figure 1

Figure 1. Models for OD-Cu. We considered two systems: (a) a Cu2O(111) slab to mimic Cu2O reduction (red-Cu2O) and (b) a Cu(111)/Cu2O configuration to resemble Cu oxidation (oxi-Cu) (side views). For each supercell, O atoms were partially removed from the two outermost layers to create three depletion motifs: (c) rhomboidal (4R, patch), (d) triangular (4T, pitting), and (e) linear (6L, strip) (top views). (f) A symmetrical, Cu-terminated system (SY-red-Cu2O) was included to investigate the influence of stoichiometry and depletion motifs. (g–i) After 10 ps of AIMD at 700 K, the final surfaces present analogous reconstruction (Videos S1–S7 (55)) and (j) STM characterization detected similar patterns as experimental Cu/Cu2O systems (56) (Figure S3). Red-Cu2O and oxi-Cu systems were labeled nS, with n number of O atoms removed from the subsurface and S the shape of the O depleted region (dark brown). Red-Cu2O and oxi-Cu suffixes were appended to differentiate both conditions.

In the reduction models, OD-Cu were constructed as a Cu2O(111) supercell with about 21 Å lateral size. Then, the oxygens in the outermost layer (12/144) were removed, as suggested by ref (45), along with part of the subsurface sites (4–6/144) to reproduce experimental reports (O content: 10–20 atom %). (19,20) The Cu/O stoichiometry for these systems accounted for an overall oxygen atomic percent of 31–30 atom %, higher than experimental values because of the contribution of the bulk oxide (Table S3). Oxygen depletion followed three different shapes: rhomboidal (R), triangular (T), and linear (L), to promote clustering, pitting, and formation of grain boundaries, respectively (Figures 1c–e and S2). The suboxide formation energies of these initial structures differ only by 0.01 eV/Cu atom (Table S3), proving that they are potentially equivalent starting points. The systems were labeled nS: n stands for the number of subsurface oxygens removed, and S indicates the depletion motif, R, L or T (Figure 1c–e). Deep reduction conditions were simulated through a symmetric slab (SY-red-Cu2O), Cu2O(111) supercell, 7 layers thick. Here, just the two central Cu2O layers were preserved while removing 120/168 of all the oxygen atoms, leaving 13 atom % of oxygen (Figure 1f). Alternatively, oxidized Cu surfaces were reproduced depositing three Cu2O layers on bulk Cu(111) to recreate the geometric stress throughout surface reconstruction. Surface and subsurface oxygens were removed following the same procedure as before: taking the 4R model as reference, the formation energies by copper atom differ by ≤0.01 eV (0.21, 0.21, and 0.22 for the 4R, 4T, and 6L systems; Table S3).

Surface reconstruction was assessed through AIMD with the PBE density functional (ref (57)) for 10 ps at 700 K (3 fs time step). Solvent, potential, and electrolyte were not included during AIMD simulations. Although the approximations of our models are severe, our analysis demonstrates the strong structural modifications which occur on these materials under reaction conditions. The assessment of the robustness of our results is summarized in Table S2. Benchmark tests on Hubbard correction and AIMD temperatures were performed on the 4R-red and 4R-oxi systems (Computational Methods in the Supporting Information). Similar surface patterns evolved upon reconstruction, while their abundance depended on Cu/O stoichiometry (Figure 1g–i). The final structures reproduced the overall disorder characterized by local recurrent features with around 1 nm periodicity and O depletion regions reported as dark areas in STM images of Cu2O/Cu(111) surfaces under CO autocatalytic reduction (56) (Figure S3). The thermodynamic stability of the models was estimated from their Pourbaix diagrams. The final snapshots of the AIMD simulations were further optimized to their lowest-energy configuration, and solvation contributions were included to the optimized structures through an implicit model. (58,59) Stabilized by configurational entropy and solvation, our disordered systems are metastable. (60) Their formation energy is slightly higher than the thermodynamically stable phase (Cu2O) by at most 0.1 eV, but significantly, they are more stable than experimentally reported oxidic phases, Cu8O and Cu64O (61) (Tables S4–S7, Figure S1, and eqs S5–S9). Moreover, in our models, O stability on reconstructed surfaces depends on its local coordination: at mild negative potential O desorption is endothermic because of high surface pH, (35−37,62) which may increase up to 14 for high cathodic current densities (63) (Supporting Discussion, Figure S4). Depending on the surface pH, the stability region of residual oxygens extends until −0.84 V vs RHE, in good agreement with recent experimental reports. (6,23,42,64,65) Uncertainty in surface pH determination by 1–2 units and the lack of configuration entropy contribution set the limit for O borderline-stability between −0.6 and −1.0 V vs RHE (Supporting Discussion). Structural characterization was performed on the two outermost layers for the whole AIMD production period. We investigated surface roughness (σ), number of surface sites, radial distribution functions (RDF), Cu coordination numbers (NCu–Cu), spectroscopic properties, and recurrent ensembles for each of the trajectories (Computational Methods). Final AIMD trajectories show similar Cu 2p and O 1s XPS fingerprints as OD-Cu experimental systems (Figure S5). Analogously, vibrational spectra (eqs S10–S13) qualitatively reproduce Raman shifts detected in experimental reports, as shown in Figures S6 and S7.

OD-Cu activity has been attributed to a higher surface area upon reconstruction. (2,7,20,30) However, previous theoretical simulations did not succeed in quantifying nanostructuring. (39,46,48−51) Through the continuous reorganization induced by AIMD, we were able to assess OD-Cu reconstruction through arithmetic average surface roughness, σ (eqs S14 and S15 and Figure S8). Theoretical atomic roughness was calculated to range within 0.8–1.4 Å for our OD-Cu models (Figure S9); thus, it was significantly higher than experimental values for crystalline Cu, 0.32 Å. (66) For red-Cu2O systems, surface roughness did not change significantly after equilibration, while oxi-Cu surfaces kept reconstructing until σ = 1.5, 1.1, and 1.0 Å for 4R, 4T, and 6L, respectively, until 8 ps AIMD time, because of the geometric stress between metallic and oxidic layers. The ratio of surface sites of the reconstructed surfaces versus surface sites of crystalline Cu2O(111) increases by 120% (140%) for red-Cu2O (oxi-Cu) with regard to pristine oxidic copper (Figure S10 and eq S16), in line with the increased electrochemically active surface area on OD-Cu. (7) 6L-oxi-Cu presents the largest increment of surface sites among all the configurations, albeit showing the lowest atomic surface roughness. Therefore, we identify grain boundaries as minor perturbations of the surface which determine mild surface roughness but large active area, as suggested experimentally. (34) In contrast, reconstruction strongly modified rhomboidal (4R) and triangular configurations (4T), increasing surface roughness (Figure 1c,d and Videos S1–S7 (55)).

To determine the local coordination of Cu atoms, we calculated Cu–Cu and Cu–O RDFs, gCu–O and gCu–Cu (eqs S17 and S18). For all the systems, gCu–O shows a well-defined minimum at a Cu–O distance of 2.50 Å, which is between the first and second peaks of bulk Cu2O: 1.87 and 3.57 Å (Figure S11). Thus, we set dCu–O = 2.50 Å as threshold for O coordination to Cu. Consequently, we found that Cu exists in three well-defined states according to its coordination to nearby oxygen atoms: metallic, suboxidic, and oxidic Cu (Figure 2). Suboxidic Cu2O0.5-like species have been also detected experimentally, (30,47,64) and EXAFS characterization confirmed an average Cu–O coordination number of 1.1 for suboxidic Cu. (64) Despite presenting different stoichiometry (31, 13, and 11 atom % O) and initial configurations (Table S3), all the models gave comparable RDFs upon AIMD, thus reinforcing the general nature of our results (Figures 2a–f and S12).

Figure 2

Figure 2. Characterization of Cu species. (a–f) Cu–Cu RDF for Cu atoms coordinated with 0–2 oxygens as shown in the insets. The first (second) coordination shell of bulk Cu (Cu2O) is shown as black (red) dashed lines. Cu–Cu RDF for the SY-red-Cu2O system is reported in Figure S12. (g) Cu atoms coordinated to 0–2 oxygens show clear differences in their Bader charges and number of Cu atoms in their first coordination shell. (h–j) Cu–Cu coordination number (NCu–Cu) cumulative maps show peaks at integer NCu–Cu, suggesting the existence of recurring ensembles. Average Cu–Cu, dashed lines, differ by 1.0 units from metallic to polarized and almost 3.0 to oxidic Cu. Bader charges and NCu–Cu distributions for the remaining systems are reported in Figures S15 and S17.

The first Cu–Cu coordination shell is a combination of crystalline Cu and Cu2O, somewhat smeared in the intermediate values (Figure 2a–f). To calculate the coordination number of each Cu to neighboring Cu atoms, NCu–Cu, we counted 1 bond when the Cu–Cu distance was the one of metallic Cu, no bonds for the one of Cu2O, and applied a Gaussian smearing for the values in between (eqs S19–20 and Figure S13). The distribution of Cu–Cu values averaged over time does not show significant changes for red-Cu2O models (Figure S14). In contrast, oxi-Cu systems again reveal a continuous reconstruction process until 6 ps, where metallic-like configurations reform from pristine low coordinated Cu. As a general trend, Cu is undercoordinated when compared to typical values for crystalline facets (Table S8). When coordinated to 1 oxygen, copper atoms lose 1 Cu bond; thus, Cu–Cu ≈ 4 (5) for the two families of models. Finally, double O coordination saturates Cu sites; thus, Cu–Cu further decreases by 2 metallic bonds, ∼2 (3) for red-Cu2O (oxi-Cu). In agreement with our theoretical predictions of Cu–Cu = 4.9, 3.6, and 2.0 for metallic, suboxidic, and oxidic copper, respectively (Figure 2h–j), Cu–Cu of 6.6, 3.08, 2.21, and 1.84 have been experimentally reported for OD-Cu systems. (64,67)

Moving ahead to address key contributors to OD-Cu performance, we then targeted Cu electronic structure. (6,15,20,22,38) We sampled the Bader charges for the whole simulation period at a time step of 48 fs. Because the seven models feature analogous structural properties (Figures 2a–f and S12) we focused the analysis on the 4R-red-Cu2O system, whereas the characterization of other models is reported in Figure S15. As shown in Figure 2g, the three Cu species described in the previous section account for well-defined oxidation states. Metallic and oxidic Cu charges are centered at 0.0 and 0.5 |e|, respectively, akin to bulk Cu and Cu2O. We labeled these species as metallic, Cu0, and oxidic copper, Cu+. Cu atoms coordinated with one oxygen exhibit intermediate positive polarization with a well-defined boundary between 0.1 ≤ qCu ≤ 0.4 |e|. Thus, we assign this species to the previously proposed polarized Cu, also called “suboxidic”, Cuδ+. (30,47,64)

The relative abundance of these three species depends on the initial configuration and stoichiometry (Figure S16 and Table S9). Red-Cu2O accounts high abundance of Cuδ+/Cu+ sites, while the stronger reconstruction occurring on oxi-Cu systems determines an increase of Cu+ species. Metallic copper is instead favored by low O atomic percentage, as expected for the SY-red-Cu2O system. The presence of residual Cu+ species upon reconstruction agrees with recent experimental reports for Cu2O nanocubes (20% at −0.95 V vs RHE) and Cu(100) under CO2 pulsed electroreduction (7–11% at −1 V vs RHE). (6,42)NCu–Cu cumulative maps prove the existence of atomic ensembles for all the three classes: metallic Cu0 (Figure 2j), polarized Cuδ+ (Figure 2i), and oxidic Cu+ (Figure 2h). The analysis of the remaining models support this finding (Figure S17).

In addition to averaged properties, a unequivocal identification of recurrent ensembles requires local characterization. Atomic ensembles are defined by their interatomic distances and angles. Therefore, we mapped the occurrence of interatomic angles versus the z-coordinate of the central atom to identify its coordination environment. As a result we detected 14 recurrent ensembles which were stable at different AIMD temperatures, Figure S18–S19, and with Hubbard correction, Figure S20. As a 2-dimensional histogram, darker areas represent higher density of atoms with a given angle with neighboring sites at a given z-coordinate, within the two outermost layers, Figure 3a-f and Figures S21–S22. For metallic copper, Cu0, we identified a few 4- and 6-coordinated Cu adatoms, Cu4Cu–Cu6Cu. In addition, surface reconstructs into reminiscent of crystalline domains, such as Cu(100), Cu(110), and Cu(111), either fully metallic or including few polarized Cuδ+. Few surface Cuδ+ species aggregate in triangular Cu3δ+O3 ensembles. This ensemble has been characterized experimentally very recently in ref (30), and reconstruction of Cu-based catalysts toward open facets was detected through operando electrochemical STM. (9,44) Oxidic Cu+ is not abundant at the outermost layers, and the interface between Cu+ and Cu0–Cuδ+ species mimics the grain boundary motif reported in Figure S2. Regarding the oxygen atoms, their preferred configuration depends on their position. Inner atoms adopt mainly bulk-like tetrahedral shapes, O4Cu,t, as well as few distorted configurations with 3-fold or 5-fold coordination, O3Cu,d, O5Cu. Besides, there is a strong, narrow signal at 45° which is characteristic of a “grain boundary” ensemble (g.b. in Figure 3g). Near-surface oxygens (Ons) prefer to adopt planar configurations, namely O3Cu,p and O4Cu,p. Finally, oxygen adatoms may coordinate with three or four Cu atoms, O3Cu,ad and O4Cu,ad. These adatoms give a mild and diffuse signal, meaning that they are less abundant than near-surface configurations and do not have any strong preference to adopt a particular shape. In recent experiments, near-surface oxygen has been found stable in Cu2O0.5 stoichiometry at potentials as reductive as −1.0 V vs RHE, (64) but there is scarce experimental information about the remaining oxygen ensembles.

