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Article

Tuning the Electronic Properties of CumAgn Bimetallic Clusters for Enhanced CO2 Activation

1
Physics Department, College of Science, Jouf University, Sakakah 11942, Saudi Arabia
2
Department of Physics, College of Science and Humanities, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
3
Department of Physics, University College of Taraba, Taif University, Taraba 21944, Saudi Arabia
4
Department of Physics, Lancaster University, Lancaster LA1 4YB, UK
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2024, 25(22), 12053; https://doi.org/10.3390/ijms252212053
Submission received: 12 October 2024 / Revised: 4 November 2024 / Accepted: 6 November 2024 / Published: 9 November 2024
(This article belongs to the Special Issue Properties and Applications of Nanoparticles and Nanomaterials)

Abstract

:
The urgent demand for efficient CO2 reduction technologies has driven enormous studies into the enhancement of advanced catalysts. Here, we investigate the electronic properties and CO2 adsorption properties of CumAgn bimetallic clusters, particularly Cu4Ag1, Cu1Ag4, Cu3Ag2, and Cu2Ag3, using generalized gradient approximation (GGA)/density functional theory (DFT). Our results show that the atomic arrangement within these clusters drastically affects their stability, charge transfer, and catalytic performance. The Cu4Ag1 bimetallic cluster emerges as the most stable structure, revealing superior charge transfer and effective chemisorption of CO2, which promotes effective activation of the CO2 molecule. In contrast, the Cu1Ag4 bimetallic cluster, in spite of comparable adsorption energy, indicates insignificant charge transfer, resulting in less pronounced CO2 activation. The Cu3Ag2 and Cu2Ag3 bimetallic clusters also display high adsorption energies with remarkable charge transfer mechanisms, emphasizing the crucial role of metal composition in tuning catalytic characteristics. This thorough examination provides constructive insights into the design of bimetallic clusters for boosted CO2 reduction. These findings could pave the way for the development of cost-effective and efficient catalysts for industrial CO2 reduction, contributing to global efforts in carbon management and climate change mitigation.

1. Introduction

Carbon dioxide (CO2) is a primary greenhouse gas responsible for global warming and climate change [1,2,3,4]. Its increasing concentration in the atmosphere, predominantly due to anthropogenic activities such as fossil fuel combustion and deforestation, has created an urgent demand for effective mitigation strategies. One promising strategy to address this issue is the catalytic conversion of CO2 into valuable chemicals, such as ethylene (C2H4), formic acid (CH2O2), and ethanol (C2H6O), among other hydrocarbons [5,6]. This method not only helps decrease CO2 atmospheric levels but also yields products with broad industrial applications [7,8]. Moreover, CO2 conversion can be conducted under ambient conditions with electricity generated from renewable sources such as wind, solar, or hydropower, making it an environmentally friendly solution [7,8].
Over the years, significant research efforts have been dedicated to developing effective catalysts for the electrochemical CO2 reduction reaction (CO2RR) [9,10]. Early studies on CO2RR catalysts mainly focused on noble metal-based catalysts, including platinum (Pt) [11], rhodium (Rh) [12], iridium (Ir) [13], palladium (Pd) [14], and gold (Au) [15]. Although these catalysts demonstrate high efficiency, their limited availability and high cost hinder scalability [11,12,13,14,15]. Consequently, there is an increasing need for earth-abundant metal-based catalysts that can sustainably and effectively transform CO2 [9,10,16].
Among these alternatives, copper (Cu) has gained attention as it facilitates the conversion of CO2 into a wide range of products, including hydrocarbons and alcohols [16,17,18,19]. Research by Dong et al. revealed that Cu79 clusters demonstrate a reduced energy barrier for CO2 reduction to CO, attributable to their high surface-to-volume ratio and coordinatively unsaturated atoms [20]. Similarly, smaller clusters like Cu4 and Cu29 have shown potential for CO2 conversion to methanol (CH3OH) at low activation energies [21,22,23,24]. Despite these advancements, current Cu-based catalysts often require high overpotentials for practical applications, resulting in low selectivity for desired products [25].
To address these challenges, recent studies have explored combining Cu with other metals to enhance CO2RR performance. Bimetallic systems, particularly Cu-Ag combinations, are known for their synergistic interactions, creating new active sites that improve catalytic efficiency [26]. Ag has shown particular promise due to its selectivity in CO2 reduction at moderate overpotentials, effectively suppressing competing hydrogen evolution reactions (HER) [27,28]. Studies have demonstrated that incorporating Ag with Cu not only enhances catalytic efficiency but also provides an economically feasible alternative to noble metals like Au and Pt [29,30]. The significance of Cu-Ag bimetallic clusters is further supported by recent experimental findings. For instance, Huang et al. observed that Cu-Ag nanowire interfaces increase methane production during CO2 reduction, achieving a Faraday efficiency of 72% [31]. This highlights the importance of understanding how varying Cu-Ag ratios affect CO2 adsorption and activation at the atomic level, as it can guide the design of optimized bimetallic catalysts [32,33,34].
Although research on CO2/Cu-Ag bimetallic clusters is inadequate [35,36], there is also a lack of detailed understanding of the atomic-level morphology of Cu-Ag nanoalloys and their interactions with CO2. To the best of our knowledge, the trapezoidal configuration of CumAgn clusters (where m + n = 5) with varying compositions of Ag atoms within the same system and their susceptibility to CO2 adsorption have not been tackled yet. Hence, it is compelling to examine the influence of Ag mixing on the stability and electronic properties of Cu clusters and their interactions with CO2 molecules. Identifying the most stable configuration for bimetallic clusters is a challenging task caused by the intricate nature of their structural complexity. Thus, it is necessary to implement the efficient density functional theory (DFT) method to investigate the potential configurations of clusters/alloys that are close to the ground state.
This study aims to address these gaps by employing DFT calculations to systematically investigate the stability, electronic properties, and CO2 adsorption behaviors of the CumAgn bimetallic cluster. By examining different compositions and configurations, we seek to identify the most stable structures and understand the mechanisms behind their interaction with CO2. The insights gained from this study could guide the design of more efficient and selective bimetallic catalysts, contributing to the development of sustainable CO2 reduction technologies and offering potential pathways for the development of scalable catalytic solutions.
To provide a comprehensive overview of the objectives of the study and methodological approach, Figure 1 presents a visual summary that clarifies the key stages of our research. This study begins with the identification of the optimal compositions of CumAgn bimetallic clusters, specifically targeting electronic properties favorable for CO2 activation. The flowchart outlines the step-by-step computational methodology employed, including the use of density functional theory (DFT) for structural and electronic analysis. By focusing on specific clusters, such as Cu4Ag1, the study aims to quantify charge transfer and adsorption energies, ultimately pinpointing the cluster composition that maximizes CO2 adsorption efficiency. These findings are particularly relevant for advancing catalytic applications in industrial CO2 reduction, providing a basis for future experimental studies.

