Direct Evidence of Reversible Changes in Electrolyte and its Interplay with LiO2 Intermediate in Li-O2 Batteries.

Lithium-oxygen batteries show promising energy storage potential with high theoretical energy density; however, further investigation of chemical reactions is required. In this study, experimental Raman and theoretical analyzes are performed for a Li-O2 battery with LiClO4/dimethyl sulfoxide (DMSO) electrolyte and carbon cathode to understand the role of intermediate species in the reactional mechanism of the cell using a high donor number solvent. Operando Raman results reveal reversible changes in the DMSO bands, in addition to the formation and decomposition of Li2O2. On discharge, a decrease in DMSO polarizability is observed and bands of DMSO-Li+-anion interactions are evidenced and supported by ab initio density functional theory (DFT) calculations. Molecular dynamics (MD) force field simulations and operando Raman show that DMSO interacts with LiO2(sol), highlighting the stability of the electrolyte compared to the interaction with reactive O 2 - ${\rm O}_2^{-}$ . On charging, the presence of Li+ indicates the formation of a lithium-deficient phase, followed by the release of Li+ and oxygen. Therefore, this study contributes to understanding the discharge/charge chemistry of a Li-O2 cell, employing a common carbon cathode and DMSO electrolyte. The combination of a simple characterization technique in operando mode and theoretical studies provides essential information on the mechanism of Li-O2 system.

Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights.

Chiral organic-inorganic perovskites exhibit unique physicochemical properties driven by the symmetry of monovalent organic cations. However, an atomistic understanding of how chiral cations transfer their chirality to the inorganic framework and the role played by van der Waals (vdW) interactions in this process is still incomplete. In this work, we report a theoretical investigation, based on density functional theory calculations within the Perdew-Burke-Ernzerhof (PBE) formulation for the exchange-correlation functional, into the role of the vdW interactions in the chirality transfer process. For that, we selected several vdW corrections, namely, Grimme (D2, D3, D3(BJ)), Tkatchenko-Scheffler (TS, TS+SCS, TS+HSI), density-dependent energy correction (dDsC), and many-body scattering (MBD) energy method correction. For the chiral perovskite systems, we selected a set of chiral organic-inorganic perovskites with several dimensions, namely, from zero-dimensional to three-dimensional, each having enantiomers with R and S configurations. Based on a statistical treatment of the relative errors of all lattice parameters with respect to experimental data, we found that D3, D3(BJ), TS, TS+SCS, TS+HSI, and MBD vdW are the most accurate corrections to describe the equilibrium structural properties of chiral perovskites using the PBE method. We identify chirality-induced sequential asymmetries of distorted octahedrons and propose angular descriptors to quantify them, where the orientations of these distortions depend on the R or S nature of the chiral cations. Furthermore, we demonstrate the importance of accurate vdW interactions in precisely describing these asymmetric distortions. By means of binding energies and charge-transfer analysis, we show that the impact of vdW corrections on the charge distribution leads to a subtle strengthening of hydrogen bonds between chiral cations and inorganic octahedra, resulting in an increase in the binding energy. Finally, we identified that the Rashba-Dresselhaus effect in two-dimensionality is refined by vdW interactions.

The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling.

There has been a growing recognition of the need for diversity and inclusion in scientific fields. This trend is reflected in the Journal of Chemical Information and Modeling (JCIM), where there has been a gradual increase in the number of papers that embrace this diversity. In this viewpoint, we analyze the evolution of the profile of papers published in JCIM from 1996 to 2022 addressing three diversity criteria, namely interdisciplinarity, geographic and gender distributions, and their impact on citation patterns. We used natural language processing tools for the classification of main areas and gender, as well as metadata, to analyze a total of 7384 articles published in the categories of research articles, reviews, and brief reports. Our analyses reveal that the relative number of articles and citation patterns are similar across the main areas within the scope of JCIM, and international collaboration and publications encompassing two to three research areas attract more citations. The percentage of female authors has increased from 1996 (less than 20%) to 2022 (more than 32%), indicating a positive trend toward gender diversity in almost all geographic regions, although the percentage of publications by single female authors remains lower than 20%. Most JCIM citations come from Europe and the Americas, with a tendency for JCIM papers to cite articles from the same continent. Furthermore, there is a correlation between the gender of the authors, as JCIM manuscripts authored by females are more likely to be cited by other JCIM manuscripts authored by females.