Figure 3

Figure 3. Recurrent ensembles in OD-Cu models. (a–f) Histograms for angles θ(ABC) measured around the first coordination shell of central atom B at different heights z(B) for the 4R-red-Cu2O system. The ensembles responsible for each feature are labeled and shown in panel g; tetra- and hexa-coordinated Cu adatoms: Cu3Cu and Cu4Cu; reminiscent of crystalline Cu: Cu(100)-like facets, including distorted forms mainly metallic or asymmetric in charge (subscripts “d” and “da”), Cu(110) and Cu(111) facets; Cu3δ+O3; Cu/Cu2O grain boundaries, g.b. (Figure S2); tri- and tetra-coordinated O adatoms: O3Cu,ad and O4Cu,ad; tri- and tetra-coordinated planar O: O3Cu,p and O4Cu,p; penta-coordinated near-surface O: O5Cu; tetrahedral O: O4Cu,t; distorted near-surface O: O3Cu,d. Comparison with other models and values of Nmax are reported in Figures S21 and S22.

Previous computational studies assessed the catalytic properties of very ordered systems, (3,51) including O as an impurity in crystalline Cu for modeling OD-Cu catalysts. (39,46,48) Our analysis proves that the landscape of OD-Cu catalysts might be much more complex because of the appearance of several new ensembles. Because metastable states, even if less abundant, can be the active sites which drive the activity and selectivity of metals and oxides, (54) here we investigated the adsorption properties of the identified ensembles to obtain new potential descriptors for CO2 reduction on OD-Cu. We evaluated *CO2, *OCCO, and 2*CO adsorption energies, as these molecules are generally reported as the key intermediates for CO2R activity and C2+ selectivity. (2) Because local configurations do not change significantly among red-Cu2O and oxi-Cu models (Figures S21 and S22), we sampled only the first ones.

Our simulations show that CO2 adsorbs via Cu–C and Cu–O bonds, ηC,O2, on Cu sites (Figure 4a, purple), or via a Ons–C bond on near-surface O (Figure 4a, magenta). CO2 adsorption energy scales linearly with the polarization of the ensembles, approximated by Q1, the sum of their Bader charges in absolute value (eqs S21 and S22). Xδ−–Cuδ+ (X = O, Cu0) asymmetric pairs are strong binding sites for CO2 because of high polarization. Cu0–Cuδ+ and Cuδ+–Cuδ+ pairs in ensembles Cu4Cu, Cu6Cu, and Cu3δ+O3 (Figure 3g) can tether CO2 more favorably than crystalline copper by 0.5 eV (0.2 eV vs 0.7 eV, Table S10). Cu+ sites, saturated by the 2 neighboring O atoms, do not play a relevant catalytic role (Figure S23). In the literature, the specific role of the Cuadatom0–Cuδ+(Cu+) pair on CO2 activation has been suggested. (39,68) Here, we provide a generalized model, proposing negative (positive) polarization on C (O) binding sites as a general descriptor for CO2 activity. As experimental evidence, CO2 adsorption has been detected via SEIRAS spectroscopy at low overpotential for suboxidic and oxidic Cu. (15) High local polarization accounts for the remarkable performance of OD-Cu, along with higher surface roughness and number of active sites (Figures S9 and S10). The high electronic density localized on near-surface O3Cu,p and O4Cu,p oxygens (Figure 3g) saturates the Ons–C bond; thus, it leads to saturation of CO2 binding energy to high exothermic values (Figure S24). As a consequence, the surface is passivated from carbonate coverage, and it is not active anymore for CO2 reduction. (38) Carbonate coverage has been reported on OD-Cu under CO2 reduction conditions via in situ and real-time surface-enhanced infrared absorption spectroscopy (SEIRAS) (Table S11).

Figure 4

Figure 4. CO2R activity and C2+ selectivity of OD-Cu versus ensemble polarization. (a) OD-Cu can adsorb CO2 either on a Cu site (purple) or on a near-surface oxygen (magenta) forming a carbonate. CO2 adsorption energy scales linearly with the polarization of the active sites, Q1: . Cu0–Cuδ+ and Cuδ+–Cuδ+ are responsible for enhancing OD-Cu CO2R (purple area), while activity of Ons sites is limited by carbonate formation. (b) Polarization of active ensembles, Q2, drives selectivity to C2 products: ΔG*OCCO = +0.7(±0.1) – 0.7(±0.1)Q2. A paired active site, Cuδ+-Ons, stabilizes the CO–CO dimer as a glyoxylate-like intermediate (dark red), enhancing C2 production. In contrast, for metallic Cu sites (red) CO dimerization is not favored, leading to a higher *CO coverage (gray), ΔG2*CO = −1.3(±0.1) + 1.3(±0.1)Q2. For very strong polarization, stable oxalates are generated on the surface (black). Q1 and Q2 are defined as the sum of absolute Bader charges of the atoms in the ensemble calculated with implicit solvation (eqs S21 and S22, Figure S27). (c) *OCCO intermediate on both OD-Cu and Cu(100) and oxalate formation on OD-Cu presents a high kinetic barrier of more than 1 eV. The pathway toward the glyoxylate-like intermediate has instead a mild barrier of 0.53 eV. Potential and dipole corrections, here not included, stabilize all intermediates similarly (Table S16). Further details on the linear regressions are shown in Table S17.

Because CO2 reduction activity is promoted by local polarization, we now focus on the CO–CO dimer, whose stability on the surface has been proposed to determine CO2 selectivity and therefore C2+ product distribution. (2,32) In Figure 4b we present the stability of the dimer for the identified local ensembles. Again, the adsorption energy for the dimer depends linearly on the sum of the Bader charges of the ensembles, Q2, proxy of their polarization (eqs S21 and S22). We can identify 3 types of adsorbed species: CO–CO dimer, *OCCO; glyoxylate-like intermediates, *OCCOO; and oxalate, *OOCCOO. Metal-only domains generate CO–CO dimers (Figure 4b, red inset), which are easily dissociated, therefore leading to similar product distribution as copper foil and nanoparticles (H2, CH4). (12,14) Polarized Cu0–Cuδ+ (100)–(110) facets (Figure 3g) exhibit similar reactivity as crystalline Cu(100) (Table S10), thus confirming the experimental hypotheses on structural and chemical affinity between crystalline open facets and OD-Cu. (27,35) For very high surface polarization, strongly bound oxalates are generated on the surface via two near-surface oxygens (Figure 4b, black inset). If formed, oxalates could cause surface passivation and Cu dissolution; however, this process is hindered by the high kinetic barrier associated, 1.51 eV (Figure 4c, black inset). Furthermore, if oxygen sites tether CO too strongly, they may desorb as CO2 (lower dashed line in Figure 4b and Table S12). Mild surface polarization makes CO–CO formation thermoneutral; therefore, it enables the dimerization reaction. (69,70) Glyoxylate-like species OC*CO(Ons) triggers OD-Cu selectivity to C2+ because of the low kinetic barrier associated to its formation, 0.53 eV (Figure 4b-c, dark red inset). The carbon atoms of this intermediate are separately adsorbed on a bridge position between low coordinated Cu and atop a near-surface oxygen. The local Cu coordination resembles either Cu(111) facets or the Cu3δ+O3 ensemble previously reported (ref (71)) (Figure S25). Glyoxylate is a well-known intermediate for prebiotic CO2 reduction, (72) although to the best of our knowledge its dehydrogenated form, OC*CO(Ons), has not yet been reported in electrochemical CO2 literature. (31,73) We highlight that glyoxylate and oxalate production may occur as well via direct CO2 reduction (Table S13) and that glyoxylate vibrational frequencies (1630, 1479, and 1145 cm–1; Table S14) are compatible with SEIRAS and IR spectroscopy signals for CO2 reduction on OD-Cu (Tables S11 and S15). We therefore propose the paired Cuδ+–Ons active site that stabilizes the glyoxylate-like intermediate to open the pathway for ethanol production on OD-Cu at −0.25 V vs RHE, (17) as a weak metal–oxygen bond has been deemed responsible for alcohol production on Cu. (74)

The product distribution of OD-Cu depends on time and can be attributed to the relative abundance of the different ensembles under CO2R conditions. (6) Low-coordinated Cu0 sites (Cu6Cu, Cu4Cu, and Cu3δ+O3; Figure 3g) present stronger CO binding energy than crystalline Cu (Figure S23). Therefore, we identify them with the strong binding sites reported on OD-Cu by Verdaguer-Casadevall et al. (75) Cuδ+ coordination tunes significantly its adsorption properties: ΔE*CO ranges from −0.5 to +0.5 eV (Figure S23). Local coordination and oxidation state influences Cu affinity to oxygen: both Cu0 and Cuδ+ are less oxophilic than Cu(100), and an increasing oxidation state leads to lower O affinity (Figure S23). The rationale of the wide OD-Cu product distribution may then be elucidated by Cu coordination and its affinity to O; thus, those descriptors could be applied in the future to explain the occurrence of specific active sites toward ethylene, ethanol, and n-propanol. (10)

We have compiled and identified three key contributions toward OD-Cu activity and C2+ selectivity: polarized active sites, open facets, and glyoxylate route. Local charge polarization strengthens CO2 binding, thus promoting a higher CO2R activity. This insight provides a solid understanding of the role of Cuδ+ as a privileged site for OD-Cu catalysts. (6,15,20,22,38) Reconstructed open facets resemble crystalline Cu(100), thus motivating ethylene production at high onset potential. The Cuδ+–Ons pair adsorbs the CO dimer exothermically as a glyoxylate-like intermediate, which accounts for the low onset potential toward C2+ products reported experimentally. (17)

In the present work we characterized oxide-derived copper catalysts at different stoichiometries and oxidation stages. After ab initio molecular dynamics simulations, the final structures present high surface area and atomic-scale roughness. Independently from the initial model assumed, Cu exists as three species: Cu0, Cuδ+, and Cu+, which combine into 14 well-defined ensembles. Among those ensembles, Cuδ+, Cu0–Cuδ+, and Cu–Ons are the active and selective sites for CO2 reduction. Cuδ+ and Cu0–Cuδ+ tether CO2 actively because of their high polarization, thus promoting CO2 activation. The Cu–Ons pair stabilizes C–C coupling via a glyoxylate-like intermediate, which opens the reaction pathway toward C2+ products from −0.5 V vs RHE because of the low kinetic barrier associated with its formation, 0.53 eV. Ons is here reported stable until −0.84 V vs RHE in good agreement with recent experimental reports. (64) Although our methodology does not include solvent, electrolyte, adsorbates, and electric field during ab initio molecular dynamics, the results are qualitatively robust and constitute a step forward in the understanding of the role of new ensembles on oxide-derived copper reactivity. Our study conciliates all the previous experimental observations concerning the nature of OD-Cu active sites during CO2 reduction time-scales and the consequent changes in product distribution. As active and selective sites have been characterized, the core of future investigations must be the development of synthetic protocols to stabilize these privileged ensembles.

Supporting Information

ARTICLE SECTIONS
Jump To

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsenergylett.0c01777.

  • Computational methods, supporting discussion, eqs S1–S24, Figures S1–S27, and Tables S1–S20 (PDF)

Terms & Conditions

Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

ARTICLE SECTIONS
Jump To

  • Corresponding Author
  • Authors
    • Federico Dattila - Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Av. Països Catalans 16, 43007 Tarragona, SpainOrcidhttp://orcid.org/0000-0001-8195-3951
    • Rodrigo Garcı́a-Muelas - Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Av. Països Catalans 16, 43007 Tarragona, SpainOrcidhttp://orcid.org/0000-0002-2219-5027
  • Notes
    The authors declare no competing financial interest.

    The data sets generated during the current study and the full ab initio molecular dynamics trajectories for red-Cu2O and oxi-Cu systems, Videos S1–S7, (55) are available in the ioChem-BD database (76) at DOI 10.19061/iochem-bd-1-165.

Acknowledgments

ARTICLE SECTIONS
Jump To

The authors acknowledge the financial support from the Spanish Ministry of Science and Innovation (Grant RTI2018-101394–B-I00) and the European Union (projects A-LEAF 732840-A-LEAF and ELCoREL 722614-ELCOREL). The Barcelona Supercomputing Center (BSC-RES) is acknowledged for providing generous computational resources. The authors thank Dr. Marçal Capdevila-Cortada and the Reviewers for fruitful scientific discussions.

References

ARTICLE SECTIONS
Jump To

This article references 76 other publications.

