Transition Metal Surfaces Research Articles

Predicting adsorption energies and the physical properties of H, N, and O adsorbed on transition metal surfaces: A machine learning study

We present a machine learning study utilizing the Hierarchically Interacting Particle Neural Network to predict the adsorption properties of atomic H, N, and O on various single metal and bimetallic single crystal FCC surfaces. Our trained HIP-NN models directly predict, from atomic species and coordinates of the clean surface, and initial adsorption site, adsorption energies with a MAE of 0.08 eV to 0.16 eV, adsorption heights with a MAE of 0.08 Å to 0.09 Å, and a buckling of the first layer of the substrate with a MAE of 0.07 Å to 0.12 Å, illustrating that a neural network can calculate the physical properties of a surface/adsorbate system along with adsorption energy. Our MAEs for adsorption energy also compare favorably with MAEs presented by other works predicting the adsorption energies of H, N, and O. We also demonstrate that while HIP-NN can predict on these systems without explicit periodic boundary conditions, the inclusion of explicit periodic boundary conditions drastically improves the results. Our results also reveal that the buckling of the first layer of the substrate can be utilized to prune datasets, removing unstable surfaces.

Understanding non-covalent interactions of graphene oxide toward transition metal surfaces and relation of binding constants with titration end points from dynamic light scattering studies

The understanding of non-covalent binding interactions of graphene oxide toward transition metal surfaces (Fe, Co, Ni, and Cu) was observed by ultraviolet–visible absorption spectroscopy, fluorescence emission spectroscopy, hydrodynamic size, and zeta potential studies through titration experiments. These interactions mainly occur through C=C double bonds of graphene oxide. Iron and cobalt nanoparticles interact strongly as compared to nickel and copper nanoparticles. The obtained Stern–Volmer plots are curved indicating that static and dynamic quenching occur simultaneously in these systems. The curves obtained for size titration graphs indicated the saturation end point for these titrations, which were then compared with binding constants obtained from linear Stern–Volmer plots. Interestingly, with lower binding constants, a higher concentration of nanoparticles was required for titration end points. These two complimentary techniques stood well quantitatively toward each other. Upon titrating the nanoparticles with graphene oxide, the zeta potential always lowered close to the value of graphene oxide, indicating that hybrids are more stable than the nanoparticles.

Ionic conductivity and disorder in calcium and barium nitrogen hydrogen phases.

Nitrogen-hydrogen based alkali and alkaline earth metal compounds have recently received a substantial amount of attention as co-catalysts for heterogeneous mild condition ammonia synthesis (MCAS). The incorporation of these materials has been shown to result in positive reaction orders with respect to H2, solving the issue of hydrogen poisoning, e.g., the occupation of the majority of transition metal (TM) active sites by H-adatoms due to the significantly faster kinetics of H2 dissociation as compared to N2. The mechanism that underlies this is thought to be the incorporation (sinking) of H-adatoms from the surface of TMs to the bulk of the N-H phases. Thus, the slower kinetics of N2 dissociation no longer inhibit ammonia synthesis, and improvements in the kinetics dissociation for TM can be realised without consideration for which specific gases are affected (e.g., the circumventing of scaling relations). The ability to transport H-adatoms from the surface of TM is therefore of fundamental importance to the properties of the N-H co-catalyst implying that the conductivity of these species towards H and N ions, and NHx species, is of utmost importance. As such, we investigate two N-H systems that can be prepared by reacting the respective hydrides with nitrogen resulting in nitride-hydride and imide forms for Ca and Ba, respectively. These have both been previously shown to promote ammonia synthesis and here we investigate their conductive properties, and discuss these systems in the context of activity and stability of the total system with specific focus on the rise of secondary anion species, and the presence of barium in the system.

Robust and facile detection of formaldehyde through transition metals doped olympicene sensors: a step forward DFT investigation.