Theoretical study of the structural and energetic properties of Ce1-xZrxO2 nanoparticles via molecular dynamics simulations.

The combination of ceria (CeO2) with different metal oxides (MO2), e.g. Ce1-xMxO2, has been strategically used to enhance its intrinsic properties. Moreover, the controlled synthesis of mixed oxide nanoparticles (NPs) opens the opportunity to explore the size dependence and chemical composition of the physical-chemical properties. However, our atomic-level understanding of how the physical-chemical and thermodynamic characteristics change with particle size and composition remains far from satisfactory. Here, we used force-field molecular dynamics simulations to investigate the effects of composition (x) and size on the physical-chemical properties of Ce1-xZrxO2 NPs with diameter from 1 (32 cations) up to 3 nm (256 cations), where x = 0.0, 0.2, 0.4, 0.6, 0.8 and 1.0. We found abrupt changes in potential energy versus temperature for NPs with more than 108 cations, indicating a structural phase transition from disordered to ordered structures, which was confirmed by the radial distribution function. We found a linear relationship between the phase transition temperature (Tpt) and the size and composition of the NPs: the increase in the molar fraction of Zr4+ and the reduction in particle size are related to lower Tpt temperature and less defined decays of potential energy versus temperature. NPs larger than 56 cations show a radial distribution function with several peaks, which is related to the order of cations and anions in these structures. These peaks gradually disappear as the size decreases and the fraction of Zr4+ increases. Similar trends were observed with X-ray diffraction analysis; for example, fluorite-like motifs occur even with 56 cations in the case of ceria, but only for NPs with 108 cations for zirconia. Common neighbor analysis confirmed that NPs with well-defined values of the temperature Tpt have face-centered cubic (fcc)-like domains in the core region. The number of ordered fcc cations increases with increasing NP size and decreasing Zr4+ concentration. Finally, we observed that ceria nucleate first during simulated annealing and occupy highly coordinated sites within the core, while Zr4+ prefers the lowest coordinated sites on the surface.

Atomic-scale insights in the interplay of chemical composition and chirality in two-dimensional chiral perovskites.

The incorporation of chiral molecules (A) in materials based on hybrid ABX3 perovskites has opened new paths to tune the optoelectronic properties of perovskites through the transfer of chirality to the inorganic BX framework. However, our atomistic understanding of the role of chemical BX composition in the magnitude of the chirality transfer is far from complete. In this study, we use density functional theory calculations and the experimental Ruddlesden-Popper chiral (R-/S-NEA)2PbBr4 structure (R-/S-NEA = R-/S-1-(1-naphthyl)ethylammonium) to investigate the effects induced by chemical substitution of Pb by Ge or Sn and Br by Cl or I on the transfer of chirality and physical-chemical properties. We have observed that different enantiomers result in opposing orientations of octahedral tiltings within the inorganic framework, thus transferring chirality to the inorganic structure. The tilts are greater in perovskites based on Pb and decrease in the sequence of Cl to Br to I, as a consequence of the decrease in the halide electronegativity that weakens the interactions between X and the -N+H3 group of the NEA chiral cation. The chirality transfer is also evident in the Rashba-Dresselhaus effects on the electronic band structure, in which we found magnitudes directly correlated to the trends of octahedra tilting. The band offsets of substitutions B and X are predominantly influenced by their natural atomic energy levels, while organic molecules play a pivotal role in modulating the ionic potential and electron affinity in systems containing light atoms. The band gap values range from 1.91 up to 3.77 eV, with chirality and anion electronegativity providing significant tuning effects on whether the band gaps are direct or indirect.

Contrasting the stability, octahedral distortions, and optoelectronic properties of 3D MABX3 and 2D (BA)2(MA)B2X7 (B = Ge, Sn, Pb; X = Cl, Br, I) perovskites.

