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Article

Electrocatalytic Pathways and Efficiency of Cuprous Oxide (Cu2O) Surfaces in CO2 Electrochemical Reduction (CO2ER) to Methanol: A Computational Approach

by
Zubair Ahmed Laghari
1,
Wan Zaireen Nisa Yahya
1,*,
Sulafa Abdalmageed Saadaldeen Mohammed
2 and
Mohamad Azmi Bustam
1
1
Department of Chemical Engineering, Centre of Research in Ionic Liquids, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak, Malaysia
2
Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark
*
Author to whom correspondence should be addressed.
Catalysts 2025, 15(2), 130; https://doi.org/10.3390/catal15020130
Submission received: 20 December 2024 / Revised: 23 January 2025 / Accepted: 24 January 2025 / Published: 29 January 2025
(This article belongs to the Special Issue Catalysis for CO2 Conversion, 2nd Edition)

Abstract

:
Carbon dioxide (CO2) can be electrochemically, thermally, and photochemically reduced into valuable products such as carbon monoxide (CO), formic acid (HCOOH), methane (CH4), and methanol (CH3OH), contributing to carbon footprint mitigation. Extensive research has focused on catalysts, combining experimental approaches with computational quantum mechanics to elucidate reaction mechanisms. Although computational studies face challenges due to a lack of accurate approximations, they offer valuable insights and assist in selecting suitable catalysts for specific applications. This study investigates the electrocatalytic pathways of CO2 reduction on cuprous oxide (Cu2O) catalysts, utilizing the computational hydrogen electrode (CHE) model based on density functional theory (DFT). The electrocatalytic performance of flat Cu2O (100) and hexagonal Cu2O (111) surfaces was systematically analysed, using the standard hydrogen electrode (SHE) as a reference. Key parameters, including free energy changes (ΔG), adsorption energies (Eads), reaction mechanisms, and pathways for various intermediates were estimated. The results showed that CO2 was reduced to CO(g) on both Cu2O surfaces at low energies. However, methanol (CH3OH) production was observed preferentially on Cu2O (111) at ΔG = −1.61 eV, whereas formic acid (HCOOH) and formaldehyde (HCOH) formation were thermodynamically unfavourable at interfacial sites. The CO2-to-methanol conversion on Cu2O (100) exhibited a total ΔG of −3.38 eV, indicating lower feasibility compared to Cu2O (111) with ΔG = −5.51 eV. These findings, which are entirely based on a computational approach, highlight the superior catalytic efficiency of Cu2O (111) for methanol synthesis. This approach also holds the potential for assessing the catalytic performance of other transition metal oxides (e.g., nickel oxide, cobalt oxide, zinc oxide, and molybdenum oxide) and their modified forms through doping or alloying with various elements.