Formaldehyde, a volatile organic compound (VOC) released by building and decoration materials, has many applications in the chemical feedstock industry. Excessive release of formaldehyde can cause serious health issues, such as chest tightness, cough, cancer, and tissue damage. Therefore, detection of formaldehyde is required. Herein transition metal (Fe, Ni, and Pd) doped olympicene is evaluated as a gas sensor for the detection of formaldehyde. The performance of the designed electrochemical sensor is evaluated through interaction energy, natural bond orbital (NBO) non-covalent interaction (NCI), electron density differences (EDD), electrostatic potential (ESP), quantum theory of atom in molecule (QTAIM), frontier molecular orbital (FMO), and density of states (DOS) analysis. Interaction energies obtained at B3LYP-D3/def-2 TZVP level of theory shows that formaldehyde is physiosorbed over the surface of transition metal doped olympicene. The trend for interaction energy is OLY(Ni)/HCHO > OLY(Fe)/HCHO > OLY(Pd)/HCHO. The presence of non-covalent interactions is confirmed by the QTAIM and NCI analyses, while transfer of charges is confirmed by natural bond orbital analysis. The reduced density gradient (RDG) approach using noncovalent interaction (NCI) analysis demonstrates that electrostatic hydrogen bonding interactions prevail in the complexes. Recovery time is calculated to check the reusability of the sensor. This study may provide a deep insight for the designing of highly efficient electrochemical sensor against formaldehyde with transition metals doped on olympicene.

Toward a new definition of surface energy for late transition metals.

Surface energy is a top-importance stability descriptor of transition metal-based catalysts. Here, we combined density functional theory (DFT) calculations and a tiling scheme measuring surface areas of metal structures to develop a simple computational model predicting the average surface energy of metal structures independently of their shape. The metals considered are W, Ru, Co, Ir, Ni, Pd, Pt, Cu, Ag and Au. Lorentzian trends derived from the DFT data proved effective at predicting the surface energy of metallic surfaces but not for metal clusters. We used machine-learning protocols to build an algorithm that improves the Lorentzian trend's accuracy and is able to predict the surface energies of metal surfaces of any crystal structure, i.e., face-centred cubic, hexagonal close-packed, and body-centred cubic, but also of nanostructures and sub-nanometer clusters. The machine-learning neural network takes easy-to-compute geometric features to predict metallic moieties surface energies with a mean absolute error of 0.091 J m-2 and an R2 score of 0.97.

The Role of Hydrogen Adsorption Site Diversity in Catalysis on Transition-Metal Phosphide Surfaces

The Role of Hydrogen Adsorption Site Diversity in Catalysis on Transition-Metal Phosphide Surfaces

Enhancing Electron Correlation at a 3d Ferromagnetic Surface.

Spin-resolved momentum microscopy and theoretical calculations are combined beyond the one-electron approximation to unveil the spin-dependent electronic structure of the interface formed between iron (Fe) and an ordered oxygen (O) atomic layer, and an adsorbate-induced enhancement of electronic correlations is found. It is demonstrated that this enhancement is responsible for a drastic narrowing of the Fe d-bands close to the Fermi energy (EF ) and a reduction of the exchange splitting, which is not accounted for in the Stoner picture of ferromagnetism. In addition, correlation leads to a significant spin-dependent broadening of the electronic bands at higher binding energies and their merging with satellite features, which are manifestations of a pure many-electron behavior. Overall, adatom adsorption can be used to vary the material parameters of transition metal surfaces to access different intermediate electronic correlated regimes, which will otherwise not be accessible. The results show that the concepts developed to understand the physics and chemistry of adsorbate-metal interfaces, relevant for a variety of research areas, from spintronics to catalysis, need to be reconsidered with many-particle effects being of utmost importance. These may affect chemisorption energy, spin transport, magnetic order, and even play a key role in the emergence of ferromagnetism at interfaces between non-magnetic systems.