2. Results and Discussion

2.1. Cu4Ag1 and Cu1Ag4 Bimetallic Clusters

Figure 2a,b depict five optimized Cu4Ag1 trapezoidal bimetallic clusters and five optimized Cu1Ag4 trapezoidal bimetallic clusters using GGA/PBE. For both cases, the ground states of these clusters are two-dimensional trapezoidal configurations, consistent with previous studies [37]. For Cu4Ag1 clusters, the most stable bimetallic cluster is observed when the Ag atom is positioned at the bottom corners of the cluster (structures 1 and 5 in Figure 2a). This result implies that the bottom corner sites promote a more favorable electronic environment for the Ag atom, possibly owing to enhanced bonding interactions with the neighboring Cu atoms. The metastable state takes place when the Ag atom is located at the top corners of the cluster (structures 2 and 3 in Figure 2a), with an energy difference of approximately 0.07 eV compared to the most stable cluster. This metastable state indicates that the top corner positions are less favorable but still within a relatively low energy range, signifying potential flexibility in the structural variation of the clusters. The least stable structure is recognized when the Ag atom occupies the center of the cluster (structures 4 in Figure 2a), revealing an energy difference of 0.23 eV. Figure 2a also confirms that changing a Cu atom with an Ag atom at various sites within the cluster induces different degrees of deformation. This deformation is ascribed to changes in bond length, aligning with prior research [38]. Moreover, the calculated average bond length of Cu-Cu is 2.38 Å and of Cu-Ag is 2.51 Å, which is close to the bulk value of 2.53 Å [39].
For Cu1Ag4 clusters, the most favorable configuration for the bimetallic cluster is achieved when the Cu atom is situated at the center of the cluster, as observed in structure 1 of Figure 2b. This stability is consistent with previous studies [37,40,41]. The observed stability implies that the central sites provide a more favorable electrical environment for the Cu atom, possibly due to increased bonding interactions with the surrounding Ag atoms. A metastable condition occurs when the Cu atom is positioned at the upper corners of the cluster (structures 4 and 5 in Figure 2b), with an energy difference of about 0.07 eV compared to the most stable cluster. This indicates that although the top corner positions are not immensely favorable, they nevertheless fall within a low energy range, demonstrating a certain level of structural adaptability. The most unstable cluster is noted when the Cu atom is positioned in the cluster’s bottom corners (structures 2 and 3 in Figure 2b), inducing an energy difference of 0.21 eV. Moreover, Figure 2b reveals that replacing an Ag atom with a Cu atom at different sites of the cluster leads to different levels of distortion. The distortions observed are attributed to variations in the length of chemical bonds. In addition, the average bond lengths computed for Ag-Ag and Cu-Ag are 2.66 Å and 2.55 Å, respectively.
To clarify the charge transfer mechanism and electronic properties of the lowest-energy configuration of Cu4Ag1 and Cu1Ag4 clusters (see structures 1 in Figure 2a,b), we applied the Bader charge analysis technique, calculated the pDOS, and presented the CDD, as illustrated in Figure 3. Bader charge calculations demonstrate that for Cu4Ag1 cluster, the Ag atom gains ~0.18 e from the Cu atoms, while for Cu1Ag4 cluster, the Ag atoms gains ~0.22 e from the Cu atom, a phenomenon clearly proven in the CDD plot. The driving force behind this charge transfer is the difference in Pauling electronegativity between Ag (1.93) and Cu (1.90) [39]. Though the variation in electronegativity is relatively small, it is sufficient to induce an obvious electron transfer, revealing the sensitivity of these clusters to subtle electronic changes. The pDOS calculations further complement these analyses by illustrating the electronic states contributing to the bonding and stability of the cluster. For the Cu4Ag1 cluster, it is evidently observed that the states range between −3.3 eV and −0.8 eV and are dominated mainly by the d orbitals of Cu atoms, with the insignificant contribution of the d orbitals of the Ag atom at around −2.7 eV. The contribution of d orbitals of the Ag atom is more pronounced in the energy range between −4.8 eV and −3.35 eV, with a minor hybridization of the d orbitals of Cu atoms at nearly −3.9 eV.
For the Cu1Ag4 cluster, it is evident that the states within the energy range of −2 eV to −1.3 eV are mainly dominated by the d orbitals of Cu atoms, with a slight contribution from the d orbitals of the Ag atom at around −1.6 eV. In the energy range of −5.2 eV to −2.5 eV, the d orbitals of the Ag atom are more explicit, displaying minor hybridization with the d and s orbitals of the Cu atom near −3.8 eV and −2.7 eV, respectively. The incorporation of Cu into the Ag cluster leads to an improved occupation of the s orbitals of the Ag atoms, as clearly apparent by the overlapped state at −1 eV in Figure 2b. This occurrence likely implies that Cu doping facilitates the d-electrons transfer to the Ag atoms within the Cu1Ag4 cluster. This electron transfer was also found in the Ag12Cu cluster [42].
For both clusters, doping an Ag atom in the Cu cluster and vice versa modifies the electronic structure, as evidenced by the changes in the DOS near the Fermi level (see Figure 3b). In particular, there is obvious hybridization between the d orbitals and sp orbitals near the Fermi level in the Cu atom and the p orbitals in the Ag atoms (see Figure 3a). Similarly, the Ag atoms display boosted overlap of their s orbitals with the sp hybridized orbitals of the Cu atom near the Fermi level (see Figure 3b). This leads to electron transfer from the Cu atom to the Ag atoms in both Cu4Ag1 and Cu1Ag4 clusters, resulting in a substantial splitting between the spin-up and spin-down DOS, which is consistent with previous reports [43]. This hybridization can improve the catalytic properties of the clusters by creating active sites with altered electronic environments, which are necessary for facilitating various chemical reactions.

2.2. Cu3Ag2 and Cu2Ag3 Bimetallic Clusters

Figure 4a,b illustrate ten optimized trapezoidal bimetallic clusters of Cu3Ag2 and Cu2Ag3, respectively, utilizing GGA/PBE methodology. In both systems, the clusters’ ground states reveal two-dimensional trapezoidal structures, corroborating the results of earlier research [37,40]. For Cu3Ag2 clusters, the most stable cluster is achieved when two Ag atoms are located at the bottom corners of the cluster (structures 1 in Figure 4a). This stability possibly arises from the bottom corner sites providing a more favorable electronic environment for the Ag atoms, potentially due to improved bonding interactions with the neighboring Cu atoms. A metastable state is noted for structures 3, 4, 5, 9, and 10 (see Figure 4a), with an energy difference of around 0.14 eV compared to the most stable cluster. The least stable structure arises for structures 2, 6, 7, and 8 (see Figure 4a), with an energy difference of 0.27 eV. Figure 4a further demonstrates that substituting of tow Cu atoms with Ag atoms at different sites within the cluster results in varying degrees of deformation, ascribed to alterations in bond lengths. Moreover, the calculated average bond lengths of the most stable cluster are 2.40 Å for Cu-Cu and 2.52 Å for Cu-Ag.
For Cu2Ag3 clusters, the most favorable arrangement is obtained when two Cu atoms are positioned within the center and top corners of the cluster, as depicted in structures 1 and 2 of Figure 4b. The observed stability implies that these sites offer a more favorable electronic environment for the Cu atom, likely due to enhanced bonding interactions with the surrounding Ag atoms. A metastable state is found for structures 4, 5, 6, 7, 8, 9, and 10 (see Figure 4b), with an energy difference of nearly 0.18 eV compared to the most stable cluster. This signifies that, while the bottom corner positions are less favorable, they remain within a low energy range, showing some degree of structural adaptability. The least stable cluster is observed when the Cu atoms are located at the bottom corners of the cluster (structure 3 in Figure 4b), resulting in an energy difference of about 0.32 eV. Moreover, Figure 4b shows that replacing Ag atoms with Cu atoms at various sites of the cluster induces different levels of distortion. These distortions are caused by changes in bond lengths. Furthermore, the computed average bond lengths for the lowest energy state are 2.62 Å, 2.42 Å, and 2.53 Å for Ag-Ag, Cu-Cu, and Cu-Ag, respectively.
To describe the charge transfer mechanism and the electronic properties of the lowest-energy structures of Cu3Ag2 and Cu2Ag3 clusters (see structures 1 in Figure 4a,b) we employed Bader charge analysis, calculated the pDOS, and illustrated the CDD, as presented in Figure 5. The Bader charge calculations indicate that in the Cu3Ag2 cluster, the Ag atoms gain approximately 0.30 e from the Cu atoms, whereas in the Cu2Ag3 cluster, the Ag atoms gain about 0.41 e from the Cu atoms. This phenomenon is clearly observed in the charge density difference plots seen in Figure 5a,b. The pDOS calculations offer further insights by identifying the electronic states that contribute to the bonding and stability of the clusters. In the Cu3Ag2 cluster, the energy range from −2.7 eV to −0.7 eV is predominantly influenced by the d orbitals of Cu atoms, with a modest contribution from the d states of the Ag atom around −2.1 eV. The Ag atom’s d orbitals are particularly prominent in the energy range from −4.8 eV to −3.1 eV, with a slight hybridization of the Cu atoms’ d orbitals.
In terms of the Cu3Ag2 cluster, the energy range from −2.5 eV to −0.8 eV is mainly dominated by the d orbitals of Cu atoms, with a small contribution from the d states of the Ag atom around −2.0 eV. The d states of the Ag atom become more prominent in the energy range from −5.0 eV to −2.5 eV, indicating modest hybridization with the d and s orbitals of the Cu atom around −4.0 eV and −2.7 eV, respectively. The incorporation of Cu into the Ag cluster results in a greater filling of the s orbitals of Ag atoms, as evidenced by the overlapping state at −1.1 eV in Figure 5b. This suggests that the addition of Cu facilitates the transfer of d-electrons to the Ag atoms in the Cu2Ag3 cluster. The electronic structure of both clusters is influenced by the doping of Ag and Cu atoms in the Cu cluster and vice versa. This effect is evident from the variations in the DOS near the Fermi level. Specifically, there is clear hybridization between the d states and sp levels near the Fermi level within the Cu atom, as well as the p orbitals within the Ag atoms (see Figure 5a). Similarly, the Ag atoms, which have neighboring atoms, demonstrate pronounced overlap of their s orbitals with the sp hybridized orbitals of the Cu atom around the Fermi level (see Figure 5b). This interaction causes the transfer of charge from the Cu atom to the Ag atoms in both Cu4Ag1 and Cu1Ag4 clusters, resulting in a significant separation between the spin-up and spin-down DOS. This observation is consistent with previous studies [43]. The hybridization can enhance the catalytic properties of the clusters by producing active sites with modified electronic environments, which are essential for facilitating several chemical reactions.