  1. 1
    Nitopi, S. Progress and perspectives of electrochemical CO2 reduction on copper in aqueous electrolyte. Chem. Rev. 2019, 119, 76107672,  DOI: 10.1021/acs.chemrev.8b00705
  2. 2
    Birdja, Y. Y.; Pérez-Gallent, E.; Figueiredo, M. C.; Göttle, A. J.; Calle-Vallejo, F.; Koper, M. T. M. Advances and challenges in understanding the electrocatalytic conversion of carbon dioxide to fuels. Nat. Energy 2019, 4, 732745,  DOI: 10.1038/s41560-019-0450-y
  3. 3
    Peterson, A. A.; Abild-Pedersen, F.; Studt, F.; Rossmeisl, J.; Nørskov, J. K. How copper catalyzes the electroreduction of carbon dioxide into hydrocarbon fuels. Energy Environ. Sci. 2010, 3, 13111315,  DOI: 10.1039/c0ee00071j
  4. 4
    Hori, Y.; Murata, A.; Takahashi, R. Formation of hydrocarbons in the electrochemical reduction of carbon dioxide at a copper electrode in aqueous solution. J. Chem. Soc., Faraday Trans. 1 1989, 85, 23092326,  DOI: 10.1039/f19898502309
  5. 5
    De Luna, P.; Hahn, C.; Higgins, D.; Jaffer, S. A.; Jaramillo, T. F.; Sargent, E. H. What would it take for renewably powered electrosynthesis to displace petrochemical processes?. Science 2019, 364, 350,  DOI: 10.1126/science.aav3506
  6. 6
    Arán-Ais, R. M.; Scholten, F.; Kunze, S.; Rizo, R.; Roldan Cuenya, B. The role of in situ generated morphological motifs and Cu(I) species in C2+ product selectivity during CO2 pulsed electroreduction. Nat. Energy 2020, 5, 317325,  DOI: 10.1038/s41560-020-0594-9
  7. 7
    Gao, D.; Arán-Ais, R. M.; Jeon, H. S.; Roldán-Cuenya, B. Rational catalyst and electrolyte design for CO2 electroreduction towards multicarbon products. Nat. Catal. 2019, 2, 198210,  DOI: 10.1038/s41929-019-0235-5
  8. 8
    Huang, J.; Hörmann, N.; Oveisi, E.; Loiudice, A.; De Gregorio, G. L.; Andreussi, O.; Marzari, N.; Buonsanti, R. Potential-induced nanoclustering of metallic catalysts during electrochemical CO2 reduction. Nat. Commun. 2018, 9, 3117,  DOI: 10.1038/s41467-018-05544-3
  9. 9
    Kim, Y. G.; Baricuatro, J. H.; Javier, A.; Gregoire, J. M.; Soriaga, M. P. The evolution of the polycrystalline copper surface, first to Cu(111) and then to Cu(100), at a fixed CO2RR potential: A study by operando EC-STM. Langmuir 2014, 30, 1505315056,  DOI: 10.1021/la504445g
  10. 10
    Lum, Y.; Ager, J. W. Evidence for product-specific active sites on oxide-derived Cu catalysts for electrochemical CO2 reduction. Nat. Catal. 2019, 2, 8693,  DOI: 10.1038/s41929-018-0201-7
  11. 11
    Auer, A.; Andersen, M.; Wernig, E.-M.; Hörmann, N. G.; Buller, N.; Reuter, K.; Kunze-Liebhäuser, J. Self-activation of copper electrodes during CO electro-oxidation in alkaline electrolyte. Nat. Catal. 2020,  DOI: 10.1038/s41929-020-00505-w
  12. 12
    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, 3947,  DOI: 10.1016/S1381-1169(03)00016-5
  13. 13
    Kuhl, K. P.; Cave, E. R.; Abram, D. N.; Jaramillo, T. F. New insights into the electrochemical reduction of carbon dioxide on metallic copper surfaces. Energy Environ. Sci. 2012, 5, 70507059,  DOI: 10.1039/c2ee21234j
  14. 14
    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, 69786986,  DOI: 10.1021/ja500328k
  15. 15
    Chou, T.-C. Controlling the oxidation state of Cu electrode and reaction intermediates for electrochemical CO2 reduction to ethylene. J. Am. Chem. Soc. 2020, 142, 28572867,  DOI: 10.1021/jacs.9b11126
  16. 16
    Li, C. W.; Kanan, M. W. CO2 reduction at low overpotential on Cu electrodes resulting from the reduction of thick Cu2O films. J. Am. Chem. Soc. 2012, 134, 72317234,  DOI: 10.1021/ja3010978
  17. 17
    Li, C. W.; Ciston, J.; Kanan, M. W. Electroreduction of carbon monoxide to liquid fuel on oxide-derived nanocrystalline copper. Nature 2014, 508, 504507,  DOI: 10.1038/nature13249
  18. 18
    Ren, D.; Deng, Y.; Handoko, A. D.; Chen, C. S.; Malkhandi, S.; Yeo, B. S. Selective electrochemical reduction of carbon dioxide to ethylene and ethanol on copper(I) oxide catalysts. ACS Catal. 2015, 5, 28142821,  DOI: 10.1021/cs502128q
  19. 19
    Kim, D.; Lee, S.; Ocon, J. D.; Jeong, B.; Lee, J. K.; Lee, J. Insights into an autonomously formed oxygen-evacuated Cu2O electrode for the selective production of C2H4 from CO2. Phys. Chem. Chem. Phys. 2015, 17, 824830,  DOI: 10.1039/C4CP03172E
  20. 20
    Mistry, H. Highly selective plasma-activated copper catalysts for carbon dioxide reduction to ethylene. Nat. Commun. 2016, 7, 12123,  DOI: 10.1038/ncomms12123
  21. 21
    Handoko, A. D.; Ong, C. W.; Huang, Y.; Lee, Z. G.; Lin, L.; Panetti, G. B.; Yeo, B. S. Mechanistic insights into the selective electroreduction of carbon dioxide to ethylene on Cu2O-derived copper catalysts. J. Phys. Chem. C 2016, 120, 2005820067,  DOI: 10.1021/acs.jpcc.6b07128
  22. 22
    De Luna, P.; Quintero-Bermudez, R.; Dinh, C.-T.; Ross, M. B.; Bushuyev, O. S.; Todorović, P.; Regier, T.; Kelley, S. O.; Yang, P.; Sargent, E. H. Catalyst electro-redeposition controls morphology and oxidation state for selective carbon dioxide reduction. Nat. Catal. 2018, 1, 103110,  DOI: 10.1038/s41929-017-0018-9
  23. 23
    Lee, S. Y.; Jung, H.; Kim, N.-K.; Oh, H.-S.; Min, B. K.; Hwang, Y. J. Mixed copper states in anodized Cu electrocatalyst for stable and selective ethylene production from CO2 reduction. J. Am. Chem. Soc. 2018, 140, 86818689,  DOI: 10.1021/jacs.8b02173
  24. 24
    Li, J. Copper adparticle enabled selective electrosynthesis of n-propanol. Nat. Commun. 2018, 9, 4614,  DOI: 10.1038/s41467-018-07032-0
  25. 25
    Ting, L. R. L.; Garcia-Muelas, R.; Martin, A. J; Veenstra, F. L. P.; Chen, S. T.-J.; Peng, Y.; Per, E. Y. X.; Pablo Garcia, S.; Lopez, N.; Perez-Ramirez, J.; Yeo, B. S. Electrochemical reduction of carbon dioxide to 1-butanol on oxide-derived copper. Angew. Chem., Int. Ed. 2020, 25, 210,  DOI: 10.1002/anie.202008289
  26. 26
    Dutta, A.; Rahaman, M.; Luedi, N. C.; Mohos, M.; Broekmann, P. Morphology matters: tuning the product distribution of CO2 electroreduction on oxide-derived Cu foam catalysts. ACS Catal. 2016, 6, 38043814,  DOI: 10.1021/acscatal.6b00770
  27. 27
    Loiudice, A.; Lobaccaro, P.; Kamali, E. A.; Thao, T.; Huang, B. H.; Ager, J. W.; Buonsanti, R. Tailoring copper nanocrystals towards C2 products in electrochemical CO2 reduction. Angew. Chem., Int. Ed. 2016, 55, 57895792,  DOI: 10.1002/anie.201601582
  28. 28
    Lum, Y.; Ager, J. W. Stability of residual oxides in oxide-derived copper catalysts for electrochemical CO2 reduction investigated with 18O labeling. Angew. Chem., Int. Ed. 2018, 57, 551554,  DOI: 10.1002/anie.201710590
  29. 29
    Zhu, Q.; Sun, X.; Yang, D.; Ma, J.; Kang, X.; Zheng, L.; Zhang, J.; Wu, Z.; Han, B. Carbon dioxide electroreduction to C2 products over copper-cuprous oxide derived from electrosynthesized copper complex. Nat. Commun. 2019, 10, 3851,  DOI: 10.1038/s41467-019-11599-7
  30. 30
    Lin, S.-C.; Chang, C.-C.; Chiu, S.-Y.; Pai, H.-T.; Liao, T.-Y.; Hsu, C.-S.; Chiang, W.-H.; Tsai, M.-K.; Chen, H. M. Operando time-resolved X-ray absorption spectroscopy reveals the chemical nature enabling highly selective CO2 reduction. Nat. Commun. 2020, 11, 3525,  DOI: 10.1038/s41467-020-17231-3
  31. 31
    Kortlever, R.; Shen, J.; Schouten, K. J. P.; Calle-Vallejo, F.; Koper, M. T. M. Catalysts and reaction pathways for the electrochemical reduction of carbon dioxide. J. Phys. Chem. Lett. 2015, 6, 40734082,  DOI: 10.1021/acs.jpclett.5b01559
  32. 32
    Pérez-Gallent, E.; Figueiredo, M. C.; Calle-Vallejo, F.; Koper, M. T. M. Spectroscopic observation of a hydrogenated CO dimer intermediate during CO reduction on Cu(100) electrodes. Angew. Chem., Int. Ed. 2017, 56, 36213624,  DOI: 10.1002/anie.201700580
  33. 33
    Cheng, T.; Xiao, H.; Goddard, W. A. Nature of the active sites for CO reduction on copper nanoparticles; Suggestions for optimizing performance. J. Am. Chem. Soc. 2017, 139, 1164211645,  DOI: 10.1021/jacs.7b03300
  34. 34
    Feng, X.; Jiang, K.; Fan, S.; Kanan, M. W. A direct grain-boundary-activity correlation for CO electroreduction on Cu nanoparticles. ACS Cent. Sci. 2016, 2, 169174,  DOI: 10.1021/acscentsci.6b00022
  35. 35
    Wang, Y. Catalyst synthesis under CO2 electroreduction favours faceting and promotes renewable fuels electrosynthesis. Nat. Catal. 2020, 3, 98106,  DOI: 10.1038/s41929-019-0397-1
  36. 36
    Ringe, S.; Morales-Guio, C. G.; Chen, L. D.; Fields, M.; Jaramillo, T. F.; Hahn, C.; Chan, K. Double layer charging driven carbon dioxide adsorption limits the rate of electrochemical carbon dioxide reduction on Gold. Nat. Commun. 2020, 11, 33,  DOI: 10.1038/s41467-019-13777-z
  37. 37
    Veenstra, F. L.; Ackerl, N.; Martı́n, A. J.; Pérez-Ramı́rez, J. Laser-microstructured copper reveals selectivity patterns in the electrocatalytic reduction of CO2. Chem. 2020, 6, 17071722,  DOI: 10.1016/j.chempr.2020.04.001
  38. 38
    Velasco-Vélez, J.-J. The role of the copper oxidation state in the electrocatalytic reduction of CO2 into valuable hydrocarbons. ACS Sustainable Chem. Eng. 2019, 7, 14851492,  DOI: 10.1021/acssuschemeng.8b05106
  39. 39
    Favaro, M.; Xiao, H.; Cheng, T.; Goddard, W. A.; Yano, J.; Crumlin, E. J. Subsurface oxide plays a critical role in CO2 activation by Cu(111) surfaces to form chemisorbed CO2, the first step in reduction of CO2. Proc. Natl. Acad. Sci. U. S. A. 2017, 114, 67066711,  DOI: 10.1073/pnas.1701405114
  40. 40
    Velasco-Velez, J.-J. Revealing the active phase of copper during the electroreduction of CO2 in aqueous electrolyte by correlating In Situ X-ray spectroscopy and In Situ electron microscopy. ACS Energy Lett. 2020, 5, 21062111,  DOI: 10.1021/acsenergylett.0c00802
  41. 41
    Zhao, Y.; Chang, X.; Malkani, A. S.; Yang, X.; Thompson, L.; Jiao, F.; Xu, B. Speciation of Cu surfaces during the electrochemical CO reduction reaction. J. Am. Chem. Soc. 2020, 142, 97359743,  DOI: 10.1021/jacs.0c02354
  42. 42
    Möller, T. Electrocatalytic CO2 reduction on CuOx nanocubes tracking the evolution of chemical state, geometric structure, and catalytic selectivity using Operando Spectroscopy. Angew. Chem., Int. Ed. 2020,  DOI: 10.1002/anie.202007136
  43. 43
    He, M.; Li, C.; Zhang, H.; Chang, X.; Chen, J. G.; Goddard, W. A., III; Cheng, M.-j.; Xu, B.; Lu, Q. Oxygen induced promotion of electrochemical reduction of CO2 via co-electrolysis. Nat. Commun. 2020, 11, 3844,  DOI: 10.1038/s41467-020-17690-8
  44. 44
    Kim, Y. G.; Soriaga, M. P. Cathodic regeneration of a clean and ordered Cu(100)-(1 × 1) surface from an air-oxidized and disordered electrode: An operando STM study. J. Electroanal. Chem. 2014, 734, 79,  DOI: 10.1016/j.jelechem.2014.09.010
  45. 45
    Scott, S. B. Absence of oxidized phases in Cu under CO reduction conditions. ACS Energy Lett. 2019, 4, 803804,  DOI: 10.1021/acsenergylett.9b00172
  46. 46
    Eilert, A. Subsurface oxygen in oxide-derived copper electrocatalysts for carbon dioxide reduction. J. Phys. Chem. Lett. 2017, 8, 285290,  DOI: 10.1021/acs.jpclett.6b02273
  47. 47
    Schedel-Niedrig, T.; Neisius, T.; Böttger, I.; Kitzelmann, E.; Weinberg, G.; Demuth, D.; Schlögl, R. Copper (sub)oxide formation: a surface sensitive characterization of model catalysts. Phys. Chem. Chem. Phys. 2000, 2, 24072417,  DOI: 10.1039/b000253o
  48. 48
    Liu, C.; Lourenço, M. P.; Hedström, S.; Cavalca, F.; Diaz-Morales, O.; Duarte, H. A.; Nilsson, A.; Pettersson, L. G. Stability and effects of subsurface oxygen in oxide-derived Cu catalyst for CO2 reduction. J. Phys. Chem. C 2017, 121, 2501025017,  DOI: 10.1021/acs.jpcc.7b08269
  49. 49
    Garza, A. J.; Bell, A. T.; Head-Gordon, M. Is subsurface oxygen necessary for the electrochemical reduction of CO2 on copper?. J. Phys. Chem. Lett. 2018, 9, 601606,  DOI: 10.1021/acs.jpclett.7b03180
  50. 50
    Fields, M.; Hong, X.; Nørskov, J. K.; Chan, K. Role of subsurface oxygen on Cu surfaces for CO2 electrochemical reduction. J. Phys. Chem. C 2018, 122, 1620916215,  DOI: 10.1021/acs.jpcc.8b04983
  51. 51
    Bagger, A.; Ju, W.; Varela, A. S.; Strasser, P.; Rossmeisl, J. Electrochemical CO2 reduction: Classifying Cu facets. ACS Catal. 2019, 9, 78947899,  DOI: 10.1021/acscatal.9b01899
  52. 52
    Calle-Vallejo, F.; Tymoczko, J.; Colic, V.; Vu, Q. H.; Pohl, M. D.; Morgenstern, K.; Loffreda, D.; Sautet, P.; Schuhmann, W.; Bandarenka, A. S. Finding optimal surface sites on heterogeneous catalysts by counting nearest neighbors. Science 2015, 350, 185189,  DOI: 10.1126/science.aab3501
  53. 53
    Fung, V.; Tao, F. F.; Jiang, D. E. General structure-reactivity relationship for oxygen on transition-metal oxides. J. Phys. Chem. Lett. 2017, 8, 22062211,  DOI: 10.1021/acs.jpclett.7b00861
  54. 54
    Zhang, Z.; Zandkarimi, B.; Alexandrova, A. N. Ensembles of metastable states govern heterogeneous catalysis on dynamic interfaces. Acc. Chem. Res. 2020, 53, 447458,  DOI: 10.1021/acs.accounts.9b00531
  55. 55
    Dattila, F. Supporting Videos 1–7; https://iochem-bd.iciq.es/browse/handle/100/26145, 2020 (accessed 2020-07-24).
  56. 56
    Yang, F.; Choi, Y.; Liu, P.; Hrbek, J.; Rodriguez, J. A. Autocatalytic reduction of a Cu2O/Cu(111) surface by CO: STM, XPS, and DFT studies. J. Phys. Chem. C 2010, 114, 1704217050,  DOI: 10.1021/jp1029079
  57. 57
    Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 1996, 77, 38653868,  DOI: 10.1103/PhysRevLett.77.3865
  58. 58
    Fishman, M.; Zhuang, H. L.; Mathew, K.; Dirschka, W.; Hennig, R. G. Accuracy of exchange-correlation functionals and effect of solvation on the surface energy of copper. Phys. Rev. B: Condens. Matter Mater. Phys. 2013, 87, 245402,  DOI: 10.1103/PhysRevB.87.245402
  59. 59
    Mathew, K.; Sundararaman, R.; Letchworth-Weaver, K.; Arias, T. A.; Hennig, R. G. Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways. J. Chem. Phys. 2014, 140, 084106,  DOI: 10.1063/1.4865107
  60. 60
    Singh, A. K.; Zhou, L.; Shinde, A.; Suram, S. K.; Montoya, J. H.; Winston, D.; Gregoire, J. M.; Persson, K. A. Electrochemical stability of metastable materials. Chem. Mater. 2017, 29, 1015910167,  DOI: 10.1021/acs.chemmater.7b03980
  61. 61
    Guan, R.; Hashimoto, H.; Kuo, K. H. Electron-microscopic study of the structure of metastable oxides formed in the initial stage of copper oxidation. II. Cu8O. Acta Crystallogr., Sect. B: Struct. Sci. 1984, B40, 560566,  DOI: 10.1107/S010876818400269X
  62. 62
    Bohra, D.; Chaudhry, J. H.; Burdyny, T.; Pidko, E. A.; Smith, W. A. Modeling the electrical double layer to understand the reaction environment in a CO2 electrocatalytic system. Energy Environ. Sci. 2019, 12, 33803389,  DOI: 10.1039/C9EE02485A
  63. 63
    Zhang, F.; Co, A. C. Direct evidence of local pH change and the role of alkali cation during CO2 electroreduction in aqueous media. Angew. Chem., Int. Ed. 2020, 59, 16741681,  DOI: 10.1002/anie.201912637
  64. 64
    Zhang, W.; Huang, C.; Xiao, Q.; Yu, L.; Shuai, L.; An, P.; Zhang, J.; Qiu, M.; Ren, Z.; Yu, Y. Atypical oxygen-bearing copper boosts ethylene selectivity toward electrocatalytic CO2 reduction. J. Am. Chem. Soc. 2020, 142, 1141711427,  DOI: 10.1021/jacs.0c01562
  65. 65
    Bai, H. Controllable CO adsorption determines ethylene and methane productions from CO2 electroreduction. Sci. Bull. 2020,  DOI: 10.1016/j.scib.2020.06.023
  66. 66
    Yu, J.; Namba, Y. Atomic surface roughness. Appl. Phys. Lett. 1998, 73, 36073609,  DOI: 10.1063/1.122839
  67. 67
    Xu, H. Highly selective electrocatalytic CO2 reduction to ethanol by metallic clusters dynamically formed from atomically dispersed copper. Nat. Energy 2020, 5, 623632,  DOI: 10.1038/s41560-020-0666-x
  68. 68
    Jiao, J. Copper atom-pair catalyst anchored on alloy nanowires for selective and efficient electrochemical reduction of CO2. Nat. Chem. 2019, 11, 222228,  DOI: 10.1038/s41557-018-0201-x
  69. 69
    Calle-Vallejo, F.; Koper, M. T. M. Theoretical considerations on the electroreduction of CO to C2 species on Cu(100) electrodes. Angew. Chem., Int. Ed. 2013, 52, 72827285,  DOI: 10.1002/anie.201301470
  70. 70
    Jiang, K.; Sandberg, R. B.; Akey, A. J.; Liu, X.; Bell, D. C.; Nørskov, J. K.; Chan, K.; Wang, H. Metal ion cycling of Cu foil for selective C–C coupling in electrochemical CO2 reduction. Nat. Catal. 2018, 1, 111119,  DOI: 10.1038/s41929-017-0009-x
  71. 71
    Dattila, F. Glyoxylate-like configurations: (Oss)OCCO, sites 1–9.  DOI: 10.19061/iochem-bd-1-165 , 2020 (accessed 2020-07-24).
  72. 72
    Muchowska, K. B.; Varma, S. J.; Moran, J. Synthesis and breakdown of universal metabolic precursors promoted by iron. Nature 2019, 569, 104107,  DOI: 10.1038/s41586-019-1151-1
  73. 73
    Handoko, A. D.; Wei, F.; Jenndy; Yeo, B. S.; Seh, Z. W. Understanding heterogeneous electrocatalytic carbon dioxide reduction through operando techniques. Nat. Catal. 2018, 1, 922934,  DOI: 10.1038/s41929-018-0182-6
  74. 74
    Katayama, Y.; Nattino, F.; Giordano, L.; Hwang, J.; Rao, R. R.; Andreussi, O.; Marzari, N.; Shao-Horn, Y. An in Situ surface-enhanced infrared absorption spectroscopy study of electrochemical CO2 reduction: Selectivity dependence on surface C-bound and O-bound reaction intermediates. J. Phys. Chem. C 2019, 123, 59515963,  DOI: 10.1021/acs.jpcc.8b09598
  75. 75
    Verdaguer-Casadevall, A.; Li, C. W.; Johansson, T. P.; Scott, S. B.; McKeown, J. T.; Kumar, M.; Stephens, I. E.; Kanan, M. W.; Chorkendorff, I. Probing the active surface sites for CO reduction on oxide-derived copper electrocatalysts. J. Am. Chem. Soc. 2015, 137, 98089811,  DOI: 10.1021/jacs.5b06227
  76. 76
    Álvarez-Moreno, M.; de Graaf, C.; López, N.; Maseras, F.; Poblet, J.; Bo, C. Managing the computational chemistry big data problem: The ioChem-BD Platform. J. Chem. Inf. Model. 2015, 55, 95103,  DOI: 10.1021/ci500593j