Oxygen‐Chlorine Chemisorption Scaling for Seawater Electrolysis on Transition Metals: The Role of Redox

AbstractTo clarify what controls species oxidation selectivity in seawater electrolysis, density functional theory (DFT) is used to identify chemisorption enthalpy trends and scaling relations for the simplest relevant adsorbates (O, Cl, and H) on relevant surfaces of 3d transition metals, as well as Pd and Pt, in face‐centered‐cubic and, if different, their ground‐state crystal structures. Approximations are tested for electron exchange‐correlation (XC) and van der Waals interactions to assess their ability to reproduce experimental adsorption enthalpies of H and O on Pt(111). The vdW‐uncorrected generalized gradient approximation to XC of Perdew, Burke, and Ernzerhof (PBE) agrees most closely with experiments. Using DFT‐PBE thereafter, it is determined that the O chemisorption enthalpy on this wide range of transition‐metal surfaces is proportional to the sum of first and second atomic ionization energies, akin to a Born–Haber cycle for a redox reaction, indicating that metal redox activity controls O chemisorption strength. Then it is shown that the O and Cl chemisorption enthalpies are strongly correlated, suggesting that the transition metals considered will oxidize unselectively water and Cl–. This strong correlation appears also for crystal reduction potentials of binary oxides and chlorides, indicating a fundamental challenge for future seawater electrode materials design.

Adsorption energies on transition metal surfaces: towards an accurate and balanced description

Density functional theory predictions of binding energies and reaction barriers provide invaluable data for analyzing chemical transformations in heterogeneous catalysis. For high accuracy, effects of band structure and coverage, as well as the local bond strength in both covalent and non-covalent interactions, must be reliably described and much focus has been put on improving functionals to this end. Here, we show that a correction from higher-level calculations on small metal clusters can be applied to improve periodic band structure adsorption energies and barriers. We benchmark against 38 reliable experimental covalent and non-covalent adsorption energies and five activation barriers with mean absolute errors of 2.2 kcal mol−1, 2.7 kcal mol−1, and 1.1 kcal mol−1, respectively, which are lower than for functionals widely used and tested for surface science evaluations, such as BEEF-vdW and RPBE.

A Machine Learning Model for Adsorption Energies of Chemical Species Applied to CO2 Electroreduction

Machine learning methods are applied to obtain adsorption energies of different chemical species on (100), (111), and (211) FCC surfaces of several transition metals and Pb. Based on information available in databases containing adsorption energies obtained via first-principles calculations, we implemented MLPRegressor, XGBRegressor, Support Vector Regressor, and Stacking machine learning models. The fourth model is created from the combination of the previous three through a Stacking technique. In a broader context, our results showed the robustness of machine learning models and the ability of these methods to speed up the screening materials to specific goals, at a low computational cost. We emphasize the ability of our models to predict the adsorption energy for different systems. Due to their generality of them, we were able to make ion predictions on metallic surfaces, taking into account the influence of different functionals. This capability is of special significance due to the difficulty of calculating the correct energy for charged systems by traditional atomistic simulations. From then on, we made predictions for important chemical species in the CO2 electroreduction process, such as the radical anion CO2 −•, an important intermediary for obtaining new products in view of a negative carbon footprint.

Looking beyond Adsorption Energies to Understand Interactions at Surface using Machine Learning

AbstractIdentifying factors that influence interactions at the surface is still an active area of research. In this work, the importance of analyzing bond length activations (BLact) along with adsorption energies (Ea) while interpreting Density Functional Theory (DFT) results is emphasized. Investigating adsorption of different small molecules, such as O2, N2, CO, and CO2, on commonly studied facets ((100), (110), and (111)) of seven fcc transition metal surfaces (M=Ag, Au, Cu, Ir, Rh, Pt, and Pd) demonstrates the missing linear correlation between Ea and BLact. Further, tree based Machine Learning (ML) models reinforce the missing linear correlation between the two parameters and also highlight the importance of analyzing both to develop a better understanding of adsorption at surfaces. The best performing Random Forest models have a mean absolute error (MAE) of 0.19 eV for Ea prediction, and even lower MAE of 0.012 Å for BLact prediction. While often d‐band center is correlated with Ea, our observations show that infact the d‐band center has a better correlation with BLact. These observations emphasizes the role of BLact in gaining a fuller picture for catalysis. The fact that the factors responsible for BLact is a lesser‐explored subject adds to the novelty of the findings.