2.3. Adsorption of CO2 on Cu4Ag1 and Cu1Ag4 Clusters

Bimetallic clusters have gathered substantial interest due to their remarkable catalytic activity and reduced susceptibility to CO2 poisoning [44]. The primary aim of this research is to understand the reactivity of CO2 gas molecules on CumAgn bimetallic clusters. Therefore, we explore the influence of compositional changes on the reactivity of CO2 molecules across bimetallic clusters of CumAgn. Before adsorbing the CO2 molecule onto the CumAgn bimetallic clusters, we optimized the isolated CO2 molecule using GGA/DFT (see Figure A1 in Appendix A). The calculated bond length (dC=O = 1.172 Å for CO2) and bond angle (θOCO = 179.96° for CO2) are in agreement with the findings of previous studies [45,46]. The initial phase of the catalytic conversion of CO2 involves the adsorption mechanism, where the molecule can either undergo physisorption or chemisorption onto the catalyst [26,45,47]. In the chemisorbed state, CO2 displays elongated C-O bonds and a decreased O-C-O bond angle, shifting from a linear to a bent configuration. This transformation implies that CO2 activation occurs due to electron transfer from the metal catalyst to the CO2 molecule’s π molecular orbitals [7,48]. Conversely, in the physisorbed state, CO2 retains its gas-phase characteristics, with an O-C-O bond angle of 180° and a C-O bond length of 1.18 Å. To provide a more systematic investigation, we carried out additional calculations on the Ag5 and Cu5 mono-clusters interacting with CO2, as shown in Figure A2. The relative energies of optimized Cu5@CO2 structures (Figure A2b) illustrate that structure 1 is the most stable, with an adsorption energy (0.70 eV) comparable to that of the Cu4Ag1@CO2 cluster. In contrast, the Ag5@CO2 configurations (Figure A2a) display a slightly different stability trend, with Structure 1 also being the most favorable but exhibiting different adsorption characteristics compared to Cu5@CO2. The pDOS and CDD plots for Ag5@CO2 and Cu5@CO2 are presented in Figure A2c,d, respectively. The pDOS for Ag5@CO2 signifies a less pronounced interaction between the Ag d-orbitals and CO2 at lower energy states (~−4.5 eV), while the Cu5@CO2 cluster reveals remarkable hybridization between the Cu d-orbitals and the CO2 orbitals in the range between −1 and −5 eV. This difference in electronic structure agrees with the CDD plots, where Cu5@CO2 exhibits more charge density transfer to the CO2 molecule than Ag5@CO2, similar to the trend observed in Cu4Ag1@CO2. Comparing these results with the Cu4Ag1@CO2 cluster, we observe that Cu5@CO2 possesses a higher charge transfer capacity, which could suggest enhanced CO2 activation. However, the mixed composition in Cu4Ag1@CO2 favors both stability and effective electron transfer, giving an ideal balance for CO2 activation. This systematic comparison emphasizes the role of Cu and Ag content in impacting the adsorption behavior and electronic attribution, aiding to enhance the design principles for efficient CO2 reduction catalysts.
Considering the most stable configuration of the Cu4Ag1 bimetallic cluster, i.e., structure 1 in Figure 2a, we placed the CO2 molecule at different sites of the cluster as displayed in Figure 6a, and we found that structure 1 is the most stable configuration compared to the metastable state, specifically, structure 2, with an energy difference of roughly 0.5 eV. In structure 1, the CO2 is highly adsorbed on the bimetallic cluster with an adsorption energy of 0.95 eV, implying a chemisorption process. Our result showed that the systems responsible for CO2 activation consistently illustrate effective adsorption and significant charge transfer of around 0.6 e¯ from the Cu4Ag1 to the CO2 molecule. This process leads to the transformation of the CO2 molecule from a linear to a bent structure (θOCO = 135.5° for CO2), along with an elongation of the C-O bonds (dO-C-O = 1.29, 1.24 Å), which is in good agreement with a previously published study on bimetallic CuNi nanoparticles [45]. The CO2 molecule favorably binds to the top sites of the Cu4Ag1 bimetallic cluster, forming bonds with two Cu atoms (dO-Cu = 1.95 Å and dC-Cu = 1.96 Å). The adsorption of CO2 on Cu4Ag1 bimetallic clusters results in modifications in the geometric structures of the clusters, with an observed Cu−Cu average bond length of approximately 2.41 Å. The outcomes indicate that bonding the CO2 to two Cu atoms in Cu4Ag1 bimetallic clusters can enhance their surface activity.
Figure 6b shows the adsorption of CO2 on bimetallic Cu1Ag4 clusters. In this case, the CO2 molecule exhibits a preference for the “top” site, yet no bonds form between CO2 and silver atoms. Considering the most stable configuration of the Cu1Ag4 bimetallic cluster as depicted in structure 1 in Figure 2b, we positioned the CO2 molecule at various sites on the cluster, as demonstrated in Figure 6b. Our estimates revealed that structure 1 remains the most stable structure, in contrast to the metastable state, structure 2, with an energy difference of nearly 0.13 eV. In structure 1, although the CO2 molecule exhibits high adsorption on the bimetallic cluster with an adsorption energy of 0.87 eV, the bond angles (θOCO = 179.67° for CO2) and bond lengths of CO2 (dO=C=O = 1.18, 1.19 Å) closely resemble those found in isolated CO2. This could be explained by slight charge transfer to the CO2 molecule, which is nearly 0.03 e¯. The calculated average bond length of Ag-Ag was observed to be approximately 2.63 Å, which is in good agreement with the study of Ag5@CO2 [49]. It can be concluded that although the adsorption energies of CO2 are comparable for both systems, the degree of electron transfer to CO2 varies substantially, which distinguishes the process of CO2 activation. Further comparison of both systems’ geometric structural parameters is illustrated in Table 1.
To elucidate the factors affecting the chemisorption of CO2 on the Cu4Ag1 bimetallic cluster, we performed calculations to determine the pDOS as demonstrated in Figure 7a. As illustrated in Figure 7a and supported by reference [50], Cu4Ag1@CO2 exhibits delocalized orbitals around the Fermi level, which is clearly evident by the hybridization of sp orbitals of Cu and O. This overlap can facilitate substantial electron transfer from these clusters to CO2, which in turn stabilizes the chemisorbed state. In contrast, the overlap orbitals of Cu1Ag4 with O (p) orbitals of the CO2 molecule are characterized by considerably lower energy levels from the Fermi level, which can be observed at −4.7 eV in Figure 7b. Furthermore, our investigation into the electron excitation of Cu4Ag1 clusters shows that the energy level of the lowest unoccupied molecular orbital (LUMO) in CO2 closely matches the excitation energies of p electrons in Cu4Ag1 clusters (see states at 3.2 eV in Figure 7a). This alignment enables the transfer of excited hot electrons from the LUMO of Cu4Ag1 clusters to the LUMO of CO2 owing to the strong coupling between their orbitals. The resultant electron-transfer state possesses a chemisorption state, which drastically reduces the energy barriers for breaking the C-O bond and forming CO [51]. While in the Cu1Ag4 system, we observed no hybridized LUMO states of the CO2 molecule with the Cu1Ag4 cluster, implying a stable state of the CO2 molecule. In addition, the excess charge observed near the O atom signifies its predominant role in the adsorption of the CO2 molecule rather than the C atom [46]. Charge density maps, as shown in Figure 7a, corroborate our results regarding the electron transfer from the clusters to the CO2 molecule.