Efficient surface passivation and toxic lead (Pb) are known obstacles to the photovoltaic application of perovskite-based solar cells. A possible solution for these problems is to use thin-films of two-dimensional (2D) perovskite-based materials and the replacement of Pb with alternative divalent cations (B); however, our atomistic understanding of the differences between (3D) three-dimensional and 2D perovskite-based materials is far from satisfactory. Herein, we report a systematic theoretical investigation based on ab initio density functional theory (DFT) calculations for both 3D MABX3 and the Ruddlesden-Popper 2D (BA)2(MA)B2X7 (B = Ge, Sn, Pb, and X = Cl, Br, I) compounds to investigate the differences (contrasts) in selected physical-chemical properties, i.e., structural parameters, energetic stability, electronic, and optical properties. We found an increased cation/anion charge separation because of the presence of organic spacers, which results in stronger Coulomb interactions in the inorganic framework, and hence, it enhances the cohesive energy (stability) within the inorganic layer. The inorganic layer constitutes the optically active region that contributes to the superior performance of perovskite-based solar cells. We quantified this effect by comparing the average electronic charges at the X sites in both 2D and 3D perovskites. This comparison is then correlated with variations in BX6-octahedron volumes, resulting in a monotonic relation. Moreover, the electronic structure characterization demonstrates that Ge-based systems present weakly sensitive band gaps to dimensionality due to a compensatory effect between Jahn-Teller distortions and quantum confinement. Lead-free GeI-, SnBr-, and SnI-based perovskites have DFT band gaps closer to the optimal value used in photovoltaic applications. Finally, as expected, the 2D systems absorption coefficients show pronounced anisotropy.

Data-driven stabilization of NimPdn-m nanoalloys: a study using density functional theory and data mining approaches.

Green hydrogen, generated through the electrolysis of water, is a viable alternative to fossil fuels, although its adoption is hindered by the high costs associated with the catalysts. Among a wide variety of potential materials, binary nickel-palladium (NiPd) systems have garnered significant attention, particularly at the nanoscale, for their efficacious roles in catalyzing hydrogen and oxygen evolution reactions. However, our atom-level understanding of the descriptors that drive their energetic stability at the nanoscale remains largely incomplete. Here, we investigate by density functional theory calculations the descriptors that drives the stability of the NimPdn-m clusters for different sizes (n = 13, 27, 41) and compositions. To achieve our goals, a large number of trial configurations were generated and selected using data mining algorithms (k-means, t-SNE) and genetic algorithms, while the most important physical-chemical descriptors were identified using Spearman correlation analysis. We have found that core-shell formation, with the smaller Ni atoms lying in the center of the particle, plays a major role in the stabilization of the nanoalloys, and this effect causes the alloys to assume a icosahedral-fragment configuration (as the unary nickel cluster) instead of a fcc fragment (as the unary palladium cluster). However, the core-shell formation in this alloy is unique in that Pd poor compositions exhibit scattered Pd atoms on the surface. As the palladium content increases, this gives rise to the complete Pd shell. This stabilization mechanism is quantitatively supported by the different correlations observed in the number of Ni-Ni and Pd-Pd bonds with energy, in which the latter tends to decrease alloy stability. Furthermore, a notable trend is the correlation between the coordination number of Ni atoms with alloy stabilization, while the coordination of Pd atoms shows an inverse correlation.

Computational screening of silver-based single-atom alloys catalysts for CO2 reduction.