Graphical Abstract

1. Introduction

Carbon dioxide (CO2) emission is a significant issue contributing to climate change and environmental pollution [1,2]. Consequently, carbon capture, utilization, and storage (CCUS) technologies have been widely developed and employed to reduce CO2 emissions [3,4]. Among CO2 utilization technologies, thermal, photochemical, and electrochemical CO2 reductions are extensively explored for converting CO2 into fuels and value-added chemicals. CO2 electrochemical reduction (CO2ER) presents a potentially sustainable and stable technique. Nonetheless, these approaches are yet to be implemented industrially due to their considerable energy consumption and low product yield.
Turning CO2 via CO2ER into fuels and chemicals highly depends upon the electrolytes and catalysts used [5]. Multiple products can be formed in CO2ER, such as formic acid (HCOOH), carbon monoxide (CO), methane (CH4), ethylene (C2H4), and methanol (CH3OH) [6]. CH3OH conversion on one side is significantly advantageous among these products due to its high market value. However, it also entails a complex reaction pathway in CO2ER requiring six electron–proton transfers, contrary to the formation of other products, that involve only one or two electron transfers, such as HCOOH or CO [7].
CH3OH, which is employed industrially as a solvent, pesticide, and alternative fuel source [8], can also be stored in fuel cells, offering direct and convenient internal combustion systems [9]. The demand for CH3OH has been increasing for various hydrocarbon applications. The total output capacity of CH3OH was recorded at over 138 billion litres from 2015 to 2020 while CH3OH utilization increased from 40% to 60% in emerging energy applications [10]. Approximately 250,000 tons of CH3OH are employed daily as a chemical feedstock or transportation fuel. Producing CH3OH through CO2ER can be cost-effective by improving the current density, reducing the system’s energy consumption using more active catalysts, and increasing the ionic conductivity of the electrolytes. Consequently, enhancing CH3OH production via CO2ER can have multidimensional benefits [11].
In CO2ER, CO2 is reduced through a redox reaction in an electrochemical cell, which yields different products at various potentials, some of the examples are provided in Equations (1)–(5), with their respective standard potentials relative to a standard hydrogen electrode (SHE) [12,13,14,15]. CH3OH has less negative potential as compared to formic acid and carbon monoxide but requires higher electron–proton transfer, making it more challenging to achieve higher efficiency and selectivity.
C O 2 + 2 H + + 2 e H C O O H     ( 0.61   V )
C O 2 + 2 H + + 2 e C O + H 2 O       ( 0.53   V )
C O 2 + 6 H + + 6 e C H 3 O H + H 2 O ( 0.38   V )
C O 2 + 12 H + + 12 e C 2 H 4 + 4 H 2 O ( 0.34   V )
C O 2 + 8 H + + 8 e C H 4 + 2 H 2 O       ( 0.24   V )
CO2 absorption in the electrolyte and adsorption/desorption at the electrode interface also involve complex reactions, thus developing an efficient system for reducing overpotential with a high methanol production rate is challenging [16,17]. Active electrocatalysts and electrolytes are necessary to improve product yield and decrease energy consumption during CO2ER [18,19,20]. Accordingly, miscellaneous catalysts have been assessed for CO2 conversion into different products [21,22]. Studies have found that metal oxides [23], bimetals [24], and alloys [25] are more feasible electrocatalysts than pure metals to produce fuels, hydrocarbons, and alcohol-based products through CO2ER [26].
A multicomponent electrocatalyst consisting of silver/sulphur-cuprous oxide/copper (Ag/S-Cu2O/Cu) demonstrated a CH3OH production at a 67.4% faradic efficiency (FE) with the presence of ionic liquid in the electrolyte [27,28]. In another report, ethanol was successfully produced with a 40.8% FE employing Ag/Cu2O electrocatalyst [29]. On the other hand, gold (Au) nanowires were reported to produce CO at 94% FE [30]. Following CO2 saturation, potassium bicarbonate (KHCO3) recorded excellent FE for alcohol-based products when the Ag/Cu electrodes were prepared through sputtering deposition [31].
Oxides composed of cations and anions have more diverse surface morphologies, compositions, and structures than metals [32]. The atomic arrangement and composition of oxides result in varying activities for different reaction coordinates. Consequently, product desorption primarily depends on the nature of the catalyst surface and its interaction with the electrolytes.
Several computational techniques have been applied to correlate the performance of the electrodes and electrolytes [33,34], effective sorption energies, and the effects of variables on the reaction pathways to understand the CO2ER mechanism on the atomic scale [35,36,37,38]. Producing HCOOH directly from *OCHO hydrogenation on Cu2O (100) surfaces has been documented with excellent accuracy [39]. Furthermore, the ideal CO2 → *COOH → *CO → CO pathway was obtained with Cu (111) and CuO (111), where * represents the adsorption site of the catalyst [40,41].
Chu et al. demonstrated through experimental and density functional theory (DFT) calculations that ethylene (C2H4) was the principal product when antimony (Sb)-modified CuO catalysts were employed [42]. The hydrogenation sequence on copper single-atom alloy for carbon monoxide (CO) production follows CO2 + * → *CO2 → *COOH → *CO + H2O → CO pathway [43]. Meanwhile, CH4 follows the longer pathway CO2 + * → *CO2 → *COOH → *CO + H2O → *HCO → *H2CO → *H3CO → CH4 + *O, where H3CO* can be hydrogenated into CH3OH with additional potential [44].
Electrocatalyst facets possess a considerable influence on electrochemical reduction catalytical activities and stability [45,46]. Consequently, establishing the role of crystal facets is critical during CH3OH activity and selectivity on catalyst surface determinations. Hence, various computational models are used to estimate the effective potentials in the gas–liquid–solid interface. The effective DFT energies, charge densities, and thermal properties, relevant to catalysts are usually determined using constant electrode potential (CEP), Grand Canonical DFT (GC-DFT), and computational hydrogen electrode (CHE) [47]. CEP normally works on the C–C coupling stage consisting of non-redox processes influenced by the applied voltage [48]. A report estimates that the predictions of the CHE model are adequate for studies involving redox reactions, HER, or OER under DFT energies. The CEP model is suitable for studying complex structures that demand the use of external potential, and it focuses on proton-coupled electron transfer (PCET) steps [49]. The CEP model considers the change in the number of electrons in the unit cell and allows fractional value as constant potential. This increases the computational cost and effort because of the need for iterative DFT calculations at each value of the applied bias. To our knowledge, the CEP has not been extensively utilized to model the CO2ER, in contrast to the commonly employed CHE [50]. Additionally, the GC-DFT method is computationally intensive, as it accounts for the potential and surface charges of the entire system, recalculating each potential during simulations with reduced precision for free energy values.
In this study, a computational hydrogen electrode (CHE) model with a semi-hydrogen H2(g) reference electrode and a copper-oxide catalyst (Cu2O) with different facets are employed during the assessments. Several types of energies have been derived through density functional theory (DFT) by solving the gas–liquid–solid interface system according to the electrochemical cell standards. Primarily, product desorption depends upon the nature of the catalyst surface and electrolyte in the system. Nevertheless, other electrolytes can also be introduced with the reference H2(g) molecule layer [51,52].
Catalyst active site selectivity can be significantly improved with computational calculations [53]. This study employed DFT, combining quantum mechanical insights with dynamic molecular simulations to provide a more comprehensive analysis to assess transition states and potential variations during CO2ER in different coordinates. During the reactions, CO2 as the reactant undergoes transition states yielding various products. DFT calculations utilizing the CHE model also enabled evaluations of reaction types, energy states, and density of states in the system [45,54,55].
The direct correlation of DFT energies to the actual potential (voltage) of a system using Cu2O (111) and (100) surfaces is still unknown. These two facets of Cu2O vary in atomic densities and atomic arrangements, which alternatively made a significant impact on selectivity and catalytic activity. Simplifying the engineering of these surfaces, understanding binding energies (how strongly intermediates attach to the surface), and the transition from non-spontaneous to spontaneous reactions for each intermediate is crucial for understanding the stability and selectivity of Cu2O. However, these aspects have not been thoroughly reported in the literature. Additionally, the CO2 adsorption and activation between these two surfaces are different and are not well characterized. To the best of our knowledge, this is the first instance of a detailed discussion employing DFT to examine the influence of geometrical variations on binding and adsorption-desorption phenomena from angles to length variation for each intermediate. Furthermore, understanding the mechanisms at the interface between a solid catalyst and a liquid electrolyte, where the electrolyte helps transport gas molecules to the catalyst, is challenging.
This study aims to predict and understand the electrocatalytic properties of CO2ER to C1 products (notably CH3OH) over Cu2O (100) and Cu2O (111) catalysts using the CHE model by assessing the sequential hydrogenation pathways. The present study determined the changes in the reaction-free energies, adsorption energies, reaction pathways, and shortest sites for CH3OH formation including adsorbate behaviour on these facets in detail. The hydrogen molecule was employed as the reference electrode, which maintained the proton and electron transfer values in the elementary steps and helped standardize the measurements and comparisons. The findings demonstrate that the selectivity and product yield depend on the crystallographic planes and the active sites of the catalyst.