Cited By

ARTICLE SECTIONS
Jump To

This article is cited by 70 publications.

  1. Chang Long, Kaiwei Wan, Yu Chen, Lei Li, Yuheng Jiang, Caoyu Yang, Qianbao Wu, Guoling Wu, Peng Xu, Jiong Li, Xinghua Shi, Zhiyong Tang, Chunhua Cui. Steering the Reconstruction of Oxide-Derived Cu by Secondary Metal for Electrosynthesis of n-Propanol from CO. Journal of the American Chemical Society 2024, 146 (7) , 4632-4641. https://doi.org/10.1021/jacs.3c11359
  2. Chansol Kim, Nitish Govindarajan, Sydney Hemenway, Junho Park, Anya Zoraster, Calton J. Kong, Rajiv Ramanujam Prabhakar, Joel B. Varley, Hee-Tae Jung, Christopher Hahn, Joel W. Ager. Importance of Site Diversity and Connectivity in Electrochemical CO Reduction on Cu. ACS Catalysis 2024, Article ASAP.
  3. Hyun Jun Kim, Giyeok Lee, Seung-Hyun Victor Oh, Catherine Stampfl, Aloysius Soon. Recalibrating the Experimentally Derived Structure of the Metastable Surface Oxide on Copper via Machine Learning-Accelerated In Silico Global Optimization. ACS Nano 2024, 18 (5) , 4559-4569. https://doi.org/10.1021/acsnano.3c12249
  4. Haibin Ma, Enric Ibáñez-Alé, Ramesha Ganganahalli, Javier Pérez-Ramírez, Núria López, Boon Siang Yeo. Direct Electroreduction of Carbonate to Formate. Journal of the American Chemical Society 2023, 145 (45) , 24707-24716. https://doi.org/10.1021/jacs.3c08079
  5. Lei Chen, Jingyi Chen, Lei Fan, Jiayi Chen, Tianyu Zhang, Junmei Chen, Shibo Xi, Baoliang Chen, Lei Wang. Additive-Assisted Electrodeposition of Cu on Gas Diffusion Electrodes Enables Selective CO2 Reduction to Multicarbon Products. ACS Catalysis 2023, 13 (18) , 11934-11944. https://doi.org/10.1021/acscatal.3c01815
  6. Hongyu An, Jim de Ruiter, Longfei Wu, Shuang Yang, Florian Meirer, Ward van der Stam, Bert M. Weckhuysen. Spatiotemporal Mapping of Local Heterogeneities during Electrochemical Carbon Dioxide Reduction. JACS Au 2023, 3 (7) , 1890-1901. https://doi.org/10.1021/jacsau.3c00129
  7. Julian Guerrero, Nathanaelle Schneider, Fabienne Dumoulin, Daniel Lincot, Umit Isci, Negar Naghavi, Marc Robert. Transparent Porous ZnO|Metal Complex Nanostructured Materials: Application to Electrocatalytic CO2 Reduction. ACS Applied Nano Materials 2023, 6 (12) , 10626-10635. https://doi.org/10.1021/acsanm.3c01591
  8. Chia-Jui Chang, Yi-An Lai, You-Chiuan Chu, Chun-Kuo Peng, Hui-Ying Tan, Chih-Wen Pao, Yan-Gu Lin, Sung-Fu Hung, Hsiao-Chien Chen, Hao Ming Chen. Lewis Acidic Support Boosts C–C Coupling in the Pulsed Electrochemical CO2 Reaction. Journal of the American Chemical Society 2023, 145 (12) , 6953-6965. https://doi.org/10.1021/jacs.3c00472
  9. Ward van der Stam. The Necessity for Multiscale In Situ Characterization of Tailored Electrocatalyst Nanoparticle Stability. Chemistry of Materials 2023, 35 (2) , 386-394. https://doi.org/10.1021/acs.chemmater.2c03286
  10. Ruonan Duan, Laixing Luo, Wu Qin, Xianbin Xiao, Rhonin Zhou, Zongming Zheng. Effects of *CO Coverage on Selective Electrocatalytic Reduction of CO2 to Ethylene over Cu2O with Undercoordinated Cu Sites. The Journal of Physical Chemistry C 2022, 126 (49) , 20878-20885. https://doi.org/10.1021/acs.jpcc.2c06898
  11. Yanyan Ding, Yangyang Xu, Lixin Zhang. Structures, Scaling Relations, and Selectivities of the Copper-Based Binary Catalysts for CO2 Reduction Reactions. The Journal of Physical Chemistry C 2022, 126 (42) , 17966-17974. https://doi.org/10.1021/acs.jpcc.2c06184
  12. Jim de Ruiter, Hongyu An, Longfei Wu, Zamorano Gijsberg, Shuang Yang, Thomas Hartman, Bert M. Weckhuysen, Ward van der Stam. Probing the Dynamics of Low-Overpotential CO2-to-CO Activation on Copper Electrodes with Time-Resolved Raman Spectroscopy. Journal of the American Chemical Society 2022, 144 (33) , 15047-15058. https://doi.org/10.1021/jacs.2c03172
  13. Federico Dattila, Ranga Rohit Seemakurthi, Yecheng Zhou, Núria López. Modeling Operando Electrochemical CO2 Reduction. Chemical Reviews 2022, 122 (12) , 11085-11130. https://doi.org/10.1021/acs.chemrev.1c00690
  14. Xiao Kun Lu, Bingzhang Lu, Haifeng Li, Khantey Lim, Linsey C. Seitz. Stabilization of Undercoordinated Cu Sites in Strontium Copper Oxides for Enhanced Formation of C2+ Products in Electrochemical CO2 Reduction. ACS Catalysis 2022, 12 (11) , 6663-6671. https://doi.org/10.1021/acscatal.2c01019
  15. Mengmeng Song, Zihao Jiao, Wenhao Jing, Ya Liu, Liejin Guo. Revealing the Nature of C–C Coupling Sites on a Cu Surface for CO2 Reduction. The Journal of Physical Chemistry Letters 2022, 13 (20) , 4434-4440. https://doi.org/10.1021/acs.jpclett.2c01010
  16. Michael T. Tang, Hong-Jie Peng, Joakim H. Stenlid, Frank Abild-Pedersen. Exploring Trends on Coupling Mechanisms toward C3 Product Formation in CO(2)R. The Journal of Physical Chemistry C 2021, 125 (48) , 26437-26447. https://doi.org/10.1021/acs.jpcc.1c07553
  17. Hakhyeon Song, Ying Chuan Tan, Beomil Kim, Stefan Ringe, Jihun Oh. Tunable Product Selectivity in Electrochemical CO2 Reduction on Well-Mixed Ni–Cu Alloys. ACS Applied Materials & Interfaces 2021, 13 (46) , 55272-55280. https://doi.org/10.1021/acsami.1c19224
  18. Joseph A. Gauthier, Joakim Halldin Stenlid, Frank Abild-Pedersen, Martin Head-Gordon, Alexis T. Bell. The Role of Roughening to Enhance Selectivity to C2+ Products during CO2 Electroreduction on Copper. ACS Energy Letters 2021, 6 (9) , 3252-3260. https://doi.org/10.1021/acsenergylett.1c01485
  19. Chao Zhan, Federico Dattila, Clara Rettenmaier, Arno Bergmann, Stefanie Kühl, Rodrigo García-Muelas, Núria López, Beatriz Roldan Cuenya. Revealing the CO Coverage-Driven C–C Coupling Mechanism for Electrochemical CO2 Reduction on Cu2O Nanocubes via Operando Raman Spectroscopy. ACS Catalysis 2021, 11 (13) , 7694-7701. https://doi.org/10.1021/acscatal.1c01478
  20. Pengwei Qi, Liang Zhao, Zhao Deng, Hao Sun, Hailong Li, Qi Liu, Xiang Li, Yuebin Lian, Jian Cheng, Jun Guo, Yi Cui, Yang Peng. Revisiting the Grain and Valence Effect of Oxide-Derived Copper on Electrocatalytic CO2 Reduction Using Single Crystal Cu(111) Foils. The Journal of Physical Chemistry Letters 2021, 12 (16) , 3941-3950. https://doi.org/10.1021/acs.jpclett.1c00588
  21. Wan Jae Dong, Jin Wook Lim, Dae Myung Hong, Jiwon Kim, Jae Yong Park, Won Seok Cho, Sangwon Baek, Jong-Lam Lee. Grain Boundary Engineering of Cu–Ag Thin-Film Catalysts for Selective (Photo)Electrochemical CO2 Reduction to CO and CH4. ACS Applied Materials & Interfaces 2021, 13 (16) , 18905-18913. https://doi.org/10.1021/acsami.1c03735
  22. Yue Wang, Xinfa Wei, Yan Li, Juanjuan Luo, Lisong Chen, Jianlin Shi. Benzyl alcohol promoted electrocatalytic reduction of carbon dioxide and C2 production by Cu2O/Cu. Chemical Engineering Journal 2024, 485 , 149800. https://doi.org/10.1016/j.cej.2024.149800
  23. Zeyu Guo, Fabao Yang, Xiaotong Li, Huiwen Zhu, Hainam Do, Kam Loon Fow, Jonathan D. Hirst, Tao Wu, Qiulin Ye, Yaqi Peng, Hao Bin Wu, Angjian Wu, Mengxia Xu. Electrocatalytic CO2 reduction to C2H4: From lab to fab. Journal of Energy Chemistry 2024, 90 , 540-564. https://doi.org/10.1016/j.jechem.2023.11.019
  24. Ernest Pastor, Zan Lian, Lu Xia, David Ecija, José Ramón Galán-Mascarós, Sara Barja, Sixto Giménez, Jordi Arbiol, Núria López, F. Pelayo García de Arquer. Complementary probes for the electrochemical interface. Nature Reviews Chemistry 2024, 355 https://doi.org/10.1038/s41570-024-00575-5
  25. Linfei Zhao, Bingsheng Xu, Zhangfu Yuan, Hongbiao Dong, Hongxin Zhao, Desheng Chen, Xiaohan Ding. Surface regulation of Cu-based catalysts to adjust the selectivity and promotion strategy of electrochemical reduction of CO2 to C2 products. Journal of Environmental Chemical Engineering 2024, 12 (1) , 111905. https://doi.org/10.1016/j.jece.2024.111905
  26. Fuping Pan, Xinyi Duan, Lingzhe Fang, Haoyang Li, Zhen Xu, Yu Wang, Teng Wang, Tao Li, Zhiyao Duan, Kai‐Jie Chen. Long‐Range Confinement‐Driven Enrichment of Surface Oxygen‐Relevant Species Promotes C−C Electrocoupling in CO 2 Reduction. Advanced Energy Materials 2024, 14 (7) https://doi.org/10.1002/aenm.202303118
  27. Wenjun Zhang, Yang Yang, Donggang Guo, Lu Liu. Recent progress on copper catalysts with different surface states for CO2 electroreduction. Journal of Energy Chemistry 2024, 88 , 10-27. https://doi.org/10.1016/j.jechem.2023.09.002
  28. Yongchan Jeong, Yongman Kim, Young Jae Kim, Jeong Young Park. In Situ Probing of CO 2 Reduction on Cu‐Phthalocyanine‐Derived Cu x O Complex. Advanced Science 2024, 11 (4) https://doi.org/10.1002/advs.202304735
  29. Jan Vavra, Gaétan P. L. Ramona, Federico Dattila, Attila Kormányos, Tatiana Priamushko, Petru P. Albertini, Anna Loiudice, Serhiy Cherevko, Núria Lopéz, Raffaella Buonsanti. Solution-based Cu+ transient species mediate the reconstruction of copper electrocatalysts for CO2 reduction. Nature Catalysis 2024, 7 (1) , 89-97. https://doi.org/10.1038/s41929-023-01070-8
  30. Mohamed M. Elnagar, Pramod V. Menezes, Walter A. Parada, Yannick Mattausch, Ludwig A. Kibler, Karl J. J. Mayrhofer, Timo Jacob. Tailoring Cu Electrodes for Enhanced CO 2 Electroreduction through Plasma Electrolysis in Non‐Conventional Phosphorus‐Oxoanion‐Based Electrolytes. ChemSusChem 2023, 16 (23) https://doi.org/10.1002/cssc.202300934
  31. Harsh R. Darji, Hanumant B. Kale, Farhan F. Shaikh, Manoj B. Gawande. Advancement and State-of-art of heterogeneous catalysis for selective CO2 hydrogenation to methanol. Coordination Chemistry Reviews 2023, 497 , 215409. https://doi.org/10.1016/j.ccr.2023.215409
  32. Mengmeng Song, Zihao Jiao, Wenhao Jing, Ya Liu, Liejin Guo. How *CO spill-over affects C–C coupling on amorphous Cu for converting CO2 to multi-carbon products. Journal of Catalysis 2023, 428 , 115170. https://doi.org/10.1016/j.jcat.2023.115170
  33. Reihaneh Amirbeigiarab, Jing Tian, Antonia Herzog, Canrong Qiu, Arno Bergmann, Beatriz Roldan Cuenya, Olaf M. Magnussen. Atomic-scale surface restructuring of copper electrodes under CO2 electroreduction conditions. Nature Catalysis 2023, 6 (9) , 837-846. https://doi.org/10.1038/s41929-023-01009-z
  34. Martina Serafini, Federica Mariani, Francesco Basile, Erika Scavetta, Domenica Tonelli. From Traditional to New Benchmark Catalysts for CO2 Electroreduction. Nanomaterials 2023, 13 (11) , 1723. https://doi.org/10.3390/nano13111723
  35. Juan‐Jesús Velasco‐Vélez, Jeffrey Poon, Dunfeng Gao, Cheng‐Hao Chuang, Arno Bergmann, Travis E. Jones, Shu‐Chih Haw, Jin‐Ming Chen, Emilia Carbonio, Rik V. Mom, Danail Ivanov, Rosa Arrigo, Beatriz Roldan Cuenya, Axel Knop‐Gericke, Robert Schlögl. Cationic Copper Species Stabilized by Zinc during the Electrocatalytic Reduction of CO 2 Revealed by In Situ X‐Ray Spectroscopy. Advanced Sustainable Systems 2023, 7 (5) https://doi.org/10.1002/adsu.202200453