Electrocatalytically reducing CO2 into value-added products is a challenging but promising process. Catalysts have been proposed to reduce the potential necessary for the reaction to occur, among which single-atom alloys (SAAs) are particularly promising. Here, we employ density functional theory calculations and the computational electrode model to predict whether silver-based SAAs have the potential to be effective electrocatalysts to convert CO2 into C1 products. We take into account surface defects by using the Ag(211) surface as a model. We also verify whether the proposed materials are prone to OH poisoning or enhance the competing hydrogen evolution reaction. Our calculations predict that these materials show weak mixing between the host and the dopant, characterized by a sharp peak in the density of states near the Fermi energy, except when copper (also a coinage metal) is used as the dopant. This affects the adsorption energy of the different intermediate molecules, yielding different reaction profiles for each substrate. As non-doped silver, copper-doped SAA tends to spontaneously desorb carbon monoxide (CO) instead of proceeding with its reduction. Other elements of the fourth period (Fe, Co, and Ni) tend to bind to the CO molecule but do not favor more reduced products. These metals also tend to enhance the hydrogen evolution reaction. On the contrary, we show that the Ir and Rh dopants have significant potential as electrocatalysts, which favors the reduction of CO over its desorption while also suppressing the hydrogen evolution reaction at potentials lower than those required by copper. They have also been shown to not be prone to poisoning by OH radicals.

Atomistic insights from DFT calculations into the catalytic properties on ceria-lanthanum clusters for methane activation.

Improving the catalytic performance of materials based on cerium oxide (CeO2) for the activation of methane (CH4) can be achieved through the following strategies: mixture of CeO2 with different oxides (e.g., CeO2-La2O3) and the use of particles with different sizes. In this study, we present a theoretical investigation of the initial CH4 dehydrogenation on (La2Ce2O7)n clusters, where n = 2, 4, and 6. Our framework relies on density functional theory calculations combined with the unity bond index-quadratic exponential potential approximation. Our results indicate that chemical species arising from the first dehydrogenation of CH4, that is, CH3 and H, bind through the formation of C-O and H-O bonds with the clusters, respectively. The coordination of the adsorption site and the chemical environment plays a crucial role in the magnitude of the adsorption energy; for example, species adsorb more strongly in the low-coordinated topO sites located close to the La atoms. Thus, it affects the activation energy barrier, which tends to be lower in configurations where the adsorption of the chemical species is stronger. During CH4 dehydrogenation, the CH3 radical can be present in a planar or tetrahedral configuration. Its conformation changes as a function of the charge transference between the molecule and the cluster, which depends on the CH3-cluster distance. Finally, we analyze the effects of the Hubbard effective parameter (Ueff) on adsorption properties, as the magnitude of localization of Ce f-states affects the hybridization of the interaction between the molecule and the clusters and hence the magnitude of the adsorption energies. We obtained a linear decrease in the adsorption energies by increasing the Ueff parameter; however, the activation energy is only slightly affected.

Theoretical investigation of (La4O6)n, (La2Ce2O7)n, and (Ce4O8)n nanoclusters (n = 10, 18): Temperature effects and O-vacancy formation.

We report a theoretical investigation of temperature, size, and composition effects on the structural, energetic, and electronic properties of the (La4O6)n, (La2Ce2O7)n, and (Ce4O8)n nanoclusters (NCs) for n = 10, 18. Furthermore, we investigated the single O vacancy formation energy as a function of the geometric location within the NC. Our calculations are based on the combination of force-field molecular dynamics (MD) simulations and density functional theory calculations. We identified a phase transition from disordered to ordered structures for all NCs via MD simulations and structural analysis, e.g., radius changes, radial distribution function, common neighbor analysis, etc. The transition is sharp for La36Ce36O126, La20Ce20O70, and Ce72O144 due to the crystalline domains in the core and less abrupt for Ce40O80, La40O60, and La72O108. As expected, radius changes are abrupt at the transition temperature, as are morphological differences between NCs located below and above the transition temperature. We found a strong dependence on the O vacancy formation energy (Evac) and its location within the NCs. For example, for La40O60, Evac decreases almost linearly as the distance from the geometric center increases; however, the same trend was not observed for Ce40O80, while there are large deviations from the linear trend for La20Ce20O70. Evac has smaller values for Ce40O80 and higher values for La40O60, that is, almost three times, while Evac has intermediate values for mixed oxides, as expected from weighted averages. Therefore, the mixture of one formula unit of La2O3 with two formula units of CeO2 has the effect of increasing the stability of CeO2 (binding energy), which increases the magnitude of the formation energy of the O vacancy.