Understanding Activity Trends in Furfural Hydrogenation on Transition Metal Surfaces

Understanding Activity Trends in Furfural Hydrogenation on Transition Metal Surfaces

Single transition metal atom stabilized on double metal carbide MXenes for hydrogen evolution reaction: a density functional theory study

Double metal carbide MXenes have received considerable attention for use in renewable energy storage technologies in recent years. Here, density functional theory calculations were performed to investigate the hydrogen evolution reaction (HER) performances of double metal carbide MXenes (Cr2TiC2O2 and the Mo2TiC2O2 monolayer (ML) modified by a single transition metal (TM) atom (Co, Ni, Cu, Zn, Rh, Pd, Ag, Cd, Ir, Pt, Au, or Hg)). The thermodynamic stabilities of TM adatoms on pristine Cr2TiC2O2 and Mo2TiC2O2 MLs and defective Cr2TiC2O2 and Mo2TiC2O2 MLs with oxygen vacancies (denoted as TM-M′2TiC2O2−δ , where M′ = Cr or Mo) were calculated, and the results indicated that the introduction of oxygen vacancies can increase the stabilities of TM adatoms. The TM modification on the MXenes surface tuned the Gibbs free energy of hydrogen adsorption G H, and the G H values of Au-, Co-Cr2TiC2O2−δ , and Ni-Mo2TiC2O2−δ closed to zero values (0.07, −0.07, and 0.02 eV, respectively). The presence of TM adatoms also changed the reaction mechanism of H2 desorption and reduced the activation barrier for H2 production to improve the catalytic efficiency. Nine TM-M′2TiC2O2−δ systems were found to have both HER activity and a lower H2 desorption reaction barrier than the pristine MXenes. Systematic electronic structure analyses showed that charge rearrangement through TM modification could tune the number of electrons gained by the surface O atom and have an impact on the hydrogen adsorption strength. These results indicated that TM surface modification is an effective method for improving the HER catalytic activity of double TM carbides.

Stabilizing Interfacial Reactions for Stable Cycling of High‐Voltage Sodium Batteries

AbstractDeveloping advanced electrolytes is critical for stabilizing electrode/electrolyte interfacial reactions and thus extending cycling stability of sodium (Na) batteries, especially when a high‐voltage cathode (such as NaNi0.68Mn0.22Co0.10O2 (NaNMC)) is used to achieve high energy density in batteries. Here, an advanced electrolyte based on sodium bis(fluorosulfonyl)imide (NaFSI)–triethyl phosphate, which is highly stable against a high‐voltage cathode, enabling long‐term cycling of sodium batteries, is reported. Na||NaNMC cells with this electrolyte demonstrate 89% capacity retention after 500 cycles with a cutoff voltage of 4.2 V versus Na/Na+. A full cell of hard carbon||NaNMC also exhibits good capacity retention of 83.5% after 200 cycles. Postmortem analyses on the cycled electrodes reveal that stabilization of the high‐voltage cathode can be attributed to the formation of a stable electrode/electrolyte interphase layer. The interphase is generated mainly by salt decomposition, which suppresses transition metal dissolution and surface reconstruction on the cathode. The optimized electrolyte can minimize solid electrolyte interphase dissolution to avoid capacity loss. This study offers a feasible pathway to achieve extended cycling of high‐voltage sodium batteries and guide further improvements in cycling performance of batteries by manipulating the chemistry of the electrolytes and interphase properties.

Electronic structure factors and the importance of adsorbate effects in chemisorption on surface alloys

The chemisorption energy is an integral aspect of surface chemistry, central to numerous fields such as catalysis, corrosion, and nanotechnology. Electronic-structure-based methods such as the Newns-Anderson model are therefore of great importance in guiding the engineering of material surfaces with optimal properties. However, existing methods are inadequate for interpreting complex, multi-metallic systems. Herein, we introduce a physics-based chemisorption model for alloyed transition metal surfaces employing primarily metal d-band properties that accounts for perturbations in both the substrate and adsorbate electronic states upon interaction. Importantly, we show that adsorbate-induced changes in the adsorption site interact with its chemical environment leading to a second-order response in chemisorption energy with the d-filling of the neighboring atoms. We demonstrate the robustness of the model on a wide range of transition metal alloys with O, N, CH, and Li adsorbates yielding a mean absolute error of 0.13 eV versus density functional theory reference chemisorption energies.