2.4. Adsorption of CO2 on Cu3Ag2 and Cu2Ag3 Clusters

Upon analyzing the most stable configuration of the Cu3Ag2 bimetallic cluster, structure 1 in Figure 4a, we explored the positioning of the CO2 molecule at various sites on the cluster, as shown in Figure 8a. Our calculation indicates that structure 1 represents the most stable cluster, with an energy difference of about 0.40 eV compared to the less stable structure 5. Structure 1 shows strong CO2 adsorption on the bimetallic cluster, with an adsorption energy of 0.81 eV, indicative of a chemisorption mechanism. Our results further demonstrate that systems involved in CO2 activation typically reveal strong adsorption and moderate electron transfer, approximately 0.14 e, from the Cu3Ag2 bimetallic cluster to the CO2 molecule. This interaction induces a transformation in the CO2 molecule from a linear to a bent geometry (θOCO = 137.65° for CO2) and elongates the C-O bonds (dO=C=O = 1.27, 1.26 Å). The CO2 molecule selectively binds to the sites on the Cu4Ag1 bimetallic cluster with the highest adsorption, forming chemical bonds with two Cu atoms (dO-Cu = 2.10 Å and dC-Cu = 2.07 Å). The adsorption of CO2 on the Cu3Ag2 cluster results in geometric alterations, with an average bond length of approximately 2.44 Å between Cu atoms. These results imply that the surface activity of Cu3Ag2 bimetallic clusters can be enhanced by the bonding of CO2 to two Cu atoms.
Figure 8b shows the adsorption process of CO2 on bimetallic Cu2Ag3 clusters. In this scenario, after examining the most stable arrangement of the Cu2Ag3 bimetallic cluster, which is referred to as structure 1 in Figure 4b, we considered the placement of the CO2 molecule at several locations on the cluster, as shown in Figure 8b. The result indicates that structure 1 is the most stable configuration, showing an energy difference of roughly 0.13 eV when compared to the less stable structure 4. Structure 1 exhibits a high adsorption for CO2, as evidenced by its strong adsorption with an energy of 0.81 eV, implying a chemisorption process. Our result also reveals that systems responsible for CO2 activation generally demonstrate substantial adsorption and a high level of electron transfer, around 0.53 e, from the Cu2Ag3 bimetallic cluster to the CO2 molecule. This interaction causes the CO2 molecule to transition from a straight shape to a curved one (θOCO = 140.36° for CO2) and lengthens the C-O bonds (dO=C=O = 1.24, 1.26 Å). The CO2 molecule exhibits a strong preference for binding to the top site on the Cu2Ag3 bimetallic cluster, making chemical bonds with one Cu atom and one Ag atom (with bond distances of dO-Cu = 2.10 Å, dO-Ag = 2.45 Å, and dC-Cu = 2.03 Å). The results indicate that the surface reactivity of Cu2Ag3 bimetallic clusters can be improved through the bonding of CO2 to the top site of the cluster. Table 2 presents a detailed comparison of the geometric structural parameters of both systems.
To elucidate the factors influencing the chemisorption of CO2 on the Cu3Ag2 bimetallic cluster, we performed calculations to determine pDOS, as shown in Figure 9a. Figure 9a indicates that Cu3Ag2@CO2 exhibits delocalized states near the Fermi level, evidenced by the hybridization of Ag (s), Cu (d), and O (p), and C (p) orbitals. This overlapping orbital facilitates charge transfer from the cluster to CO2, thereby stabilizing the chemisorbed state. Similarly, the orbitals of the Cu2Ag3 cluster overlap with the CO2 orbitals, namely Cu (p), Cu (d), O (p), and C (p), as observed at Fermi energy in Figure 9b. This hybridization allows charge transfer from the cluster to CO2. Additionally, our analysis of electron excitation in Cu3Ag2 clusters shows that the energy level of the LUMO in CO2 closely matches the excitation energies of p electrons in Cu3Ag2 clusters (see states at 3.2 eV in Figure 9a). The alignment between the LUMO of Cu4Ag1 clusters and the LUMO of CO2 facilitates effective transmission of excited hot electrons due to strong orbital coupling. This charge-transfer state adopts a chemisorption structure, effectively lowering the energy barriers for C-O bond dissociation and CO formation. Similarly, in the Cu1Ag4 system, the energy level of the LUMO in CO2 aligns closely with the excitation energies of the p electrons of Cu and s electrons of Ag, particularly at the states around 3.5 eV, as illustrated in Figure 9b. This alignment between the LUMO of Cu4Ag1 clusters and the LUMO of CO2 enables the efficient transfer of excited hot electrons, supported by a strong orbital interaction. Furthermore, the presence of excess charge near the O atom suggests its predominant role in CO2 adsorption, as opposed to the C atom. The CDD maps presented in Figure 9a,b corroborate our results regarding electron transfer from the clusters to the CO2 molecule.