Ab initio study for late steps of CO2 and CO electroreduction: from CHCO* toward C2 products on Cu and CuZn nanoclusters.

Electroreduction of CO2 to C2 products such as ethanol is motivated by its potential application to satisfy global energy demand in a more sustainable and renewable way. Cooper-based catalysts have exhibited highlighted performance in obtaining C2 products, but large overpotentials and poor selectivity are still challenging. Herein, we employed density functional theory calculations and the computational hydrogen electrode model to study the impact of CuZn alloys on the mechanism and selectivity of CO2 and CO electroreduction to C2 products. On both clusters, the preferred pathway to ethanol and ethylene shares a common intermediate: CH2CHO*. On Cu55, ethanol formation would occur at lower electrode potential than the formation of ethylene, which agrees with experimental studies. Since Cu42Zn13 increases the Gibbs free energy change between CH2CHO* and adsorbed acetaldehyde, the alloy exhibited lower selectivity toward ethanol than Cu55 cluster. The role of Zn is mainly related to the stronger adsorption of the intermediates on Cu42Zn13 than in the Cu55 group. Our results suggested that the d states of Zn are involved in the adsorption of intermediates, strengthening the interaction.

The role of single-atom Rh-dopants in the adsorption properties of OH and CO on stepped Ag(211) surfaces.

Several chemical reactions with commercial and environmental importance can benefit from the development of more active or selective heterogeneous catalysts. Particularly, those catalyzed by metallic surfaces are usually impacted by the presence of defects such as kinks and dopants. Here, we employed density functional theory calculations within van der Waals correction to investigate the effects of single-atom Rh-dopants in the adsorption properties of OH and CO on stepped Ag(211) surfaces. From our calculations and analyses, we found that the dopant is more energetically stable when replacing more coordinated (and less exposed to the vacuum) sites of the surface. However, in the presence of both molecules, this trend is inverted, and the dopant is more stable in the least coordinated site (step). While OH presents high adsorption energies on both doped and non-doped silver surfaces, CO binds weakly to the noble metal, and strongly on doped sites. The results are relevant for understanding single-atom catalysts on noble-metal surfaces, where the difference in selectivity and activity between the host metal and dopants is exploited. The charge redistribution caused by the dopant, and the appearance of a sharp peak in the density of states of the surface are used to rationalize the results and provide insights into the interactions involved in the adsorption of both molecules.

Underlying mechanisms of gold nanoalloys stabilization.

Gold nanoclusters have attracted significant attention due to their unique physical-chemical properties, which can be tuned by alloying with elements such as Cu, Pd, Ag, and Pt to design materials for various applications. Although Au-nanoalloys have promising applications, our atomistic understanding of the descriptors that drive their stability is far from satisfactory. To address this problem, we considered 55-atom model nanoalloys that have been synthesized by experimental techniques. Here, we combined data mining techniques for creating a large sample of representative configurations, density functional theory for performing total energy optimizations, and Spearman correlation analyses to identify the most important descriptors. Among our results, we have identified trends in core-shell formation in the AuCu and AuPd systems and an onion-like design in the AuAg system, characterized by the aggregation of gold atoms on nanocluster surfaces. These features are explained by Au's surface energy, packing efficiency, and charge transfer mechanisms, which are enhanced by the alloys' preference for adopting the structure of the alloying metal rather than the low-symmetry one presented by Au55. These generalizations provide insights into the interplay between electronic and structural properties in gold nanoalloys, contributing to the understanding of their stabilization mechanisms and potential applications in various fields.

Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder.