2. Results and Discussion

2.1. Models and Molecular Activation on Cu2O (100) and Cu2O (111) Sites

The varying behaviours of the adsorbates following DFT calculations on cuprous oxide facets Cu2O (100) and Cu2O (111) are illustrated in Figure 1 and Figure 2, respectively. The change in adsorbates’ geometries before and after interaction with the catalyst are given in Table 1. The colours white, red, black, and orange-red were assigned to hydrogen, oxygen, carbon, and copper atoms, respectively, while the dimensions are reported in Angstrom (Å) for length, and degree for angle. The structural diversions of different adsorbates and CO2 on the flat Cu2O (100) and hexagonal Cu2O (111) surfaces were determined, and the change on (100) and (111) surfaces was also discussed.
The standard molecular dimensions were confirmed through different databases, including Materials Project, PubChem, and the Crystallography Open Database (COD) [56,57,58]. Structural deviations indicate the catalytic activities of the catalyst interacting with different absorbates. The Cu-O-Cu in both Cu2O (100) and Cu2O (111) shows a constant angle of 109.5° after geometry optimization; however, Cu2O (100) exhibits higher angle changes as compared to Cu2O (111). Details in dimension changes for facets are given in Table S1 [59,60].
In the case of CO2ER, the higher adsorption of reaction coordinates negatively impacts selectivity and efficiency towards higher electron–proton transfer for selective products, like in the case of CH3OH production [61,62]. The higher adsorption in most of the adsorbates for Cu2O (100) with *CO2, *H3CO, and *CH3OH recorded the highest O-Cu-O angle differences with 177.519°, 173.954°, and 175.326 as shown in Figure 1. This entity possesses the capability to facilitate one or two electron–proton transfers, ultimately resulting in the formation of the carboxyl functional group (COOH) or CO(g) through CO2 + * → *CO2 → *COOH→ *CO + H2O → CO(g) with extra energy to proceed for the reaction. The (100) surface has also less non-stoichiometric O termination, making this surface unstable during CO2ER. The (100) surface, in this case, is reactive and prone to noticeable changes in atomic locations, bond angles, and surface shape, and can be degraded rather than proceeding with an electrochemical reduction reaction. Moreover, minimal changes on the same surface were recorded for *CO, *HCOOH, and *HCOH. The major reason for the unstable (100) surface is its low oxygen coverage with less than 0.5 monolayer (ML), with the top layer being occupied with Cu, which can move down during the reaction, and the O atomic layer taking part to activate the adsorbates for the reaction. As a result of the electronegativity difference, the O attracts the shared electrons more strongly towards H to form a polar covalent bond, compared to the Cu, which has delocalized electrons and needs additional forces to bind with H, namely temperature, pressure, and pH.
However, the Cu2O (111) top surface has an O layer available for H exposure, making Cu atoms more stable on this surface for catalytical activity [61,62,63]. This is also validated by the positive free energy (ΔG) values and non-spontaneous reactions for *CO and *HCOH on Cu2O (111). The higher tendency of O bonding towards Cu from various adsorbates in Cu2O (100) can oxidize the Cu surface, leading to copper hydroxide (Cu(OH)2) and copper carbonate (CuCO3) formation that reduces the lifespan of the catalyst rather than alleviating the CO2ER, which has also been witnessed in multiple research works [64]. Furthermore, the considerable CO-CO interactions induced rearrangements in the Cu2O structure, requiring more energy to further CO conversions into HCOOH and HCOH [65,66].
The pristine, (defect-free) Cu2O (111) surfaces employed in this study showed varying catalytic activities due to the dangling coordinatively unsaturated copper (CuU) atom bonds on the Cu2O (111) surfaces, making them more catalytically active [67]. The non-polar stoichiometric oxygen-terminated surface of Cu2O (111) exhibited more stability as shown in Figure 2a [67,68,69]. The highest structure change in O-Cu-O for Cu2O (111) was seen for *COOH, *HCOOH, and *CH3OH, while the least changes were recorded for *CO2, *HCOO, and *H3CO. The ∠O-Cu-O angle for *CH3OH on Cu2O (100) was recorded at 175.326° and Cu2O (111) exhibited an angle of 169.569°. On the other hand, the Cu-O-Cu change in angle for *CH3OH was 110.725° for Cu2O (100) and 103.228° for Cu2O (111). These variations in Cu2O (111) for CH3OH are due to flexible Cu in the catalyst and strong hydroxyl (-OH) bonding towards Cu atoms from methanol. This change is based on the structure relaxation and rearrangement of Cu and O to minimize overall energy in the final product.
The *CH3OH shows higher adsorption in Cu2O (100) as illustrated in Figure 1i, which entirely changes the structure of CH3OH and makes it difficult to stabilize and detach from the surface. The change in the angle of O-C-H in CH3OH after optimization was measured at 142.048° on Cu2O (100), which is much higher than the (111) surface. Due to the larger angle and structural changes, CH3OH becomes unstable on the Cu2O (100) surface. This instability increases the likelihood that *CH3OH will dissociate into carbon monoxide (CO) gas or methoxy (H3CO) rather than forming CH3OH(l).
The standard angle of O=C=O for CO2 is found to change from 180° to 177.645° at the Cu2O (100) surface and to 179.895° on the Cu2O (111) surface. The Cu2O (100) is more reactive with less coordinated atoms, and additional unsaturated bonds interact with adsorbed CO2 molecules leading to greater distortion in CO2 molecules. It enhances the weakening of the C-O bond and can be slightly better for CO2 activation than the (111) surface, with the latter consuming more energy during initial reduction. Therefore, the reaction from *CO2 to *COOH was also determined to be more promising on the (100) surface following the free energy profile. The H stretching in *HCOO and *COOH towards Cu atoms were noted on (100) and (111) surfaces, respectively, which helps to catalytically decompose *HCOO and *COOH towards CO with the highest angle variation in H-C-O of 67.422° in *HCOO on (100) surface, and C-O-H of 86.745° in *COOH for (111) surface (see Table 1).
The CO(g) was found to be stable on both surfaces with minor changes in length. In the case of *HCOOH, the O forming the bond with the Cu atom was found with the highest change on the (100) surface, increasing the angle from 109.514° to 104.742° for ∠O–C–H. Meanwhile, for the (111) surface, the change was observed from 109.514° to 107.428°. Therefore, the desorption of HCOOH(l) from adsorbed *HCOOH on the (111) surface must be higher. Similarly, the variation in angle for H–C–O for *HCOH and *H3CO computed after adsorption was 96.812° and 123.132° on the Cu2O (100) and (111) surfaces, respectively. This phenomenon involved carbon (C) bonding from *HCOH towards Cu. In bulk, this can lead to the formation of CuCO3 on the surface, producing H2O molecules in the electrolyte as a by-product (see Figure 1).
Similar but less pronounced changes were observed on the Cu2O (111) surface. This suggests that the catalytic conversion of adsorbed molecules occurs more stably without distorting the surface. Therefore, the catalytic activity for converting CO2 to CH3OH is more promising on Cu2O (111) compared to Cu2O (100).