3. Computational Methodology

The calculations for trapezoidal CumAgn bimetallic clusters were conducted using the Kohn–Sham (KS) [52] spin-polarized DFT method, facilitated by the Quantum ESPRESSO software program v6.7 [53]. The exchange-correlation energies were assessed with the Perdew–Burke–Ernzerhof (PBE) functional [54], an implementation of the generalized gradient approximation (GGA) [55]. Electron-ion interactions were modeled with a projected augmented-wave (PAW) pseudopotential type [56]. A kinetic energy cut-off of 40 Ry was set to the plane-wave basis wave function, and a cut-off of 225 Ry was utilized for the charge density. To enhance convergence for bimetallic clusters, Gaussian smearing was utilized for the electronic levels. The optimization of all structures was carried out with a force convergence criterion set to 10−3 eV/Å, allowing all atoms to relax. During the process of geometric relaxation, a convergence threshold value of 10−6 Ry was used to achieve the electronic self-consistency. To prevent interactions between periodic images, the CumAgn bimetallic clusters were placed in a large supercell measuring approximately 17 Å × 14 Å × 10 Å for optimization. In the relaxation step, all calculations were performed at the Γ-point within the Brillouin zone. Then single-point calculations were performed, where a K-point grid of 2 × 2 × 2 was used to improve the accuracy of the electronic properties results. Furthermore, the Bader charge technique was utilized to investigate electron transfer [57]. The Visualization for Electronic and Structural Analysis (VESTA) software [58] was utilized to analyze CDD figures and to visualize all models presented in this study. We calculated the adsorption energy ( E a d s ) of CO2 using the following equation.
E a d s = E t o t E c l u s t e r E C O 2
where E t o t is the system’s total energy, E c l u s t e r is the bimetallic cluster’s total energy, and E C O 2 is the isolated CO2 molecule’s total energy. The charge density difference was calculated using the following equation.
Δ ρ = ρ A B C ρ A ρ B
where ρ A B C is the charge density of the whole system and ρ A and ρ B are the charge density of system A and system B in the system, respectively.

4. Conclusions

This study presents a comprehensive analysis of the structural and electronic properties of the CunAgm bimetallic clusters, which offers valuable insights into the design of stable and efficient catalytic materials for CO2 conversion into useful products. Through a systematic investigation of CumAgn clusters (Cu4Ag1, Cu1Ag4, Cu3Ag2, and Cu2Ag3), we observed significant variations in electronic properties, stability, and CO2 interaction, influenced strongly by the specific arrangement of Cu and Ag atoms. The Cu4Ag1 cluster, featuring Ag at the bottom corners, demonstrated the highest stability due to enhanced bonding interactions, whereas the Cu1Ag4 configuration showed notable stability with Cu centered, facilitating efficient electron transfer from Cu to Ag, thereby enhancing catalytic potential.
In terms of CO2 adsorption, the Cu4Ag1 cluster exhibited the highest chemisorption energy and significant electron transfer to the CO2 molecule, leading to effective activation of CO2 for catalytic reactions. Although the Cu1Ag4 cluster displayed strong adsorption energy, it showed limited electron transfer, suggesting a less efficient activation process. Both Cu3Ag2 and Cu2Ag3 clusters also demonstrated strong adsorption energies and electron transfer capabilities, though with distinct structural distortions and bonding behaviors that underscore the impact of atomic composition and configuration on catalytic efficiency. Overall, this comparative analysis emphasizes the crucial role of atomic configuration in optimizing the catalytic properties of CumAgn bimetallic clusters for CO2 reduction. These findings underscore the potential for designing bimetallic clusters with targeted compositions and structures to enhance their catalytic performance in industrial CO2 reduction applications, advancing sustainable approaches for addressing critical environmental challenges.

Author Contributions

M.A. (Moteb Alotaibi) originally conceived the concept; the calculations were carried out by M.A. (Moteb Alotaibi), T.A., F.A., N.A., M.A. (Majd Alsunaid), L.A. and T.F.Q. All authors provided essential contributions to interpreting the data reported in this manuscript. M.A. and A.K.I. coordinated the writing of the manuscript with input from T.A. All authors have read and agreed to the published version of the manuscript.

Funding

This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2024/R/1445).

Data Availability Statement

Data are contained within the article.

Acknowledgments

Moteb Alotaibi and Talal F. Qahtan are grateful to the Deanship of Scientific Research at Prince Sattam bin Abdulaziz University, Alkharj, Saudi Arabia. Turki Alotaibi is grateful to Jouf University, Saudi Arabia. Fatimah Alhwaiti is grateful to the University College of Taraba, Taif University. Ali Ismael is grateful for financial assistance from Lancaster University, UK. Moteb Alotaibi thanks KAUST For computer time, this research used Shaheen III managed by the Supercomputing Core Laboratory at King Abdullah University of Science & Technology (KAUST) in Thuwal, Saudi Arabia.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

This section contains calculations on the isolated CO2 molecule, such as the optimized structure, net charge, charge density difference, and partial density of states.
Figure A1. (a) Optimized structure of the isolated CO2 molecule. (b) Charge density difference of CO2. (c) Partial density of states of CO2. Note: blue numbers represent the amount of electrons on each atom.
Figure A1. (a) Optimized structure of the isolated CO2 molecule. (b) Charge density difference of CO2. (c) Partial density of states of CO2. Note: blue numbers represent the amount of electrons on each atom.
Ijms 25 12053 g0a1
Figure A2. (a) Relative energies of optimized Ag5@CO2 bimetallic clusters by varying sites of Ag atom. (b) Relative energies of optimized Cu5@CO2 bimetallic clusters by varying sites of Cu atom. (c) pDOS and CDD of the Ag5@CO2 bimetallic cluster. (d) pDOS and CDD of the Cu5@CO2 bimetallic cluster. Blue and gray balls denote copper and silver atoms, respectively.
Figure A2. (a) Relative energies of optimized Ag5@CO2 bimetallic clusters by varying sites of Ag atom. (b) Relative energies of optimized Cu5@CO2 bimetallic clusters by varying sites of Cu atom. (c) pDOS and CDD of the Ag5@CO2 bimetallic cluster. (d) pDOS and CDD of the Cu5@CO2 bimetallic cluster. Blue and gray balls denote copper and silver atoms, respectively.
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References