  36. Juhee Jang, Shangqian Zhu, Ernest Pahuyo Delmo, Tiehuai Li, Qinglan Zhao, Yinuo Wang, Lili Zhang, Hongwen Huang, Jingjie Ge, Minhua Shao. Facile design of oxide‐derived Cu nanosheet electrocatalyst for CO 2 reduction reaction. EcoMat 2023, 5 (5) https://doi.org/10.1002/eom2.12334
  37. Chen-Cheng Liao, Tsung-Han Tsai, Chun-Chih Chang, Ming-Kang Tsai. The use of plate-type electric force field for the explicit simulations of electrochemical CO dimerization on Cu(1 1 1) surface. Chemical Physics 2023, 568 , 111821. https://doi.org/10.1016/j.chemphys.2023.111821
  38. Matteo Cioni, Daniela Polino, Daniele Rapetti, Luca Pesce, Massimo Delle Piane, Giovanni M. Pavan. Innate dynamics and identity crisis of a metal surface unveiled by machine learning of atomic environments. The Journal of Chemical Physics 2023, 158 (12) https://doi.org/10.1063/5.0139010
  39. Jianfang Zhang, Zhengyuan Li, Rui Cai, Tianyu Zhang, Shize Yang, Lu Ma, Yan Wang, Yucheng Wu, Jingjie Wu. Switching CO 2 Electroreduction Selectivity Between C 1 and C 2 Hydrocarbons on Cu Gas‐Diffusion Electrodes. ENERGY & ENVIRONMENTAL MATERIALS 2023, 6 (2) https://doi.org/10.1002/eem2.12307
  40. Tangsheng Zou, Florentine L.P. Veenstra, Enric Ibáñez-Alé, Rodrigo García-Muelas, Guido Zichittella, Antonio J. Martín, Núria López, Javier Pérez-Ramírez. Chlorine-promoted copper catalysts for CO2 electroreduction into highly reduced products. Cell Reports Physical Science 2023, 4 (3) , 101294. https://doi.org/10.1016/j.xcrp.2023.101294
  41. Hui Ning, Zhenmei Jiao, Peifang Lu, Mingwang Wang, Yani Wang, Li Wang, Yan Zhao, Xiang Fei, Dewen Song, Mingbo Wu. UV‐Light‐Induced Surface Reconstruction of Cubic Cu 2 O Promotes CO 2 Electroreduction to C 2 Products. Chemistry – An Asian Journal 2022, 17 (24) https://doi.org/10.1002/asia.202200980
  42. Qiong Lei, Liang Huang, Jun Yin, Bambar Davaasuren, Youyou Yuan, Xinglong Dong, Zhi-Peng Wu, Xiaoqian Wang, Ke Xin Yao, Xu Lu, Yu Han. Structural evolution and strain generation of derived-Cu catalysts during CO2 electroreduction. Nature Communications 2022, 13 (1) https://doi.org/10.1038/s41467-022-32601-9
  43. Ibrahim M. Badawy, Ahmed Mohsen Ismail, Ghada E. Khedr, Manar M. Taha, Nageh K. Allam. Selective electrochemical reduction of CO2 on compositionally variant bimetallic Cu–Zn electrocatalysts derived from scrap brass alloys. Scientific Reports 2022, 12 (1) https://doi.org/10.1038/s41598-022-17317-6
  44. Pengfei Hou, Yumiao Tian, Di Jin, Xiaochun Liu, Yu Xie, Fei Du, Xing Meng. Advances in theoretical calculations of MXenes as hydrogen and oxygen evolution reaction (water splitting) electrocatalysts. Journal of Physics D: Applied Physics 2022, 55 (46) , 464002. https://doi.org/10.1088/1361-6463/ac8b1a
  45. Ernest Pastor, Laura Montañés, Ana Gutiérrez-Blanco, Franziska S. Hegner, Camilo A. Mesa, Núria López, Sixto Giménez. The role of crystal facets and disorder on photo-electrosynthesis. Nanoscale 2022, 14 (42) , 15596-15606. https://doi.org/10.1039/D2NR03609F
  46. Hengzhou Liu, Naveen Agrawal, Arna Ganguly, Yifu Chen, Jungkuk Lee, Jiaqi Yu, Wenyu Huang, Mark Mba Wright, Michael J. Janik, Wenzhen Li. Ultra-low voltage bipolar hydrogen production from biomass-derived aldehydes and water in membrane-less electrolyzers. Energy & Environmental Science 2022, 15 (10) , 4175-4189. https://doi.org/10.1039/D2EE01427K
  47. Robert H. Lavroff, Harry W. T. Morgan, Zisheng Zhang, Patricia Poths, Anastassia N. Alexandrova. Ensemble representation of catalytic interfaces: soloists, orchestras, and everything in-between. Chemical Science 2022, 13 (27) , 8003-8016. https://doi.org/10.1039/D2SC01367C
  48. Yi‐Rung Lin, Dong Un Lee, Shunquan Tan, David M. Koshy, Tiras Y. Lin, Lei Wang, Daniel Corral, Jaime E. Avilés Acosta, Jose A. Zamora Zeledon, Victor A. Beck, Sarah E. Baker, Eric B. Duoss, Christopher Hahn, Thomas F. Jaramillo. Vapor‐Fed Electrolyzers for Carbon Dioxide Reduction Using Tandem Electrocatalysts: Cuprous Oxide Coupled with Nickel‐Coordinated Nitrogen‐Doped Carbon. Advanced Functional Materials 2022, 32 (28) https://doi.org/10.1002/adfm.202113252
  49. Jianfang Zhang, Yan Wang, Zhengyuan Li, Shuai Xia, Rui Cai, Lu Ma, Tianyu Zhang, Josh Ackley, Shize Yang, Yucheng Wu, Jingjie Wu. Grain Boundary‐Derived Cu + /Cu 0 Interfaces in CuO Nanosheets for Low Overpotential Carbon Dioxide Electroreduction to Ethylene. Advanced Science 2022, 9 (21) https://doi.org/10.1002/advs.202200454
  50. Liren Sun, Jinyu Han, Qingfeng Ge, Xinli Zhu, Hua Wang. Understanding the role of Cu + /Cu 0 sites at Cu 2 O based catalysts in ethanol production from CO 2 electroreduction -A DFT study. RSC Advances 2022, 12 (30) , 19394-19401. https://doi.org/10.1039/D2RA02753D
  51. Chongyi Ling, Yu Cui, Shuaihua Lu, Xiaowan Bai, Jinlan Wang. How computations accelerate electrocatalyst discovery. Chem 2022, 8 (6) , 1575-1610. https://doi.org/10.1016/j.chempr.2022.03.015
  52. Chenyuan Zhu, Siwen Zhao, Guoshuai Shi, Liming Zhang. Structure‐Function Correlation and Dynamic Restructuring of Cu for Highly Efficient Electrochemical CO 2 Conversion. ChemSusChem 2022, 15 (7) https://doi.org/10.1002/cssc.202200068
  53. Janis Timoshenko, Arno Bergmann, Clara Rettenmaier, Antonia Herzog, Rosa M. Arán-Ais, Hyo Sang Jeon, Felix T. Haase, Uta Hejral, Philipp Grosse, Stefanie Kühl, Earl M. Davis, Jing Tian, Olaf Magnussen, Beatriz Roldan Cuenya. Steering the structure and selectivity of CO2 electroreduction catalysts by potential pulses. Nature Catalysis 2022, 5 (4) , 259-267. https://doi.org/10.1038/s41929-022-00760-z
  54. Sathya Mohan, Brahmari Honnappa, Ashil Augustin, Mariyappan Shanmugam, Chitiphon Chuaicham, Keiko Sasaki, Boopathy Ramasamy, Karthikeyan Sekar. A Critical Study of Cu2O: Synthesis and Its Application in CO2 Reduction by Photochemical and Electrochemical Approaches. Catalysts 2022, 12 (4) , 445. https://doi.org/10.3390/catal12040445
  55. Lucas G. Verga, Paulo C. D. Mendes, Vivianne K. Ocampo-Restrepo, Juarez L. F. Da Silva. Exploring the adsorption site coordination as a strategy to tune copper catalysts for CO 2 electro-reduction. Catalysis Science & Technology 2022, 12 (3) , 869-879. https://doi.org/10.1039/D1CY02010B
  56. Dhivyasundar Sundar, Lakshmanan Karuppasamy, Lakshmanan Gurusamy, Cheng-Hua Liu, Jerry J. Wu. Perovskites-like composites for CO2 photoreduction into hydrocarbon fuels. Current Opinion in Green and Sustainable Chemistry 2022, 33 , 100563. https://doi.org/10.1016/j.cogsc.2021.100563
  57. Sergio Pablo-García, Florentine L. P. Veenstra, Louisa Rui Lin Ting, Rodrigo García-Muelas, Federico Dattila, Antonio J. Martín, Boon Siang Yeo, Javier Pérez-Ramírez, Núria López. Mechanistic routes toward C 3 products in copper-catalysed CO 2 electroreduction. Catalysis Science & Technology 2022, 12 (2) , 409-417. https://doi.org/10.1039/D1CY01423D
  58. Da Li, Hao Zhang, Hang Xiang, Shahid Rasul, Jean-Marie Fontmorin, Paniz Izadi, Alberto Roldan, Rebecca Taylor, Yujie Feng, Liam Banerji, Alexander Cowan, Eileen Hao Yu, Jin Xuan. How to go beyond C 1 products with electrochemical reduction of CO 2. Sustainable Energy & Fuels 2021, 5 (23) , 5893-5914. https://doi.org/10.1039/D1SE00861G
  59. Saudagar Dongare, Neetu Singh, Haripada Bhunia, Pramod K. Bajpai, Asit Kumar Das. Electrochemical Reduction of Carbon Dioxide to Ethanol: A Review. ChemistrySelect 2021, 6 (42) , 11603-11629. https://doi.org/10.1002/slct.202102829
  60. Sebastian Kunze, Liviu C. Tănase, Mauricio J. Prieto, Philipp Grosse, Fabian Scholten, Lucas de Souza Caldas, Dennis van Vörden, Thomas Schmidt, Beatriz Roldan Cuenya. Plasma-assisted oxidation of Cu(100) and Cu(111). Chemical Science 2021, 12 (42) , 14241-14253. https://doi.org/10.1039/D1SC04861A
  61. Sergio Pablo‐García, Rodrigo García‐Muelas, Albert Sabadell‐Rendón, Núria López. Dimensionality reduction of complex reaction networks in heterogeneous catalysis: From l inear‐scaling relationships to statistical learning techniques. WIREs Computational Molecular Science 2021, 11 (6) https://doi.org/10.1002/wcms.1540
  62. Katherine Villa, José Ramón Galán-Mascarós, Núria López, Emilio Palomares. Photocatalytic water splitting: advantages and challenges. Sustainable Energy & Fuels 2021, 5 (18) , 4560-4569. https://doi.org/10.1039/D1SE00808K
  63. Zhongyuan Xie, Yuan Qiu, Sanshuang Gao, Jiaqiang Sun, Huanqi Cao, Shusheng Zhang, Jun Luo, Xijun Liu. Surface Oxidized Ag Nanofilms Towards Highly Effective CO 2 Reduction. ChemElectroChem 2021, 8 (18) , 3579-3583. https://doi.org/10.1002/celc.202100921
  64. Hongyu An, Longfei Wu, Laurens D. B. Mandemaker, Shuang Yang, Jim de Ruiter, Jochem H. J. Wijten, Joris C. L. Janssens, Thomas Hartman, Ward van der Stam, Bert M. Weckhuysen. Sub‐Second Time‐Resolved Surface‐Enhanced Raman Spectroscopy Reveals Dynamic CO Intermediates during Electrochemical CO 2 Reduction on Copper. Angewandte Chemie 2021, 133 (30) , 16712-16720. https://doi.org/10.1002/ange.202104114
  65. Hongyu An, Longfei Wu, Laurens D. B. Mandemaker, Shuang Yang, Jim de Ruiter, Jochem H. J. Wijten, Joris C. L. Janssens, Thomas Hartman, Ward van der Stam, Bert M. Weckhuysen. Sub‐Second Time‐Resolved Surface‐Enhanced Raman Spectroscopy Reveals Dynamic CO Intermediates during Electrochemical CO 2 Reduction on Copper. Angewandte Chemie International Edition 2021, 60 (30) , 16576-16584. https://doi.org/10.1002/anie.202104114
  66. Xuerui Cao, Guangwei Cao, Mei Li, Xinli Zhu, Jinyu Han, Qingfeng Ge, Hua Wang. Enhanced Ethylene Formation from Carbon Dioxide Reduction through Sequential Catalysis on Au Decorated Cubic Cu 2 O Electrocatalyst. European Journal of Inorganic Chemistry 2021, 2021 (24) , 2353-2364. https://doi.org/10.1002/ejic.202100229
  67. Benjamin A. Zhang, Daniel G. Nocera. Cascade Electrochemical Reduction of Carbon Dioxide with Bimetallic Nanowire and Foam Electrodes. ChemElectroChem 2021, 8 (10) , 1918-1924. https://doi.org/10.1002/celc.202100295
  68. Y. Zhong, S. Wang, M. Li, J. Ma, S. Song, A. Kumar, H. Duan, Y. Kuang, X. Sun. Rational design of copper-based electrocatalysts and electrochemical systems for CO2 reduction: From active sites engineering to mass transfer dynamics. Materials Today Physics 2021, 18 , 100354. https://doi.org/10.1016/j.mtphys.2021.100354
  69. Lucas G. Verga, Paulo C. D. Mendes, Vivianne K. Ocampo-Restrepo, Juarez L. F. Da Silva. The role of site coordination on the CO 2 electroreduction pathway on stepped and defective copper surfaces. Catalysis Science & Technology 2021, 11 (8) , 2770-2781. https://doi.org/10.1039/D0CY02337J
  70. Hilmar Guzmán, Nunzio Russo, Simelys Hernández. CO 2 valorisation towards alcohols by Cu-based electrocatalysts: challenges and perspectives. Green Chemistry 2021, 23 (5) , 1896-1920. https://doi.org/10.1039/D0GC03334K
  • Abstract