2.2. Adsorption Energies (Eads)

The adsorption energies (Eads) and thermodynamic properties of the different species and catalysts evaluated in the present study were calculated at standard temperature and pressure (298 K and 1 atm) (see Tables S2–S4 in the Supplementary Materials). After geometry optimization, hydrogen gas (H2) exhibited the lowest heat capacity of 6.99 J/K and an enthalpy of 4.57 kcal/mol, indicating that it has the lowest formation enthalpy among the substances studied [70]. On Cu2O (100) and (111), the thermodynamic characteristics of various adsorbates revealed a precisely proportional relationship between molar masses and free energies. The Eads obtained in this study were determined following the equations given in Supporting Information Equations (S1)–(S8). According to the results given in Figure 3, the more negative adsorption energies (Eads) lead to higher exergonic rates (more spontaneous) and require more potential than their positive counterparts, requiring more potential to drive CO2 reduction. Consequently, the adsorption energy is inversely related to the free energy changes during the adsorption and desorption processes.
The compounds with low molecular weight yielded less negative adsorption. The Eads released during *CO2 was less negative (−0.37 eV) than the Eads of *HCOOH (−1.19 eV) on Cu2O (100), which indicates that *CO2→CO2 or CO is more exergonic than *CO2 → HCOOH. The Eads show a good correlation with molecular activation, as discussed in the previous section. The Cu2O (111) also documented similar results, where *CO2 and *HCOOH recorded Eads of −0.46 eV and −1.08 eV, respectively. The Eads for *CH3OH on Cu2O (100) and Cu2O (111) were recorded at −2.8 eV and −2.0 eV, respectively, indicating the bulk adsorption of *CH3OH on Cu2O (100) than Cu2O (111). On the other hand, *CO2 recorded the lowest Eads, considering it is produced in the first elementary step before hydrogenation. The adsorption energies (Eads) of *CO were found to be −0.48 eV for the (100) surface and a much lower value of −0.84 eV for the (111) surface. The adsorption energy value indicates the stability of the adsorbate on the catalyst surface where a more negative value means a stronger bond and more stable adsorption. In this case, CO molecules have a stronger interaction with Cu2O (111) than Cu2O (100). Furthermore, the more negative values of Eads (stronger bond) from CO2 activation to *CH3OH can be explained by the increasing number of H and O atoms available in the molecular structures. A slightly higher difference in adsorption energies between *H3CO and *CH3OH was observed during the interaction of H from *H3CO and C/O from *CH3OH. Moreover, the weak van der Waals forces between hydrogen (H) and copper (Cu) or oxygen (O), combined with the strong chemical bonding of carbon (C) or oxygen (O) to copper, can lead to the formation of CuCO3 or Cu(OH)2. This results in the deactivation of the catalyst surface. Therefore, further investigation of the catalyst surface using bulk electrolysis or long-term chronoamperometric measurements is recommended.