  1. Duan, Y.; Meng, F.; Liu, K.; Yi, S.; Li, S.; Yan, J.; Jiang, Q. Amorphizing of Cu Nanoparticles toward Highly Efficient and Robust Electrocatalyst for CO2 Reduction to Liquid Fuels with High Faradaic Efficiencies. Adv. Mater. 2018, 30, e1706194. [Google Scholar] [CrossRef] [PubMed]
  2. Lei, F.; Liu, W.; Sun, Y.; Xu, J.; Liu, K.; Liang, L.; Yao, T.; Pan, B.; Wei, S.; Xie, Y. Metallic tin quantum sheets confined in graphene toward high-efficiency carbon dioxide electroreduction. Nat. Commun. 2016, 7, 12697. [Google Scholar] [CrossRef] [PubMed]
  3. Rabiee, A.; Nematollahi, D. Electrochemical reduction of CO2 to formate ion using nanocubic mesoporous In(OH)3/carbon black system. Mater. Chem. Phys. 2017, 193, 109–116. [Google Scholar] [CrossRef]
  4. Wang, P.; Qiao, M.; Shao, Q.; Pi, Y.; Zhu, X.; Li, Y.; Huang, X. Phase and structure engineering of copper tin heterostructures for efficient electrochemical carbon dioxide reduction. Nat. Commun. 2018, 9, 4933. [Google Scholar] [CrossRef] [PubMed]
  5. Houghton, J. Global warming. Rep. Prog. Phys. 2005, 68, 1343–1403. [Google Scholar] [CrossRef]
  6. Zhang, W.; Hu, Y.; Ma, L.; Zhu, G.; Wang, Y.; Xue, X.; Chen, R.; Yang, S.; Jin, Z. Progress and Perspective of Electrocatalytic CO2 Reduction for Renewable Carbonaceous Fuels and Chemicals. Adv. Sci. 2017, 5, 1700275. [Google Scholar] [CrossRef]
  7. Xing, M.; Guo, L.; Hao, Z. Theoretical insight into the electrocatalytic reduction of CO2 with different metal ratios and reaction mechanisms on palladium–copper alloys. Dalton Trans. 2018, 48, 1504–1515. [Google Scholar] [CrossRef]
  8. Zhu, D.D.; Liu, J.L.; Qiao, S.Z. Recent Advances in Inorganic Heterogeneous Electrocatalysts for Reduction of Carbon Dioxide. Adv. Mater. 2016, 28, 3423–3452. [Google Scholar] [CrossRef]
  9. Costentin, C.; Robert, M.; Savéant, J.-M. Catalysis of the electrochemical reduction of carbon dioxide. Chem. Soc. Rev. 2012, 42, 2423–2436. [Google Scholar] [CrossRef]
  10. He, Z.; Qian, Q.; Ma, J.; Meng, Q.; Zhou, H.; Song, J.; Liu, Z.; Han, B. Water-Enhanced Synthesis of Higher Alcohols from CO2 Hydrogenation over a Pt/Co3O4 Catalyst under Milder Conditions. Angew. Chem. 2015, 128, 747–751. [Google Scholar] [CrossRef]
  11. Zhang, X.; Li, X.; Zhang, D.; Su, N.Q.; Yang, W.; Everitt, H.O.; Liu, J. Product selectivity in plasmonic photocatalysis for carbon dioxide hydrogenation. Nat. Commun. 2017, 8, 14542. [Google Scholar] [CrossRef] [PubMed]
  12. Park, S.; Bézier, D.; Brookhart, M. An Efficient Iridium Catalyst for Reduction of Carbon Dioxide to Methane with Trialkylsilanes. J. Am. Chem. Soc. 2012, 134, 11404–11407. [Google Scholar] [CrossRef] [PubMed]
  13. Gao, D.; Zhou, H.; Cai, F.; Wang, J.-G.; Wang, G.; Bao, X. Pd-Containing Nanostructures for Electrochemical CO2 Reduction Reaction. ACS Catal. 2018, 8, 1510–1519. [Google Scholar] [CrossRef]
  14. Klinkova, A.; De Luna, P.; Dinh, C.-T.; Voznyy, O.; Larin, E.M.; Kumacheva, E.; Sargent, E.H. Rational Design of Efficient Palladium Catalysts for Electroreduction of Carbon Dioxide to Formate. ACS Catal. 2016, 6, 8115–8120. [Google Scholar] [CrossRef]
  15. Zhu, W.; Michalsky, R.; Metin, Ö.; Lv, H.; Guo, S.; Wright, C.J.; Sun, X.; Peterson, A.A.; Sun, S. Monodisperse Au Nanoparticles for Selective Electrocatalytic Reduction of CO2 to CO. J. Am. Chem. Soc. 2013, 135, 16833–16836. [Google Scholar] [CrossRef]
  16. Knurr, B.J.; Weber, J.M. Solvent-Mediated Reduction of Carbon Dioxide in Anionic Complexes with Silver Atoms. J. Phys. Chem. A 2013, 117, 10764–10771. [Google Scholar] [CrossRef]
  17. Knurr, B.J.; Weber, J.M. Structural Diversity of Copper–CO2 Complexes: Infrared Spectra and Structures of [Cu(CO2)n] Clusters. J. Phys. Chem. A 2014, 118, 10246–10251. [Google Scholar] [CrossRef]
  18. Knurr, B.J.; Weber, J.M. Solvent-Driven Reductive Activation of Carbon Dioxide by Gold Anions. J. Am. Chem. Soc. 2012, 134, 18804–18808. [Google Scholar] [CrossRef]
  19. Xie, H.; Wang, T.; Liang, J.; Li, Q.; Sun, S. Cu-based nanocatalysts for electrochemical reduction of CO2. Nano Today 2018, 21, 41–54. [Google Scholar] [CrossRef]
  20. Dong, H.; Li, Y.; Jiang, D.-E. First-Principles Insight into Electrocatalytic Reduction of CO2 to CH4 on a Copper Nanoparticle. J. Phys. Chem. C 2018, 122, 11392–11398. [Google Scholar] [CrossRef]
  21. Shen, H.M.; Li, Y.W.; Sun, Q. Cu atomic chains supported on β-borophene sheets for effective CO2; electroreduction. Nanoscale 2018, 10, 11064–11071. [Google Scholar] [CrossRef] [PubMed]
  22. Liu, C.; Yang, B.; Tyo, E.; Seifert, S.; DeBartolo, J.; von Issendorff, B.; Zapol, P.; Vajda, S.; Curtiss, L.A. Carbon Dioxide Conversion to Methanol over Size-Selected Cu4 Clusters at Low Pressures. J. Am. Chem. Soc. 2015, 137, 8676–8679. [Google Scholar] [CrossRef] [PubMed]
  23. Yang, Y.; Evans, J.; Rodriguez, J.A.; White, M.G.; Liu, P. Fundamental studies of methanol synthesis from CO2 hydrogenation on Cu(111), Cu clusters, and Cu/ZnO( 000 1 - ). Phys. Chem. Chem. Phys. 2010, 12, 9909–9917. [Google Scholar] [CrossRef] [PubMed]
  24. Du, D.; Zhu, H.; Guo, Y.; Hong, X.; Zhang, Q.; Suo, B.; Zou, W.; Li, Y. Anchoring Cu Clusters over Defective Graphene for Electrocatalytic Reduction of CO2. J. Phys. Chem. C 2022, 126, 11611–11618. [Google Scholar] [CrossRef]
  25. Saputro, A.G.; Agusta, M.K.; Wungu, T.D.K.; Suprijadi; Rusydi, F.; Dipojono, H.K. DFT study of adsorption of CO2on palladium cluster doped by transition metal. J. Physics: Conf. Ser. 2016, 739, 012083. [Google Scholar] [CrossRef]
  26. Wang, H.; Zhou, X.; Yu, T.; Lu, X.; Qian, L.; Liu, P.; Lei, P. Surface restructuring in AgCu single-atom alloy catalyst and self-enhanced selectivity toward CO2 reduction. Electrochim. Acta 2022, 426, 140774. [Google Scholar] [CrossRef]
  27. Zhang, M.; Zhang, Z.; Zhao, Z.; Huang, H.; Anjum, D.H.; Wang, D.; He, J.-H.; Huang, K.-W. Tunable Selectivity for Electrochemical CO2 Reduction by Bimetallic Cu–Sn Catalysts: Elucidating the Roles of Cu and Sn. ACS Catal. 2021, 11, 11103–11108. [Google Scholar] [CrossRef]
  28. Smith, J.H.C. Molecular equivalence of carbohydrates to carbon dioxide in photosynthesis. Plant Physiol. 1943, 18, 207–223. [Google Scholar] [CrossRef]
  29. Hong, Z.; Wang, C.; Zhang, X.; Wang, X.; Zhang, Y. Research Progress of Copper-Based Bimetallic Electrocatalytic Reduction of CO2. Catalysts 2023, 13, 376. [Google Scholar] [CrossRef]