    Figure 1

    Figure 1. Models for OD-Cu. We considered two systems: (a) a Cu2O(111) slab to mimic Cu2O reduction (red-Cu2O) and (b) a Cu(111)/Cu2O configuration to resemble Cu oxidation (oxi-Cu) (side views). For each supercell, O atoms were partially removed from the two outermost layers to create three depletion motifs: (c) rhomboidal (4R, patch), (d) triangular (4T, pitting), and (e) linear (6L, strip) (top views). (f) A symmetrical, Cu-terminated system (SY-red-Cu2O) was included to investigate the influence of stoichiometry and depletion motifs. (g–i) After 10 ps of AIMD at 700 K, the final surfaces present analogous reconstruction (Videos S1–S7 (55)) and (j) STM characterization detected similar patterns as experimental Cu/Cu2O systems (56) (Figure S3). Red-Cu2O and oxi-Cu systems were labeled nS, with n number of O atoms removed from the subsurface and S the shape of the O depleted region (dark brown). Red-Cu2O and oxi-Cu suffixes were appended to differentiate both conditions.

    Figure 2

    Figure 2. Characterization of Cu species. (a–f) Cu–Cu RDF for Cu atoms coordinated with 0–2 oxygens as shown in the insets. The first (second) coordination shell of bulk Cu (Cu2O) is shown as black (red) dashed lines. Cu–Cu RDF for the SY-red-Cu2O system is reported in Figure S12. (g) Cu atoms coordinated to 0–2 oxygens show clear differences in their Bader charges and number of Cu atoms in their first coordination shell. (h–j) Cu–Cu coordination number (NCu–Cu) cumulative maps show peaks at integer NCu–Cu, suggesting the existence of recurring ensembles. Average Cu–Cu, dashed lines, differ by 1.0 units from metallic to polarized and almost 3.0 to oxidic Cu. Bader charges and NCu–Cu distributions for the remaining systems are reported in Figures S15 and S17.