2.3. ΔG Profiles and Reduction Pathways of CO2ER

The ΔG profiles of the CO(g), HCOOH(l), HCOH(l), and CH3OH(l) products derived from DFT calculations on both surfaces are given in Figure 4. Based on the results, CO2 activation energies on Cu2O (100) and (111) were recorded at −0.37 eV and −0.45 eV, respectively. The data also revealed that *CO2 reduction to *HCOO is endergonic (non-spontaneous) on both surfaces compared to *COOH. Conversely, the *CO2 to *COOH reaction is slightly negative and exergonic (spontaneous), with a ΔG of −0.34 eV and −0.20 eV on the Cu2O (100) and (111) surfaces, respectively.
The formation of *HCOOH from *HCOO and *COOH intermediates is exergonic, with a ΔG of −0.82 eV and −0.10 eV for Cu2O (100) and (111), respectively. The results indicate that *COOH production and desorption are constructive in both facets. Nonetheless, HCOOH(l) desorption needs more energy than CO(g) production. The reaction also originated at the negative side of the energy profile, confirming CO(g) as the primary product on both surfaces. Consequently, CO(g) production following the *CO2 → *COOH → *HCOOH → CO(g) pathway is more favourable than the HCOOH(l) pathway, according to the *CO2 → *COOH → *HCOOH → HCOOH(l) reaction pathway.
An experimental report also supported the findings in this study that CO(g) production was more quantitative in primary reactions [71]. It can be proved that the *CO2 → *COOH → *HCOOH reaction is more spontaneous than *CO2 → *HCOO → *HCOOH. The energy differences calculated for HCOH(l) desorption for the two pathways *CO2 → *HCOO → *CO → *HCO → *H2CO → HCOH(l) and *CO2 → *COOH → *HCOOH → *HCO → *H2CO → H2CO(l), were −0.72 eV and −1.77 eV, respectively. Based on the results, the *CO2 → *COOH pathway is more exergonic than *CO2 → *HCOO for HCOH(l) production on Cu2O (100). Similarly, concerning the pathways from *HCOH onwards, the *HCOH → *H3CO → *H3COH → CH3OH(l) reaction is more favourable than the *HCOH → *H2COH → *H3COH → CH3OH(l) counterpart to yield CH3OH(l). The reaction pathways and changes in the reaction ΔG for all elementary steps are listed in Table 2.
It can then be deduced that the surface of the Cu2O (111) shows higher exposure to O atoms than C atoms compared to those of the Cu2O (100) surfaces during its crystallographic oxygen orientation, which enhances the chances of hydrogenation to proceed further and form CH3OH. Consequently, the two surfaces show different energy profiles. At a laboratory scale, the crystallographic planes of Cu2O (100) and (111) can be synthesized via wet chemical reductions, electrodeposition, anodization, and solvothermal synthesis [45], and can be used as electrocatalysts for CO2ER. The products, such as H2CO(l) from *H2CO or *H2COH, and CO(g) from *CO, obtained with Cu2O (100), were slightly more spontaneous than Cu2O (111). Nevertheless, among the CO2 reduction to CH3OH pathways evaluated in this study, the *CO2 → *COOH → *HCOOH → *HCO → *HCOH → *H2COH → *H3COH → CH3OH(l) reaction with Cu2O (111) shows the shortest pathway, as shown in Figure 5. The reaction involving Cu2O (100) required an additional 0.90 eV to produce CH3OH, determined from *H3COH adsorption according to DFT energy calculations and ZPE profiles.
The (100) surfaces exhibited energy profiles closer to positive values, with minor deviations in adsorbates. In contrast, the Cu2O (111) surface remained on the negative side of the energy profile, showing a more significant energy difference from *HCOOH to *HCO compared to the Cu2O (100) facet. This shows that the Cu2O (111) surface has higher catalytic activity and reaction rates. Based on calculations, the total ΔG needed to reduce *CO2 to CH3OH with Cu2O (100) and (111) was approximately −3.14 eV and −5.72 eV, respectively. Negative values of ΔG indicate that the reaction is spontaneous and energetically favourable. Consequently, this makes the Cu2O (111) surface a more viable choice for the electroreduction of CO2 to CH3OH.
Detailed reactions are documented in Supplementary Materials Equations (S9)–(S21), while the direct conversion of adsorbate from its latest reaction coordinates and possible reduction pathways are illustrated in Figure 6. *CO2 is adsorbed on the surface and proceeded towards CH3OH(l) with multiple electron–proton transfer via hydrogenation. The CO(g) in this case can be produced from adsorbed *HCOO or *COOH, which remain adsorbed on the catalyst surface and are then converted into *HCOOH via hydrogenation, where HCOOH(l) is easily produced. The *HCO generated after the removal of the hydroxide anions is converted into H2CO(l) or *HCOH which can then proceed to produce CH3OH and CH4. Understanding the energy pathways for these products can help predict the applied potential needed at the laboratory scale for feasible CO2ER into value-added products. Based on the elementary phases and activation energies, the ΔG for the catalyst Cu2O (100), in descending, order are: *H3CO < *H3COH < *H2C < *COOH < *HCOOH < *HCOH < *CH3OH(l) < *H2COH < *H2CO < *CO < *HCO < *CO2. Meanwhile, the ΔG for the catalyst Cu2O (111) are: *H3CO < *HCOOH < *H2COH< *H3COH < *CO < *HCO < *H2CO < *HCOH < *COOH < *CH3OH(l) < *H2C < *HCOO < *CO2.
The data showed that *H3CO interactions consumed the most energy, while *CO2 interactions required the least energy in both cuprous oxides. The total energy required to reduce *CO2 to *CO through the *COOH pathway is −0.5 eV employing Cu2O (100), while Cu2O (111) recorded a value of 0.4 eV. The results indicated that Cu2O (100) is superior to Cu2O (111) for CO(g) and bicarbonate production. Nonetheless, the oxide is unsuitable for transforming CO(g) to CH3OH(l) due to the higher potential required.
The formation of CH3OH exhibits sluggish reaction rates, as it involves six electron transfers through various intermediates. In contrast, products such as formate or CO require less electron transfer and have higher reaction rates. Additionally, catalysts tend to decline in activity over time, further reducing reaction rates. Our results demonstrate that the extensive pathway for CH3OH formation leads to low reaction rates from *CO2 to CH3OH (Figure 5 and Figure 6).
These reaction pathways suggest that CO2ER to CH3OH needs a longer reaction pathway requiring higher overpotentials than formate or CO. Consequently, based on our findings, the Cu2O (100) surface is not effective for long reactions due to surface reconstruction, unlike the more stable Cu2O (111) (Figure 2a). Nonetheless, doping or complexing Cu2O with single-atom catalysts (SACs) could enhance reaction stability and increase reaction rates for CH3OH formation, as supported by previous reports [72,73,74,75,76].
On the other hand, a straightforward and favourable reaction pathway from CO2 to CH3OH is proposed using Equations (6)–(9). In this pathway, an oxygen atom from either the Cu2O (100) or Cu2O (111) surface adsorbs onto the carbon atom of CO2, forming a carboxyl (COOH) radical. This radical then reacts with hydrogen/protons to produce formic acid (HCOOH). As previously discussed, the carbon atom in formic acid has a higher affinity for the Cu2O (111) surface, especially when an exposed oxygen atom is present. This interaction promotes the formation of methanol (CH3OH).
C O 2 + e C O 2 *
C O 2 * + H + C O O H
C O O H + e + H + H * C O O H
H * C O O H + e + H + C H 3 O H
According to the results presented in this work, CO desorption from *HCOO is achievable by applying extra potential, following the trends of energy activation. This process breaks the C-O bonds, converting *HCOO to CO from metal oxide sites. Alternatively, *COOH will lead to *CO production via O-H removal in the form of water. *OCHO production on metal sites is also possible from oxide formation. Initially, metals are converted to metal oxides, which can directly produce HCOOH(l). Cu2O, being a metal oxide, provides the highest yield of HCOOH(l) [77]. H2CO(l) can be obtained through a four-electron reduction process: *HCOOH → *HCO + H2O → *H2CO → H2CO(l). Similarly, sequential protonation of *HCOOH → *HCO + H2O → *H2CO → *H3CO → *H3COH → CH3OH(l) produces CH3OH(l). However, these pathways depend on the relative hydrogenation stability of the catalyst [78,79].
Several studies have verified the synthesis of the octahedron (111), hexagonal (111), and dodecahedral (110) crystal facets with six, eight, and twelve crystal planes from cubic Cu2O (100) through X-ray diffraction (XRD) analysis [80,81]. Although most reports focused on performance without considering the effects on electronic energies, the free energy values documented in this study are comparable with other reported computational studies as shown in Table 3.
Furthermore, the correlation of the respective energies offers various avenues for material selection. For example, nanosized Cu2O particles were developed and enclosed within cubic Cu2O (100) and Cu2O (111) octahedron structures utilizing the hydrothermal method [86]. The study reported 35.4% as the highest FE, achieved with the octahedron Cu2O (111) structure, while 26.2% FE was achieved by the cubic Cu2O (100) for alcohol base products [86]. In another study, CO2 was reduced to methane with 66.57% FE on the exposed surfaces of Cu nanostructure with predominant (111) orientation [87]. A facet-regulating experiment yielded Cu2O (111) nanocatalysts. The substance was produced via the reductant-controlled method and achieved 74.1% FE for ethylene (C2H4) [88]. Performance comparison of various products between Cu2O (100) and Cu2O (111) from different literatures is presented in Table 4.
Research on the same material found that the tetrahedral Cu2O (111) crystal lattice was favourable for CH3OH selectivity when modified from Cu2O (100). Other studies indicated that the highest CO(g) FE was achieved with cubic Cu2O (100) [91,92], supporting the findings of this study. The literature also noted that CH3OH production with Cu2O (111) was optimal due to its defect-free nature, which offers more adsorption sites and surface oxygen availability. At 140 K, the surfaces could form a mixed layer of methoxy, formaldehyde, and other CH-containing species [93]. The active CH-bond breaking properties of the structure also enable the catalyst to convert CO2 to CH3OH [94]. Conclusively, the surface of Cu2O (111) possesses exceptional structural and electrical characteristics, making it efficient for the selective electrochemical reduction of CO2 to CH3OH [93]. These attributes include the availability of adsorption sites, surface oxygen, and the capacity to stimulate crucial reaction steps. Additionally, doping other elements with different orientations and ratios on copper and copper oxides could lead to varied results [95].