  30. Skúlason, E.; Tripkovic, V.; Björketun, M.E.; Gudmundsdóttir, S.; Karlberg, G.; Rossmeisl, J.; Bligaard, T.; Jónsson, H.; Nørskov, J.K. Modeling the Electrochemical Hydrogen Oxidation and Evolution Reactions on the Basis of Density Functional Theory Calculations. J. Phys. Chem. C 2010, 114, 110913. [Google Scholar] [CrossRef]
  31. Nørskov, J.K.; Bligaard, T.; Logadottir, A.; Kitchin, J.R.; Chen, J.G.; Pandelov, S.; Stimming, U. Trends in the Exchange Current for Hydrogen Evolution. J. Electrochem. Soc. 2005, 152, J23. [Google Scholar] [CrossRef]
  32. Huang, J.; Mensi, M.; Oveisi, E.; Mantella, V.; Buonsanti, R. Structural Sensitivities in Bimetallic Catalysts for Electrochemical CO2 Reduction Revealed by Ag–Cu Nanodimers. J. Am. Chem. Soc. 2019, 141, 2490–2499. [Google Scholar] [CrossRef] [PubMed]
  33. Choi, C.; Cai, J.; Lee, C.; Lee, H.M.; Xu, M.; Huang, Y. Intimate atomic Cu-Ag interfaces for high CO2RR selectivity towards CH4 at low over potential. Nano Res. 2021, 14, 3497–3501. [Google Scholar] [CrossRef]
  34. Jeon, Y.E.; Ko, Y.N.; Kim, J.; Choi, H.; Lee, W.; Kim, Y.E.; Lee, D.; Kim, H.Y.; Park, K.T. Selective production of ethylene from CO2; over CuAg tandem electrocatalysts. J. Ind. Eng. Chem. 2022, 116, 191–198. [Google Scholar] [CrossRef]
  35. Kostecki, R.; Augustynski, J. Photon-driven reduction reactions on silver. J. Appl. Electrochem. 1993, 23, 567–572. [Google Scholar] [CrossRef]
  36. Ni, Z.; Liang, H.; Yi, Z.; Guo, R.; Liu, C.; Liu, Y.; Sun, H.; Liu, X. Research progress of electrochemical CO2 reduction for copper-based catalysts to multicarbon products. Coord. Chem. Rev. 2021, 441, 213983. [Google Scholar] [CrossRef]
  37. Wei-Yin, L.; Sha, Z.; Lian, H. Structural, optical, electronic, and magnetic properties of Ag-Cu bimetallic clusters: A density functional theory study. J. Nanoparticle Res. 2018, 20, 188. [Google Scholar] [CrossRef]
  38. Ferrando, R.; Fortunelli, A.; Johnston, R.L. Searching for the optimum structures of alloy nanoclusters. Phys. Chem. Chem. Phys. 2007, 10, 640–649. [Google Scholar] [CrossRef]
  39. Li, W.; Chen, F. A density functional theory study of structural, electronic, optical and magnetic properties of small Ag–Cu nanoalloys. J. Nanoparticle Res. 2013, 15, 1809. [Google Scholar] [CrossRef]
  40. Kilimis, D.A.; Papageorgiou, D.G. Structural and electronic properties of small bimetallic Ag–Cu clusters. Eur. Phys. J. D 2009, 56, 189–197. [Google Scholar] [CrossRef]
  41. Ding, L.-P.; Kuang, X.-Y.; Shao, P.; Zhao, Y.-R.; Li, Y.-F. A comparative study on geometries, stabilities, and electronic properties between bimetallic AgnX(X= Au, Cu; n=1−8) and pure silver clusters. Chin. Phys. B 2012, 21, 043601. [Google Scholar] [CrossRef]
  42. Ma, W.; Chen, F. Optical and electronic properties of Cu doped Ag clusters. J. Alloy. Compd. 2012, 541, 79–83. [Google Scholar] [CrossRef]
  43. Rao, Y.; Lei, Y.; Cui, X.; Liu, Z.; Chen, F. Optical and magnetic properties of Cu-doped 13-atom Ag nanoclusters. J. Alloy. Compd. 2013, 565, 50–55. [Google Scholar] [CrossRef]
  44. Lei, X.L.; Wu, M.S.; Liu, G.; Xu, B.; Ouyang, C.Y. The Role of Cu in Degrading Adsorption of CO on the PtnCu Clusters. J. Phys. Chem. A 2013, 117, 8293–8297. [Google Scholar] [CrossRef] [PubMed]
  45. Austin, N.; Butina, B.; Mpourmpakis, G. CO2 activation on bimetallic CuNi nanoparticles. Prog. Nat. Sci. 2016, 26, 487–492. [Google Scholar] [CrossRef]
  46. Baraiya, B.A.; Mankad, V.; Jha, P.K. Uncovering the structural, electronic and vibrational properties of atomically precise PdmCun clusters and their interaction with CO2 molecule. Spectrochim. Acta Part A: Mol. Biomol. Spectrosc. 2019, 229, 117912. [Google Scholar] [CrossRef]
  47. Nabi, A.G.; Hussain, A.; Di Tommaso, D. Ab initio random structure searching and catalytic properties of copper-based nanocluster with Earth-abundant metals for the electrocatalytic CO2-to-CO conversion. Mol. Catal. 2022, 527, 112406. [Google Scholar] [CrossRef]
  48. Vogt, C.; Monai, M.; Sterk, E.B.; Palle, J.; Melcherts, A.E.M.; Zijlstra, B.; Groeneveld, E.; Berben, P.H.; Boereboom, J.M.; Hensen, E.J.M.; et al. Understanding carbon dioxide activation and carbon–carbon coupling over nickel. Nat. Commun. 2019, 10, 5330. [Google Scholar] [CrossRef]
  49. Alotaibi, M.; Alotaibi, T.; Alshammari, M.; Ismael, A.K. The Structural and Electronic Properties of the Ag5 Atomic Quantum Cluster Interacting with CO2, CH4, and H2O Molecules. Crystals 2023, 13, 1691. [Google Scholar] [CrossRef]
  50. Yang, Z.; Fu, Z.; Zhang, Y.; Wu, R. Direct CO Oxidation by Lattice Oxygen on Zr-Doped Ceria Surfaces. Catal. Lett. 2010, 141, 78–82. [Google Scholar] [CrossRef]
  51. Zhang, X.-G.; Liu, Y.; Zhan, C.; Jin, X.; Chi, Q.; Wu, D.-Y.; Zhao, Y.; Tian, Z.-Q. Reaction Selectivity for Plasmon-Driven Carbon Dioxide Reduction on Silver Clusters: A Theoretical Prediction. J. Phys. Chem. C 2019, 123, 11101–11108. [Google Scholar] [CrossRef]
  52. Chu, C.-H.; Leung, C.-W. The convolution equation of Choquet and Deny on [IN]-groups. Integral Equ. Oper. Theory 2001, 40, 391–402. [Google Scholar] [CrossRef]
  53. Giannozzi, P.; Baroni, S.; Bonini, N.; Calandra, M.; Car, R.; Cavazzoni, C.; Ceresoli, D.; Chiarotti, G.L.; Cococcioni, M.; Dabo, I.; et al. QUANTUM ESPRESSO: A modular and open-source software project for quantum simulations of materials. J. Phys. Condens. Matter 2009, 21, 395502. [Google Scholar] [CrossRef] [PubMed]
  54. Perdew, J.P.; Burke, K.; Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 1996, 77, 3865–3868. [Google Scholar] [CrossRef]
  55. Blöchl, P.E. Projector augmented-wave method. Phys. Rev. B 1994, 50, 17953–17979. [Google Scholar] [CrossRef]
  56. Kresse, G.; Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 1999, 59, 1758–1775. [Google Scholar] [CrossRef]
  57. Henkelman, G.; Arnaldsson, A.; Jónsson, H. A fast and robust algorithm for Bader decomposition of charge density. Comput. Mater. Sci. 2005, 36, 354–360. [Google Scholar] [CrossRef]
  58. Momma, K.; Izumi, F. VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data. J. Appl. Crystallogr. 2011, 44, 1272–1276. [Google Scholar] [CrossRef]
Figure 1. Flowchart of study objectives, DFT-based methodology, and key findings, emphasizing the efficiency of the Cu4Ag1 cluster in CO2 reduction.
Figure 1. Flowchart of study objectives, DFT-based methodology, and key findings, emphasizing the efficiency of the Cu4Ag1 cluster in CO2 reduction.