    Figure 3

    Figure 3. Recurrent ensembles in OD-Cu models. (a–f) Histograms for angles θ(ABC) measured around the first coordination shell of central atom B at different heights z(B) for the 4R-red-Cu2O system. The ensembles responsible for each feature are labeled and shown in panel g; tetra- and hexa-coordinated Cu adatoms: Cu3Cu and Cu4Cu; reminiscent of crystalline Cu: Cu(100)-like facets, including distorted forms mainly metallic or asymmetric in charge (subscripts “d” and “da”), Cu(110) and Cu(111) facets; Cu3δ+O3; Cu/Cu2O grain boundaries, g.b. (Figure S2); tri- and tetra-coordinated O adatoms: O3Cu,ad and O4Cu,ad; tri- and tetra-coordinated planar O: O3Cu,p and O4Cu,p; penta-coordinated near-surface O: O5Cu; tetrahedral O: O4Cu,t; distorted near-surface O: O3Cu,d. Comparison with other models and values of Nmax are reported in Figures S21 and S22.

    Figure 4

    Figure 4. CO2R activity and C2+ selectivity of OD-Cu versus ensemble polarization. (a) OD-Cu can adsorb CO2 either on a Cu site (purple) or on a near-surface oxygen (magenta) forming a carbonate. CO2 adsorption energy scales linearly with the polarization of the active sites, Q1: . Cu0–Cuδ+ and Cuδ+–Cuδ+ are responsible for enhancing OD-Cu CO2R (purple area), while activity of Ons sites is limited by carbonate formation. (b) Polarization of active ensembles, Q2, drives selectivity to C2 products: ΔG*OCCO = +0.7(±0.1) – 0.7(±0.1)Q2. A paired active site, Cuδ+-Ons, stabilizes the CO–CO dimer as a glyoxylate-like intermediate (dark red), enhancing C2 production. In contrast, for metallic Cu sites (red) CO dimerization is not favored, leading to a higher *CO coverage (gray), ΔG2*CO = −1.3(±0.1) + 1.3(±0.1)Q2. For very strong polarization, stable oxalates are generated on the surface (black). Q1 and Q2 are defined as the sum of absolute Bader charges of the atoms in the ensemble calculated with implicit solvation (eqs S21 and S22, Figure S27). (c) *OCCO intermediate on both OD-Cu and Cu(100) and oxalate formation on OD-Cu presents a high kinetic barrier of more than 1 eV. The pathway toward the glyoxylate-like intermediate has instead a mild barrier of 0.53 eV. Potential and dipole corrections, here not included, stabilize all intermediates similarly (Table S16). Further details on the linear regressions are shown in Table S17.

  • References

    ARTICLE SECTIONS
    Jump To

    This article references 76 other publications.