3. Model and Computational Details

The DFT calculations in the current study were performed using the DMol3 in Materials Studio (MS 20.1). The selection of DFT calculations, utilizing a transition from a single crystal to an amorphous system, aligns well with the parameters employed in this study. DFT has been widely reported in numerous research studies for its high quality and accuracy, particularly when analysing different molecules across a broad range of crystal systems [96,97,98]. The evaluations were conducted in a generalized gradient approximation (GGA) as an exchange-correlation function according to the Perdew–Burke–Ernzerh (PBE) scheme. The calculations were performed on (3 × 3 × 3) Cu2O (100) and Cu2O (111) surfaces, a 3.71 Å lattice constant, a 2 × 3 surface slab, and a 20 Å thick vacuum slab perpendicular z-direction to avoid periodic interaction between periodic images.
The vacuum slab was constructed consisting of three atomic layers, where the top layer of Cu2O was kept relaxed during geometry optimization and the bottom two layers were kept fixed. For all intermediate adsorptions, a top hollow site with perpendicular orientation was consistently employed as the model configuration. The intermediates and stable compounds were placed between hollow sites of Cu and O to see the possible interaction of molecules towards catalyst sites. To observe potential interactions between the π-electrons of various adsorbates with the d-orbitals of Cu atoms, and coordination of oxygen lone pairs with Cu sites, a perpendicular orientation was selected. This configuration provides multiple Cu atoms for coordination, promoting the stabilization of intermediates through chemical bonding. Furthermore, the presence of surface oxygen atoms on Cu2O can contribute to hydrogen bonding or polar interactions, potentially facilitating the hydrogenation pathway.
In this study, the spin moment under regular crystals was restricted, while geometry optimization for free molecules was marked as unrestricted. Ideal unit cells were obtained by employing cartesian coordinates. In the present study, all electrons were selected for core treatment. A double numerical plus d-functions (DND) numerical basis set at a 4.4 basis file was employed due to significant atomic mass. The gamma k-point set was used during electronic calculations, which aided orbital determinations. Geometry optimization in this study was performed at the lowest observed binding energy.
According to the CHE model, the standard hydrogen electrode (SHE) is used to measure the redox potential, which is based on reversible hydrogen redox reaction and can be written as Equations (10) and (11) [99].
H 2 2 H + + 2 e
H ( a q ) + + e 1 2 H 2 ( g )
The electrode potential in this relation is computed by subtracting the experimental value of the absolute standard hydrogen electrode potential from the calculated potential of any other reference electrode potential. On the contrary, if the SHE itself is used as a reference electrode, then the potential of this SHE is added to the value of the working electrode and species reacting with that electrode. Hence, following the same calculations, the free energy values for all intermediates determined through DFT were added from the hydrogen energies relevant to the balanced e reactions in this study (given in Supplementary Materials from Equations (S9)–(S21)). The oxidation–reduction in the current study was determined according to Equations (12)–(14):
1 2 O 2 + O *
O * + H + + e H O *
H O * + H + + e H 2 O +
where * denotes the catalyst site.
The same method was used for all adsorbates and intermediates adsorption and activation on Cu2O surfaces having different facets. The SHE was employed to compare catalyst sites and various species participating in CO2 activation to CH3OH desorption post-foundation. For all reaction coordinates, the parameters employed for the calculation were based on H + + e transfer at standard potential (pH 7, 1 bar pressure, and 298 K temperature) as given in Equations (8)–(10). The free energy of hydrogen was first optimized using DFT and used for further calculations, including free energy profiles and adsorption energies (Eads).
Eads were determined following Equation (15). The Gibbs free energy (ΔG) of all elementary steps involved was computed utilizing chemical reactions based on ( H + + e ) transfer on the adsorbed CO2 hydrogenation. A detailed reaction adsorption energy list for all species is presented in Supplementary Information Equations (S1)–(S8) [54]:
E a d s = E s l a b + a d s t o t a l E i s o s l a b   E i s o a d s
where slab represents the unit cells with Cu2O (100) and Cu2O (111) catalysts, iso-slab denotes the isolated slab system, and ads indicates adsorption.