Some of the most common applications of machine learning (ML) algorithms dealing with small molecules usually fall within two distinct domains, namely, the prediction of molecular properties and the design of novel molecules with some desirable property. Here we unite these applications under a single molecular representation and ML algorithm by modifying the grammar variational autoencoder (GVAE) model with the incorporation of property information into its training procedure, thus creating a supervised GVAE (SGVAE). Results indicate that the biased latent space generated by this approach can successfully be used to predict the molecular properties of the input molecules, produce novel and unique molecules with some desired property and also estimate the properties of random sampled molecules. We illustrate these possibilities by sampling novel molecules from the latent space with specific values of the lowest unoccupied molecular orbital (LUMO) energy after training the model using the QM9 data set. Furthermore, the trained model is also used to predict the properties of a hold-out set and the resulting mean absolute error (MAE) shows values close to chemical accuracy for the dipole moment and atomization energies, even outperforming ML models designed to exclusive predict molecular properties using the SMILES as molecular representation. Therefore, these results show that the proposed approach is a viable way to provide generative ML models with molecular property information in a way that the generation of novel molecules is likely to achieve better results, with the benefit that these new molecules can also have their molecular properties accurately predicted.

SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning.

Machine learning as a tool for chemical space exploration broadens horizons to work with known and unknown molecules. At its core lies molecular representation, an essential key to improve learning about structure-property relationships. Recently, contrastive frameworks have been showing impressive results for representation learning in diverse domains. Therefore, this paper proposes a contrastive framework that embraces multimodal molecular data. Specifically, our approach jointly trains a graph encoder and an encoder for the simplified molecular-input line-entry system (SMILES) string to perform the contrastive learning objective. Since SMILES is the basis of our method, i.e., we built the molecular graph from the SMILES, we call our framework as SMILES Contrastive Learning (SMICLR). When stacking a nonlinear regressor on the SMICLR's pretrained encoder and fine-tuning the entire model, we reduced the prediction error by, on average, 44% and 25% for the energetic and electronic properties of the QM9 data set, respectively, over the supervised baseline. We further improved our framework's performance when applying data augmentations in each molecular-input representation. Moreover, SMICLR demonstrated competitive representation learning results in an unsupervised setting.

Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of Finite-Size Particles.

Nanoclusters are remarkably promising for the capture and activation of small molecules for fuel production or as precursors for other chemicals of high commercial value. Since this process occurs under a wide variety of experimental conditions, an improved atomistic understanding of the stability and phase transitions of these systems will be key to the development of successful technological applications. In this work, we proposed a theoretical framework to explore the potential energy surface and configuration space of nanoclusters to map the most important morphologies presented by those systems and the phase transitions between them. A fully automated process was developed, which combines global optimization techniques, classical molecular dynamics, and unsupervised machine learning algorithms. To showcase these capabilities of the approach, we explored the example of copper nanoclusters (Cun) where n = 13, 38, 55, 75, 98, 102, and 147. We not only reported a graphical potential energy surface for each size, but also explored the topology of the configuration space via structural and thermodynamic analyses. The effect of size on the potential energy surface and the critical temperature for solid-liquid phase transitions were also reported, highlighting the impact of magic numbers on those quantities.

Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining.

Ionic liquids have attracted the attention of researchers as possible electrolytes for electrochemical energy storage devices. However, their properties, such as the electrochemical stability window (ESW), ionic conductivity, and diffusivity, are influenced both by the chemical structures of cations and anions and by their combinations. Most studies in the literature focus on the understanding of common ionic liquids, and little effort has been made to find ways to improve our atomistic understanding of those systems. The goal of this paper is to explore the structural characteristics of cations and anions that form ionic liquids that can expand the HOMO/LUMO gap, a property directly linked to the ESW of the electrolyte. For that, we design a framework for randomly generating new ions by combining their fragments. Within this framework, we generate about 104 cations and 104 anions and fully optimize their structures using density functional theory. Our calculations show that aromatic cations are less stable ionic liquids than aliphatic ones, an expected result if chemical rationale is used. More importantly, we can improve the gap by adding electron-donating and electron-withdrawing functional groups to the cations and anions, respectively. The increase can be about 2 V, depending on the case. This improvement is reflected in a wider ESW.

Computational investigation of van der Waals corrections in the adsorption properties of molecules on the Cu(111) surface.