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Figure 2. (a) Relative energies of optimized Cu4Ag1 bimetallic clusters by varying sites of Ag atom. (b) Relative energies of optimized Cu1Ag4 bimetallic clusters by varying sites of Cu atom. Blue and gray balls denote copper and silver atoms, respectively.
Figure 2. (a) Relative energies of optimized Cu4Ag1 bimetallic clusters by varying sites of Ag atom. (b) Relative energies of optimized Cu1Ag4 bimetallic clusters by varying sites of Cu atom. Blue and gray balls denote copper and silver atoms, respectively.
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Figure 3. (a) pDOS and CDD of Cu4Ag1 bimetallic cluster. (b) pDOS and CDD of Cu1Ag4 bimetallic cluster. The vertical line shows the Fermi level, and blue and yellow clouds indicate the negative and positive potentials.
Figure 3. (a) pDOS and CDD of Cu4Ag1 bimetallic cluster. (b) pDOS and CDD of Cu1Ag4 bimetallic cluster. The vertical line shows the Fermi level, and blue and yellow clouds indicate the negative and positive potentials.
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Figure 4. (a) Relative energies of optimized Cu3Ag2 bimetallic clusters by varying sites of the Ag atom. (b) Relative energies of the optimized Cu2Ag3 bimetallic clusters by varying sites of the Cu atom.
Figure 4. (a) Relative energies of optimized Cu3Ag2 bimetallic clusters by varying sites of the Ag atom. (b) Relative energies of the optimized Cu2Ag3 bimetallic clusters by varying sites of the Cu atom.
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Figure 5. (a) pDOS and CDD of the Cu3Ag2 bimetallic cluster. (b) pDOS and CDD of the Cu2Ag3 bimetallic cluster. The vertical line shows the Fermi level, and blue and yellow clouds indicate the negative and positive potentials.
Figure 5. (a) pDOS and CDD of the Cu3Ag2 bimetallic cluster. (b) pDOS and CDD of the Cu2Ag3 bimetallic cluster. The vertical line shows the Fermi level, and blue and yellow clouds indicate the negative and positive potentials.
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Figure 6. (a) Relative energies of optimized Cu4Ag1@CO2 bimetallic clusters by varying sites of CO2 molecules. (b) Relative energies of optimized Cu1Ag4@CO2 bimetallic clusters by varying sites of CO2 molecules. Blue, gray, red, and brown balls denote copper, silver, oxygen, and carbon atoms, respectively.
Figure 6. (a) Relative energies of optimized Cu4Ag1@CO2 bimetallic clusters by varying sites of CO2 molecules. (b) Relative energies of optimized Cu1Ag4@CO2 bimetallic clusters by varying sites of CO2 molecules. Blue, gray, red, and brown balls denote copper, silver, oxygen, and carbon atoms, respectively.
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Figure 7. (a) pDOS and CDD of the Cu4Ag1@CO2 bimetallic cluster. (b) pDOS and CDD of the Cu1Ag4@CO2 bimetallic cluster.
Figure 7. (a) pDOS and CDD of the Cu4Ag1@CO2 bimetallic cluster. (b) pDOS and CDD of the Cu1Ag4@CO2 bimetallic cluster.
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Figure 8. (a) Relative energies of optimized Cu3Ag2@CO2 bimetallic clusters by varying sites of CO2 molecules. (b) Relative energies of optimized Cu2Ag3@CO2 bimetallic clusters by varying sites of CO2 molecules.
Figure 8. (a) Relative energies of optimized Cu3Ag2@CO2 bimetallic clusters by varying sites of CO2 molecules. (b) Relative energies of optimized Cu2Ag3@CO2 bimetallic clusters by varying sites of CO2 molecules.
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Figure 9. (a) pDOS and CDD of the Cu3Ag2@CO2 bimetallic cluster. (b) pDOS and CDD of the Cu2Ag3@CO2 bimetallic cluster.
Figure 9. (a) pDOS and CDD of the Cu3Ag2@CO2 bimetallic cluster. (b) pDOS and CDD of the Cu2Ag3@CO2 bimetallic cluster.
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Table 1. Adsorption energy (Eads) of CO2, bond length (dO=C=O) of C-O, and bond angle (θOCO) of the CO2 molecule. For reference, the calculated bond lengths and angles of the isolated CO2 molecule are 1.172 Å and 179.96 o, respectively.
Table 1. Adsorption energy (Eads) of CO2, bond length (dO=C=O) of C-O, and bond angle (θOCO) of the CO2 molecule. For reference, the calculated bond lengths and angles of the isolated CO2 molecule are 1.172 Å and 179.96 o, respectively.
SystemEads (eV)dO=C=O (Å)θOCO(o)
Cu4Ag1
Structure 10.951.29, 1.24135.50
Structure 20.541.28, 1.24136.59
Structure 30.271.27, 1.22139.65
Cu1Ag4
Structure 10.871.18, 1.19179.67
Structure 20.401.19, 1.19179.65
Structure 30.811.19, 1.19179.71
Structure 40.401.19, 1.19179.50
Table 2. Adsorption energy (Eads) of CO2, bond length (dO=C=O) of C-O, and bond angle (θOCO) of CO2 molecule.
Table 2. Adsorption energy (Eads) of CO2, bond length (dO=C=O) of C-O, and bond angle (θOCO) of CO2 molecule.
SystemEads (eV)dO=C=O (Å)θOCO(o)
Cu3-Ag2
Structure 10.811.27, 1.26137.65
Structure 20.131.18, 1.19179.74
Structure 30.131.19, 1.19179.68
Structure 40.271.19, 1.19179.39
Structure 50.401.19, 1.18179.89
Cu2-Ag3
Structure 10.811.24, 1.26140.36
Structure 20.541.19. 1.19179.65
Structure 30.541.19, 1.18179.79
Structure 40.681.19, 1.18179.78
Structure 50.271.18, 1.19179.06
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Alotaibi, T.; Alotaibi, M.; Alhawiti, F.; Aldosari, N.; Alsunaid, M.; Aldawas, L.; Qahtan, T.F.; Ismael, A.K. Tuning the Electronic Properties of CumAgn Bimetallic Clusters for Enhanced CO2 Activation. Int. J. Mol. Sci. 2024, 25, 12053. https://doi.org/10.3390/ijms252212053

AMA Style

Alotaibi T, Alotaibi M, Alhawiti F, Aldosari N, Alsunaid M, Aldawas L, Qahtan TF, Ismael AK. Tuning the Electronic Properties of CumAgn Bimetallic Clusters for Enhanced CO2 Activation. International Journal of Molecular Sciences. 2024; 25(22):12053. https://doi.org/10.3390/ijms252212053

Chicago/Turabian Style

Alotaibi, Turki, Moteb Alotaibi, Fatimah Alhawiti, Nawir Aldosari, Majd Alsunaid, Lama Aldawas, Talal F. Qahtan, and Ali K. Ismael. 2024. "Tuning the Electronic Properties of CumAgn Bimetallic Clusters for Enhanced CO2 Activation" International Journal of Molecular Sciences 25, no. 22: 12053. https://doi.org/10.3390/ijms252212053

APA Style

Alotaibi, T., Alotaibi, M., Alhawiti, F., Aldosari, N., Alsunaid, M., Aldawas, L., Qahtan, T. F., & Ismael, A. K. (2024). Tuning the Electronic Properties of CumAgn Bimetallic Clusters for Enhanced CO2 Activation. International Journal of Molecular Sciences, 25(22), 12053. https://doi.org/10.3390/ijms252212053

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