4. Conclusions

In this study, density functional theory (DFT) calculations were employed to predict and understand the electrocatalytic properties of CO2 electroreduction (CO2ER) to C1 products over Cu2O (100) and Cu2O (111) catalysts using the computational hydrogen electrode (CHE) model. The study focused on the performance of CO2ER towards CH3OH production on different facets of Cu2O. The results showed that carbon monoxide (CO) formation was favoured during the initial reduction of CO2 on both crystallographic planes. However, the Cu2O (111) surface, with its protrusions, exhibited higher catalytic activity and selectivity for methanol (CH) compared to Cu2O (100). The production of CH3OH on Cu2O (111) was more exergonic than on Cu2O (100). Both Cu2O (100) and Cu2O (111) surfaces demonstrated similar tendencies to produce CO at low potentials during the decoupling of carbon from adsorbed *CO2. Theoretically, the small Cu2O cubic structure has a higher active surface area for CO selectivity than cupric oxide (CuO) and demonstrated stability in catalysis during CO production. These findings are consistent with data reported in other studies. The study demonstrated that crystallographic orientation affects adsorbates and desorption paths in CO2ER. The analysis of the free energies of adsorption and desorption indicated that the reaction proceeded through CO2 activation, leading to the formation of CH3OH. This computational approach can help screen potential electrocatalysts and understand reaction pathways to achieve desired value-added products like CH3OH. Further experimental validation at the laboratory scale is essential to confirm these findings.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/catal15020130/s1, Table S1: Change in angles in O-Cu-O and Cu-O-Cu in Cu2O (100) and Cu2O (111) after interaction of different adsorbents; Table S2: Eads calculated for Cu2O (100) and Cu2O (111); Equations (S1)–(S8) used to calculate Eads of various adsorbates; Equations (S9)–(S21): All chemical reactions of different species for adsorption; Table S3: The standard thermodynamic quantities of different species, molecules, and catalysts calculated at 298 k for Cu2O (100); Table S4: The standard thermodynamic quantities of different species, molecules, and catalysts calculated at 298 k for Cu2O (111). Ref. [100] is cited in the Supplementary Materials.

Author Contributions

Z.A.L.: Original manuscript write-up, and performed simulations and data analysis. W.Z.N.Y.: conceptualization, supervision, writing, review and editing, formal analysis, proofreading, project administration, and funding acquisition. S.A.S.M.: review and editing, formal analysis, and proofreading. M.A.B.: supervision and resources. All authors have read and agreed to the published version of the manuscript.

Funding

The authors also wish to express their thanks for the financial support provided by the YUTP-FRG (015LC0-455) grant.

Data Availability Statement

The data supporting this article have been included in the Supplementary Materials. The computational data and materials used in this paper are available upon request.