Here, we report a computational investigation on the role of the most common van der Waals (vdW) corrections (D2, D3, D3(BJ), TS, TS+SCS, TS+HI, and dDsC) employed in density functional theory (DFT) calculations within local and semilocal exchange-correlation functionals to improve the description of the interaction between molecular species and solid surfaces. For this, we selected several molecular model systems, namely, the adsorption of small molecules (CH3, CH4, CO, CO2, H2O, and OH) on the close-packed Cu(111) surface, which bind via chemisorption or physisorption mechanisms. As expected, we found that the addition of the vdW corrections enhances the energetic stability of the Cu bulk in the face-centered cubic structure, which contributes to increasing the magnitude of the mechanical properties (elastic constants, bulk, Young, and shear modulus). Except for the TS+SCS correction, all vdW corrections substantially increase the surface energy, while the work function changes by about 0.05 eV (largest change). However, we found substantial differences among the vdW corrections when comparing its effects on interlayer spacing relaxations. Based on bulk and surface results, we selected only the D3 and dDsC vdW corrections for the study of the adsorption properties of the selected molecules on the Cu(111) surface. Overall, the addition of these vdW corrections has a greater effect on weakly interacting systems (CH4, CO2, H2O), while the chemisorption systems (CH3, CO, OH) are less affected.

Ab initio investigation of the role of the d-states on the adsorption and activation properties of CO2 on 3d, 4d, and 5d transition-metal clusters.

We report a theoretical investigation of the adsorption and activation properties of CO2 on eight-atom 3d, 4d, and 5d transition-metal (TM) clusters based on density functional theory calculations. From our results and analyses, in the lowest energy configurations, CO2 binds via a chemisorption mechanism on Fe, Co, Ni, Ru, Rh, Pd, Os, Ir, and Pt (adsorption energy from -0.49 eV on Pt up to -1.40 eV on Os), where CO2 breaks its linearity and adopts an angular configuration due to the charge transfer from the clusters toward the C atom in the adsorbed CO2. In contrast, it binds via physisorption on Cu, Ag, and Au and maintains its linearity due to a negligible charge transfer toward CO2 and has a small adsorption energy (from -0.17 eV on Cu up to -0.18 eV on Ag). There is an energetic preference for twofold bridge TM sites, which favors binding of C with two TM atoms, which enhances the charge transfer ten times than on the top TM sites (onefold). We identified that the strength of the CO2-TM8 interaction increases when the energy values of the highest occupied molecular orbital (HOMO) of the TM8 are closer to the energy values of the lowest unoccupied molecular orbital of CO2, which contributes to maximize the charge transfer toward the molecule. Beyond the energy position of the HOMO states, the delocalization of 5d orbitals plays an important role in the adsorption strength in TM, especially for the iron group, e.g., the adsorption energies are -1.08 eV (Fe, 3d), -1.19 eV (Ru, 4d), and -1.40 eV (Os, 5d).

Ab initio study of the adsorption properties of CO2 reduction intermediates: The effect of Ni5Ga3 alloy and the Ni5Ga3/ZrO2 interface.

The Ni5Ga3 alloy supported on ZrO2 is a promising catalyst for the reduction of CO2 due to its higher selectivity to methanol at ambient pressure, e.g., activity comparable to industrial catalysts. However, our atomistic understanding of the role of the cooperative effects induced by the Ni5Ga3 alloy formation and its Ni5Ga3/ZrO2 interface in the CO2 reduction is still far from satisfactory. In this work, we tackle these questions by employing density functional theory calculations to investigate the adsorption properties of key CO2 reduction intermediates (CO2, H2, cis-COOH, trans-COOH, HCOO, CO, HCO, and COH) on Ni8, Ga8, Ni5Ga3, (ZrO2)16, and Ni5Ga3/(ZrO2)16. We found that Ni containing clusters tended to assume wetting configurations on the (ZrO2)16 cluster, while the presence of Ga atoms weakens the adsorption energies on the oxide surface. We also observed that CO2 was better activated on the metal-oxide interfaces and on the oxide surface, where it was able to form CO3-like structures. Meanwhile, H2 activation was only observed on Ni sites, which indicates the importance of distinct adsorption sites that can favor different CO2 reduction steps. Moreover, the formation of the metal-oxide interface showed to be beneficial for the adsorption of COOH isomers and unfavorable for the adsorption of HCOO.