    1. 1
      Nitopi, S. Progress and perspectives of electrochemical CO2 reduction on copper in aqueous electrolyte. Chem. Rev. 2019, 119, 76107672,  DOI: 10.1021/acs.chemrev.8b00705
    2. 2
      Birdja, Y. Y.; Pérez-Gallent, E.; Figueiredo, M. C.; Göttle, A. J.; Calle-Vallejo, F.; Koper, M. T. M. Advances and challenges in understanding the electrocatalytic conversion of carbon dioxide to fuels. Nat. Energy 2019, 4, 732745,  DOI: 10.1038/s41560-019-0450-y
    3. 3
      Peterson, A. A.; Abild-Pedersen, F.; Studt, F.; Rossmeisl, J.; Nørskov, J. K. How copper catalyzes the electroreduction of carbon dioxide into hydrocarbon fuels. Energy Environ. Sci. 2010, 3, 13111315,  DOI: 10.1039/c0ee00071j
    4. 4
      Hori, Y.; Murata, A.; Takahashi, R. Formation of hydrocarbons in the electrochemical reduction of carbon dioxide at a copper electrode in aqueous solution. J. Chem. Soc., Faraday Trans. 1 1989, 85, 23092326,  DOI: 10.1039/f19898502309
    5. 5
      De Luna, P.; Hahn, C.; Higgins, D.; Jaffer, S. A.; Jaramillo, T. F.; Sargent, E. H. What would it take for renewably powered electrosynthesis to displace petrochemical processes?. Science 2019, 364, 350,  DOI: 10.1126/science.aav3506
    6. 6
      Arán-Ais, R. M.; Scholten, F.; Kunze, S.; Rizo, R.; Roldan Cuenya, B. The role of in situ generated morphological motifs and Cu(I) species in C2+ product selectivity during CO2 pulsed electroreduction. Nat. Energy 2020, 5, 317325,  DOI: 10.1038/s41560-020-0594-9
    7. 7
      Gao, D.; Arán-Ais, R. M.; Jeon, H. S.; Roldán-Cuenya, B. Rational catalyst and electrolyte design for CO2 electroreduction towards multicarbon products. Nat. Catal. 2019, 2, 198210,  DOI: 10.1038/s41929-019-0235-5
    8. 8
      Huang, J.; Hörmann, N.; Oveisi, E.; Loiudice, A.; De Gregorio, G. L.; Andreussi, O.; Marzari, N.; Buonsanti, R. Potential-induced nanoclustering of metallic catalysts during electrochemical CO2 reduction. Nat. Commun. 2018, 9, 3117,  DOI: 10.1038/s41467-018-05544-3
    9. 9
      Kim, Y. G.; Baricuatro, J. H.; Javier, A.; Gregoire, J. M.; Soriaga, M. P. The evolution of the polycrystalline copper surface, first to Cu(111) and then to Cu(100), at a fixed CO2RR potential: A study by operando EC-STM. Langmuir 2014, 30, 1505315056,  DOI: 10.1021/la504445g
    10. 10
      Lum, Y.; Ager, J. W. Evidence for product-specific active sites on oxide-derived Cu catalysts for electrochemical CO2 reduction. Nat. Catal. 2019, 2, 8693,  DOI: 10.1038/s41929-018-0201-7
    11. 11
      Auer, A.; Andersen, M.; Wernig, E.-M.; Hörmann, N. G.; Buller, N.; Reuter, K.; Kunze-Liebhäuser, J. Self-activation of copper electrodes during CO electro-oxidation in alkaline electrolyte. Nat. Catal. 2020,  DOI: 10.1038/s41929-020-00505-w
    12. 12
      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, 3947,  DOI: 10.1016/S1381-1169(03)00016-5
    13. 13
      Kuhl, K. P.; Cave, E. R.; Abram, D. N.; Jaramillo, T. F. New insights into the electrochemical reduction of carbon dioxide on metallic copper surfaces. Energy Environ. Sci. 2012, 5, 70507059,  DOI: 10.1039/c2ee21234j
    14. 14
      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, 69786986,  DOI: 10.1021/ja500328k
    15. 15
      Chou, T.-C. Controlling the oxidation state of Cu electrode and reaction intermediates for electrochemical CO2 reduction to ethylene. J. Am. Chem. Soc. 2020, 142, 28572867,  DOI: 10.1021/jacs.9b11126
    16. 16
      Li, C. W.; Kanan, M. W. CO2 reduction at low overpotential on Cu electrodes resulting from the reduction of thick Cu2O films. J. Am. Chem. Soc. 2012, 134, 72317234,  DOI: 10.1021/ja3010978
    17. 17
      Li, C. W.; Ciston, J.; Kanan, M. W. Electroreduction of carbon monoxide to liquid fuel on oxide-derived nanocrystalline copper. Nature 2014, 508, 504507,  DOI: 10.1038/nature13249
    18. 18
      Ren, D.; Deng, Y.; Handoko, A. D.; Chen, C. S.; Malkhandi, S.; Yeo, B. S. Selective electrochemical reduction of carbon dioxide to ethylene and ethanol on copper(I) oxide catalysts. ACS Catal. 2015, 5, 28142821,  DOI: 10.1021/cs502128q
    19. 19
      Kim, D.; Lee, S.; Ocon, J. D.; Jeong, B.; Lee, J. K.; Lee, J. Insights into an autonomously formed oxygen-evacuated Cu2O electrode for the selective production of C2H4 from CO2. Phys. Chem. Chem. Phys. 2015, 17, 824830,  DOI: 10.1039/C4CP03172E
    20. 20
      Mistry, H. Highly selective plasma-activated copper catalysts for carbon dioxide reduction to ethylene. Nat. Commun. 2016, 7, 12123,  DOI: 10.1038/ncomms12123
    21. 21
      Handoko, A. D.; Ong, C. W.; Huang, Y.; Lee, Z. G.; Lin, L.; Panetti, G. B.; Yeo, B. S. Mechanistic insights into the selective electroreduction of carbon dioxide to ethylene on Cu2O-derived copper catalysts. J. Phys. Chem. C 2016, 120, 2005820067,  DOI: 10.1021/acs.jpcc.6b07128
    22. 22
      De Luna, P.; Quintero-Bermudez, R.; Dinh, C.-T.; Ross, M. B.; Bushuyev, O. S.; Todorović, P.; Regier, T.; Kelley, S. O.; Yang, P.; Sargent, E. H. Catalyst electro-redeposition controls morphology and oxidation state for selective carbon dioxide reduction. Nat. Catal. 2018, 1, 103110,  DOI: 10.1038/s41929-017-0018-9
    23. 23
      Lee, S. Y.; Jung, H.; Kim, N.-K.; Oh, H.-S.; Min, B. K.; Hwang, Y. J. Mixed copper states in anodized Cu electrocatalyst for stable and selective ethylene production from CO2 reduction. J. Am. Chem. Soc. 2018, 140, 86818689,  DOI: 10.1021/jacs.8b02173
    24. 24
      Li, J. Copper adparticle enabled selective electrosynthesis of n-propanol. Nat. Commun. 2018, 9, 4614,  DOI: 10.1038/s41467-018-07032-0
    25. 25
      Ting, L. R. L.; Garcia-Muelas, R.; Martin, A. J; Veenstra, F. L. P.; Chen, S. T.-J.; Peng, Y.; Per, E. Y. X.; Pablo Garcia, S.; Lopez, N.; Perez-Ramirez, J.; Yeo, B. S. Electrochemical reduction of carbon dioxide to 1-butanol on oxide-derived copper. Angew. Chem., Int. Ed. 2020, 25, 210,  DOI: 10.1002/anie.202008289
    26. 26
      Dutta, A.; Rahaman, M.; Luedi, N. C.; Mohos, M.; Broekmann, P. Morphology matters: tuning the product distribution of CO2 electroreduction on oxide-derived Cu foam catalysts. ACS Catal. 2016, 6, 38043814,  DOI: 10.1021/acscatal.6b00770
    27. 27
      Loiudice, A.; Lobaccaro, P.; Kamali, E. A.; Thao, T.; Huang, B. H.; Ager, J. W.; Buonsanti, R. Tailoring copper nanocrystals towards C2 products in electrochemical CO2 reduction. Angew. Chem., Int. Ed. 2016, 55, 57895792,  DOI: 10.1002/anie.201601582
    28. 28
      Lum, Y.; Ager, J. W. Stability of residual oxides in oxide-derived copper catalysts for electrochemical CO2 reduction investigated with 18O labeling. Angew. Chem., Int. Ed. 2018, 57, 551554,  DOI: 10.1002/anie.201710590
    29. 29
      Zhu, Q.; Sun, X.; Yang, D.; Ma, J.; Kang, X.; Zheng, L.; Zhang, J.; Wu, Z.; Han, B. Carbon dioxide electroreduction to C2 products over copper-cuprous oxide derived from electrosynthesized copper complex. Nat. Commun. 2019, 10, 3851,  DOI: 10.1038/s41467-019-11599-7
    30. 30
      Lin, S.-C.; Chang, C.-C.; Chiu, S.-Y.; Pai, H.-T.; Liao, T.-Y.; Hsu, C.-S.; Chiang, W.-H.; Tsai, M.-K.; Chen, H. M. Operando time-resolved X-ray absorption spectroscopy reveals the chemical nature enabling highly selective CO2 reduction. Nat. Commun. 2020, 11, 3525,  DOI: 10.1038/s41467-020-17231-3
    31. 31
      Kortlever, R.; Shen, J.; Schouten, K. J. P.; Calle-Vallejo, F.; Koper, M. T. M. Catalysts and reaction pathways for the electrochemical reduction of carbon dioxide. J. Phys. Chem. Lett. 2015, 6, 40734082,  DOI: 10.1021/acs.jpclett.5b01559
    32. 32
      Pérez-Gallent, E.; Figueiredo, M. C.; Calle-Vallejo, F.; Koper, M. T. M. Spectroscopic observation of a hydrogenated CO dimer intermediate during CO reduction on Cu(100) electrodes. Angew. Chem., Int. Ed. 2017, 56, 36213624,  DOI: 10.1002/anie.201700580
    33. 33
      Cheng, T.; Xiao, H.; Goddard, W. A. Nature of the active sites for CO reduction on copper nanoparticles; Suggestions for optimizing performance. J. Am. Chem. Soc. 2017, 139, 1164211645,  DOI: 10.1021/jacs.7b03300
    34. 34
      Feng, X.; Jiang, K.; Fan, S.; Kanan, M. W. A direct grain-boundary-activity correlation for CO electroreduction on Cu nanoparticles. ACS Cent. Sci. 2016, 2, 169174,  DOI: 10.1021/acscentsci.6b00022
    35. 35
      Wang, Y. Catalyst synthesis under CO2 electroreduction favours faceting and promotes renewable fuels electrosynthesis. Nat. Catal. 2020, 3, 98106,  DOI: 10.1038/s41929-019-0397-1
    36. 36
      Ringe, S.; Morales-Guio, C. G.; Chen, L. D.; Fields, M.; Jaramillo, T. F.; Hahn, C.; Chan, K. Double layer charging driven carbon dioxide adsorption limits the rate of electrochemical carbon dioxide reduction on Gold. Nat. Commun. 2020, 11, 33,  DOI: 10.1038/s41467-019-13777-z
    37. 37
      Veenstra, F. L.; Ackerl, N.; Martı́n, A. J.; Pérez-Ramı́rez, J. Laser-microstructured copper reveals selectivity patterns in the electrocatalytic reduction of CO2. Chem. 2020, 6, 17071722,  DOI: 10.1016/j.chempr.2020.04.001
    38. 38
      Velasco-Vélez, J.-J. The role of the copper oxidation state in the electrocatalytic reduction of CO2 into valuable hydrocarbons. ACS Sustainable Chem. Eng. 2019, 7, 14851492,  DOI: 10.1021/acssuschemeng.8b05106
    39. 39
      Favaro, M.; Xiao, H.; Cheng, T.; Goddard, W. A.; Yano, J.; Crumlin, E. J. Subsurface oxide plays a critical role in CO2 activation by Cu(111) surfaces to form chemisorbed CO2, the first step in reduction of CO2. Proc. Natl. Acad. Sci. U. S. A. 2017, 114, 67066711,  DOI: 10.1073/pnas.1701405114
    40. 40
      Velasco-Velez, J.-J. Revealing the active phase of copper during the electroreduction of CO2 in aqueous electrolyte by correlating In Situ X-ray spectroscopy and In Situ electron microscopy. ACS Energy Lett. 2020, 5, 21062111,  DOI: 10.1021/acsenergylett.0c00802
    41. 41
      Zhao, Y.; Chang, X.; Malkani, A. S.; Yang, X.; Thompson, L.; Jiao, F.; Xu, B. Speciation of Cu surfaces during the electrochemical CO reduction reaction. J. Am. Chem. Soc. 2020, 142, 97359743,  DOI: 10.1021/jacs.0c02354
    42. 42
      Möller, T. Electrocatalytic CO2 reduction on CuOx nanocubes tracking the evolution of chemical state, geometric structure, and catalytic selectivity using Operando Spectroscopy. Angew. Chem., Int. Ed. 2020,  DOI: 10.1002/anie.202007136
    43. 43
      He, M.; Li, C.; Zhang, H.; Chang, X.; Chen, J. G.; Goddard, W. A., III; Cheng, M.-j.; Xu, B.; Lu, Q. Oxygen induced promotion of electrochemical reduction of CO2 via co-electrolysis. Nat. Commun. 2020, 11, 3844,  DOI: 10.1038/s41467-020-17690-8
    44. 44
      Kim, Y. G.; Soriaga, M. P. Cathodic regeneration of a clean and ordered Cu(100)-(1 × 1) surface from an air-oxidized and disordered electrode: An operando STM study. J. Electroanal. Chem. 2014, 734, 79,  DOI: 10.1016/j.jelechem.2014.09.010
    45. 45
      Scott, S. B. Absence of oxidized phases in Cu under CO reduction conditions. ACS Energy Lett. 2019, 4, 803804,  DOI: 10.1021/acsenergylett.9b00172
    46. 46
      Eilert, A. Subsurface oxygen in oxide-derived copper electrocatalysts for carbon dioxide reduction. J. Phys. Chem. Lett. 2017, 8, 285290,  DOI: 10.1021/acs.jpclett.6b02273
    47. 47
      Schedel-Niedrig, T.; Neisius, T.; Böttger, I.; Kitzelmann, E.; Weinberg, G.; Demuth, D.; Schlögl, R. Copper (sub)oxide formation: a surface sensitive characterization of model catalysts. Phys. Chem. Chem. Phys. 2000, 2, 24072417,  DOI: 10.1039/b000253o
    48. 48
      Liu, C.; Lourenço, M. P.; Hedström, S.; Cavalca, F.; Diaz-Morales, O.; Duarte, H. A.; Nilsson, A.; Pettersson, L. G. Stability and effects of subsurface oxygen in oxide-derived Cu catalyst for CO2 reduction. J. Phys. Chem. C 2017, 121, 2501025017,  DOI: 10.1021/acs.jpcc.7b08269
    49. 49
      Garza, A. J.; Bell, A. T.; Head-Gordon, M. Is subsurface oxygen necessary for the electrochemical reduction of CO2 on copper?. J. Phys. Chem. Lett. 2018, 9, 601606,  DOI: 10.1021/acs.jpclett.7b03180
    50. 50
      Fields, M.; Hong, X.; Nørskov, J. K.; Chan, K. Role of subsurface oxygen on Cu surfaces for CO2 electrochemical reduction. J. Phys. Chem. C 2018, 122, 1620916215,  DOI: 10.1021/acs.jpcc.8b04983
    51. 51
      Bagger, A.; Ju, W.; Varela, A. S.; Strasser, P.; Rossmeisl, J. Electrochemical CO2 reduction: Classifying Cu facets. ACS Catal. 2019, 9, 78947899,  DOI: 10.1021/acscatal.9b01899
    52. 52
      Calle-Vallejo, F.; Tymoczko, J.; Colic, V.; Vu, Q. H.; Pohl, M. D.; Morgenstern, K.; Loffreda, D.; Sautet, P.; Schuhmann, W.; Bandarenka, A. S. Finding optimal surface sites on heterogeneous catalysts by counting nearest neighbors. Science 2015, 350, 185189,  DOI: 10.1126/science.aab3501
    53. 53
      Fung, V.; Tao, F. F.; Jiang, D. E. General structure-reactivity relationship for oxygen on transition-metal oxides. J. Phys. Chem. Lett. 2017, 8, 22062211,  DOI: 10.1021/acs.jpclett.7b00861
    54. 54
      Zhang, Z.; Zandkarimi, B.; Alexandrova, A. N. Ensembles of metastable states govern heterogeneous catalysis on dynamic interfaces. Acc. Chem. Res. 2020, 53, 447458,  DOI: 10.1021/acs.accounts.9b00531
    55. 55
      Dattila, F. Supporting Videos 1–7; https://iochem-bd.iciq.es/browse/handle/100/26145, 2020 (accessed 2020-07-24).
    56. 56
      Yang, F.; Choi, Y.; Liu, P.; Hrbek, J.; Rodriguez, J. A. Autocatalytic reduction of a Cu2O/Cu(111) surface by CO: STM, XPS, and DFT studies. J. Phys. Chem. C 2010, 114, 1704217050,  DOI: 10.1021/jp1029079
    57. 57
      Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 1996, 77, 38653868,  DOI: 10.1103/PhysRevLett.77.3865
    58. 58
      Fishman, M.; Zhuang, H. L.; Mathew, K.; Dirschka, W.; Hennig, R. G. Accuracy of exchange-correlation functionals and effect of solvation on the surface energy of copper. Phys. Rev. B: Condens. Matter Mater. Phys. 2013, 87, 245402,  DOI: 10.1103/PhysRevB.87.245402
    59. 59
      Mathew, K.; Sundararaman, R.; Letchworth-Weaver, K.; Arias, T. A.; Hennig, R. G. Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways. J. Chem. Phys. 2014, 140, 084106,  DOI: 10.1063/1.4865107
    60. 60
      Singh, A. K.; Zhou, L.; Shinde, A.; Suram, S. K.; Montoya, J. H.; Winston, D.; Gregoire, J. M.; Persson, K. A. Electrochemical stability of metastable materials. Chem. Mater. 2017, 29, 1015910167,  DOI: 10.1021/acs.chemmater.7b03980
    61. 61
      Guan, R.; Hashimoto, H.; Kuo, K. H. Electron-microscopic study of the structure of metastable oxides formed in the initial stage of copper oxidation. II. Cu8O. Acta Crystallogr., Sect. B: Struct. Sci. 1984, B40, 560566,  DOI: 10.1107/S010876818400269X
    62. 62
      Bohra, D.; Chaudhry, J. H.; Burdyny, T.; Pidko, E. A.; Smith, W. A. Modeling the electrical double layer to understand the reaction environment in a CO2 electrocatalytic system. Energy Environ. Sci. 2019, 12, 33803389,  DOI: 10.1039/C9EE02485A
    63. 63
      Zhang, F.; Co, A. C. Direct evidence of local pH change and the role of alkali cation during CO2 electroreduction in aqueous media. Angew. Chem., Int. Ed. 2020, 59, 16741681,  DOI: 10.1002/anie.201912637
    64. 64
      Zhang, W.; Huang, C.; Xiao, Q.; Yu, L.; Shuai, L.; An, P.; Zhang, J.; Qiu, M.; Ren, Z.; Yu, Y. Atypical oxygen-bearing copper boosts ethylene selectivity toward electrocatalytic CO2 reduction. J. Am. Chem. Soc. 2020, 142, 1141711427,  DOI: 10.1021/jacs.0c01562
    65. 65
      Bai, H. Controllable CO adsorption determines ethylene and methane productions from CO2 electroreduction. Sci. Bull. 2020,  DOI: 10.1016/j.scib.2020.06.023
    66. 66
      Yu, J.; Namba, Y. Atomic surface roughness. Appl. Phys. Lett. 1998, 73, 36073609,  DOI: 10.1063/1.122839
    67. 67
      Xu, H. Highly selective electrocatalytic CO2 reduction to ethanol by metallic clusters dynamically formed from atomically dispersed copper. Nat. Energy 2020, 5, 623632,  DOI: 10.1038/s41560-020-0666-x
    68. 68
      Jiao, J. Copper atom-pair catalyst anchored on alloy nanowires for selective and efficient electrochemical reduction of CO2. Nat. Chem. 2019, 11, 222228,  DOI: 10.1038/s41557-018-0201-x
    69. 69
      Calle-Vallejo, F.; Koper, M. T. M. Theoretical considerations on the electroreduction of CO to C2 species on Cu(100) electrodes. Angew. Chem., Int. Ed. 2013, 52, 72827285,  DOI: 10.1002/anie.201301470
    70. 70
      Jiang, K.; Sandberg, R. B.; Akey, A. J.; Liu, X.; Bell, D. C.; Nørskov, J. K.; Chan, K.; Wang, H. Metal ion cycling of Cu foil for selective C–C coupling in electrochemical CO2 reduction. Nat. Catal. 2018, 1, 111119,  DOI: 10.1038/s41929-017-0009-x
    71. 71
      Dattila, F. Glyoxylate-like configurations: (Oss)OCCO, sites 1–9.  DOI: 10.19061/iochem-bd-1-165 , 2020 (accessed 2020-07-24).
    72. 72
      Muchowska, K. B.; Varma, S. J.; Moran, J. Synthesis and breakdown of universal metabolic precursors promoted by iron. Nature 2019, 569, 104107,  DOI: 10.1038/s41586-019-1151-1
    73. 73
      Handoko, A. D.; Wei, F.; Jenndy; Yeo, B. S.; Seh, Z. W. Understanding heterogeneous electrocatalytic carbon dioxide reduction through operando techniques. Nat. Catal. 2018, 1, 922934,  DOI: 10.1038/s41929-018-0182-6
    74. 74
      Katayama, Y.; Nattino, F.; Giordano, L.; Hwang, J.; Rao, R. R.; Andreussi, O.; Marzari, N.; Shao-Horn, Y. An in Situ surface-enhanced infrared absorption spectroscopy study of electrochemical CO2 reduction: Selectivity dependence on surface C-bound and O-bound reaction intermediates. J. Phys. Chem. C 2019, 123, 59515963,  DOI: 10.1021/acs.jpcc.8b09598
    75. 75
      Verdaguer-Casadevall, A.; Li, C. W.; Johansson, T. P.; Scott, S. B.; McKeown, J. T.; Kumar, M.; Stephens, I. E.; Kanan, M. W.; Chorkendorff, I. Probing the active surface sites for CO reduction on oxide-derived copper electrocatalysts. J. Am. Chem. Soc. 2015, 137, 98089811,  DOI: 10.1021/jacs.5b06227
    76. 76
      Álvarez-Moreno, M.; de Graaf, C.; López, N.; Maseras, F.; Poblet, J.; Bo, C. Managing the computational chemistry big data problem: The ioChem-BD Platform. J. Chem. Inf. Model. 2015, 55, 95103,  DOI: 10.1021/ci500593j
  • Supporting Information

    Supporting Information

    ARTICLE SECTIONS
    Jump To

    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsenergylett.0c01777.

    • Computational methods, supporting discussion, eqs S1–S24, Figures S1–S27, and Tables S1–S20 (PDF)


    Terms & Conditions

    Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Pair your accounts.

Export articles to Mendeley

Get article recommendations from ACS based on references in your Mendeley library.

Pair your accounts.

Export articles to Mendeley

Get article recommendations from ACS based on references in your Mendeley library.

You’ve supercharged your research process with ACS and Mendeley!

STEP 1:
Click to create an ACS ID

Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

MENDELEY PAIRING EXPIRED
Your Mendeley pairing has expired. Please reconnect