Acknowledgments

The authors would like to express gratitude to the Department of Chemical Engineering and the Centre of Research in Ionic Liquids (CORIL) of Universiti Teknologi PETRONAS for providing technical assistance and research facilities.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The representations following activation and interaction of the Cu2O (100) site with different adsorbates after geometry optimization; (a) original dimension of Cu2O (100) and structures of adsorbates, (b) *CO2, (c) *HCOO, (d) *COOH, (e) *CO, (f) *HCOOH, (g) *HCOH, (h) *H3CO, and (i) *CH3OH.
Figure 1. The representations following activation and interaction of the Cu2O (100) site with different adsorbates after geometry optimization; (a) original dimension of Cu2O (100) and structures of adsorbates, (b) *CO2, (c) *HCOO, (d) *COOH, (e) *CO, (f) *HCOOH, (g) *HCOH, (h) *H3CO, and (i) *CH3OH.
Catalysts 15 00130 g001
Figure 2. The representations following activation and interaction of the Cu2O (111) site with different adsorbates after geometry optimization; (a) Original dimension of Cu2O (111) and structures of adsorbates, (b) *CO2, (c) *HCOO, (d) *COOH, (e) *CO, (f) *HCOOH, (g) *HCOH, (h) *H3CO, and (i) *CH3OH.
Figure 2. The representations following activation and interaction of the Cu2O (111) site with different adsorbates after geometry optimization; (a) Original dimension of Cu2O (111) and structures of adsorbates, (b) *CO2, (c) *HCOO, (d) *COOH, (e) *CO, (f) *HCOOH, (g) *HCOH, (h) *H3CO, and (i) *CH3OH.
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Figure 3. Adsorption energies of different adsorbates on Cu2O (100) and Cu2O (111).
Figure 3. Adsorption energies of different adsorbates on Cu2O (100) and Cu2O (111).
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Figure 4. The free energy (ΔG) diagram for various products over Cu2O (100), and Cu2O (111) surfaces.
Figure 4. The free energy (ΔG) diagram for various products over Cu2O (100), and Cu2O (111) surfaces.
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Figure 5. The two different pathways for CO2ER to CH3OH over the Cu2O (100) and Cu2O (111) surfaces.
Figure 5. The two different pathways for CO2ER to CH3OH over the Cu2O (100) and Cu2O (111) surfaces.
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Figure 6. The suggested CO2 reduction pathways to CO(g), HCOOH(l), H2CO(l), and CH3OH. The red arrows indicate the desorption pathways for different products.
Figure 6. The suggested CO2 reduction pathways to CO(g), HCOOH(l), H2CO(l), and CH3OH. The red arrows indicate the desorption pathways for different products.
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Table 1. Details of CO2 and other adsorbates geometrical variations after interaction on Cu2O (100) and Cu2O (111) surfaces.
Table 1. Details of CO2 and other adsorbates geometrical variations after interaction on Cu2O (100) and Cu2O (111) surfaces.
Compound NameCompound StructureAfter Activation on Cu2O (100)After Activation on Cu2O (111)
Carbon dioxide (CO2)Catalysts 15 00130 i001∠O–Cu–O = 177.645°∠O–Cu–O = 179.895°
Formate (HCOO)Catalysts 15 00130 i0021∠H–C–O = 112.549°
2∠H–C–O = 67.422°
3∠O–C–O = 179.807°
1∠H–C–O = 101.402°
2∠H–C–O = 101.549°
3∠O–C–O = 157.048°
Carboxyl (COOH)Catalysts 15 00130 i0031∠O–C–O = 146.253°
2∠C–O-H = 106.324°
1∠O–C–O = 175.551°
2∠C–O–H = 86.745°
Carbon Monoxide (CO)Catalysts 15 00130 i004C↔ O = 1.140° C↔ O = 1.153°
Formic Acid (HCOOH)Catalysts 15 00130 i0051∠H−O−C = 113.255°
2∠O−C−H = 104.742°
3∠H−C−O = 123.340°
1∠H−O−C = 106.827°
2∠O−C−H = 107.428°
3∠H−C−O = 125.390°
Hydroxymethylene (HCOH)Catalysts 15 00130 i0061∠H−O−C = 113.278°
2∠H−C−O = 96.812°
1∠H−O−C = 107.966°
2∠H−C−O = 101.392°
Methoxy (H3CO)Catalysts 15 00130 i0071∠H−C−O = 108.861°
2∠H−C−O = 119.843°
3∠H−C−O = 123.132°
1∠H−O−C = 108.156°
2∠H−C−O = 110.627°
3∠H−C−O = 113.182°
Methanol (CH3OH)Catalysts 15 00130 i0081∠H−C−H = 107.87°
2∠H−O−C = 108.644°
3∠O−C−H = 142.048°
1∠H−C−H = 106.152°
2∠H−O−C = 103.948°
3∠O−C−H = 106.581°
Table 2. The changes in the reaction ΔG for all elementary steps on Cu2O (100) and Cu2O (111).
Table 2. The changes in the reaction ΔG for all elementary steps on Cu2O (100) and Cu2O (111).
ReactionΔG (eV) for Cu2O (100)ΔG (eV) for Cu2O (111)
* + CO2(g) * C O 2 −0.37−0.11
* C O 2 * H C O O 0.22−0.12
* C O 2 * C O O H 0.300.08
* H C O O * C O + H 2 O −0.100.16
* C O O H * C O + H 2 O −0.430.43
* C O O H * H C O O H 0.270.50
* C O * H C O −0.140.23
* H C O * H C O H 0.140.41
* H C O * H 2 C O 0.0030.29
* H C O * H 2 C O H 0.050.46
* H C O * H 3 C O 0.860.63
* H 2 C O H * H 2 C + H 2 O 0.37−0.05
* H 2 C O H * H 3 C O H 0.600.45
* H 3 C O H C H 3 O H 0.070.08
Table 3. Comparison of free energies calculated for cuprous oxide (Cu2O) using DFT.
Table 3. Comparison of free energies calculated for cuprous oxide (Cu2O) using DFT.
AdsorbateAdsorbentFree Energy (eV)Reference
* C O 2 Cu2O (100)−0.37This work
Cu2O (111)−0.11
*HCOOCu2O (100)0.22This work
Cu2O (111)−0.12
*COOHCu2O (100)0.30This work
Cu2O (111)0.08
*COCu2O (111)−0.10This work
Cu2O (100)0.16
*HCOOHCu2O (111)0.27This work
Cu2O (100)0.50
*CO2Cu2O (111)−0.09[82]
* H C O O −0.14
* C O O H 0.35
* C O −0.50
* H C O O H −0.40
CO2Cu2O (111)0.00[83]
* C O −0.50
* H C O O H −0.01
*CO2Cu2O (111)−0.13[84]
* C O O H −0.12
* C O −0.65
CO2Cu2O0.00[85]
C O O H 0.10
C O −1.00
H C O O H −0.50
Table 4. CO2ER products and performance over cuprous oxide (Cu2O).
Table 4. CO2ER products and performance over cuprous oxide (Cu2O).
MaterialProduct% Faradic EfficiencyReferences
Cu2O (100)CH3OH26.20[86]
Cu2O (111)CH3OH35.7
Cu2O (100)CO20
Cu2O (111)CO40
Cu2O (100)C2H438[45]
Cu2O (111)C2H445
Cu2O (111)CH3OH29.1[89]
Cu2O (100)C2H430.1[90]
Cu2O (111)C2H444.9
Cu2O (111)/Cu2O (100)C2H457.8
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Laghari, Z.A.; Yahya, W.Z.N.; Mohammed, S.A.S.; Bustam, M.A. Electrocatalytic Pathways and Efficiency of Cuprous Oxide (Cu2O) Surfaces in CO2 Electrochemical Reduction (CO2ER) to Methanol: A Computational Approach. Catalysts 2025, 15, 130. https://doi.org/10.3390/catal15020130

AMA Style

Laghari ZA, Yahya WZN, Mohammed SAS, Bustam MA. Electrocatalytic Pathways and Efficiency of Cuprous Oxide (Cu2O) Surfaces in CO2 Electrochemical Reduction (CO2ER) to Methanol: A Computational Approach. Catalysts. 2025; 15(2):130. https://doi.org/10.3390/catal15020130

Chicago/Turabian Style

Laghari, Zubair Ahmed, Wan Zaireen Nisa Yahya, Sulafa Abdalmageed Saadaldeen Mohammed, and Mohamad Azmi Bustam. 2025. "Electrocatalytic Pathways and Efficiency of Cuprous Oxide (Cu2O) Surfaces in CO2 Electrochemical Reduction (CO2ER) to Methanol: A Computational Approach" Catalysts 15, no. 2: 130. https://doi.org/10.3390/catal15020130

APA Style

Laghari, Z. A., Yahya, W. Z. N., Mohammed, S. A. S., & Bustam, M. A. (2025). Electrocatalytic Pathways and Efficiency of Cuprous Oxide (Cu2O) Surfaces in CO2 Electrochemical Reduction (CO2ER) to Methanol: A Computational Approach. Catalysts, 15(2), 130. https://doi.org/10.3390/catal15020130

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