Role of Surface Oxygen Vacancies and Oxygen Species on CuO Nanostructured Surfaces in Model Catalytic Oxidation and Reductions: Insight into the Structure-Activity Relationship Toward the Performance.

Defect engineering, such as modification of oxygen vacancy density, has been considered as an effective approach to tailor the catalytic performance on transition-metal oxide nanostructured surfaces. The role of oxygen vacancies (OV) on the surface of the as-prepared, zinnia-shaped morphology of CuO nanostructures and their marigold forms on calcination at 800 °C has been investigated through the study of model catalytic reactions of reduction of 4-nitrophenol and aerobic oxidation of benzyl alcohol. The OV on the surfaces of different morphologies of CuO have been identified and quantified through Rietveld analysis and HRTEM, EPR, and XPS studies. The structure-activity relationships between surface oxygen vacancies (OV) and catalytic performance have been systematically investigated. The enhanced catalytic performance of the cubic CuO nanostructures compared to their as-prepared forms has been attributed to the formation of surface oxygen species on the reactive and dominant (110) surface that has low oxygen vacancy formation energy. The mechanistic role of surface oxygen species in the studied reactions has been quantitatively correlated with the catalytic activity of the different morphological forms of the CuO nanostructures.

Adsorption Site Preference Determined by Triangular Topology: Application of the Method of Moments to Transition Metal Surfaces

The adsorption sites of the top and hollow on the close-packed surfaces of transition metals are well known. In this paper, which site is more preferred for the adsorption of atoms and molecular fragments on the metal surfaces is discussed based on the topology of the adsorption geometry. For this purpose, the method of moments for the electronic density of states is applied to the surface. Adsorption at the hollow site generates a triangular topology, leading to a more negative value of the third moment (μ3) than that at the top site, which generates no triangular topology. When the difference in energy between the two adsorption sites is plotted against the band filling of the metal surface, a characteristic node at around the intermediate band filling can be found. This is a signature that the energy difference curve is controlled by μ3. Roughly speaking, the hollow-site adsorption, which has a more negative μ3 value, takes precedence at low band fillings, while the top site adsorption, which has a less negative μ3 value, takes precedence at high band fillings. One can conclude that an adsorption structure with more three-membered rings on a surface is more stable at low electron counts whereas that with less three-membered rings is more stable at high electron counts. However, if the strength of the metal–adsorbate bond is significantly greater than that of the metal–metal bond, the effect of the second moment (μ2) on the energy difference curve cannot be neglected. The hollow-site adsorption leads to a larger value of μ2 due to the topological feature of a larger coordination number around the adsorbate atom. As a result, the hollow-site adsorption is preferred over the top site at any band filling.

Charting the Atomic C Interaction with Transition Metal Surfaces.

Carbon interaction with transition metal (TM) surfaces is a relevant topic in heterogeneous catalysis, either for its poisoning capability, for the recently attributed promoter role when incorporated in the subsurface, or for the formation of early TM carbides, which are increasingly used in catalysis. Herein, we present a high-throughput systematic study, adjoining thermodynamic plus kinetic evidence obtained by extensive density functional calculations on surface models (324 diffusion barriers located on 81 TM surfaces in total), which provides a navigation map of these interactions in a holistic fashion. Correlation between previously proposed electronic descriptors and ad/absorption energies has been tested, with the d-band center being found the most suitable one, although machine learning protocols also underscore the importance of the surface energy and the site coordination number. Descriptors have also been tested for diffusion barriers, with ad/absorption energies and the difference in energy between minima being the most appropriate ones. Furthermore, multivariable, polynomial, and random forest regressions show that both thermodynamic and kinetic data are better described when using a combination of different descriptors. Therefore, looking for a single perfect descriptor may not be the best quest, while combining different ones may be a better path to follow.

(Invited) Mechanism of Interlayer Transport on a Growing Metal Surface: 2D vs. 3D Growth

The atomic scale transitions corresponding to diffusion and interlayer transport of metal adatoms on the low energy, close packed surfaces of several transition metals are studied using density functional theory calculations within the generalized gradient approximation. Minimum energy paths and estimates of activation energy are calculated for processes that influence whether the crystal grows layer-by-layer, i.e. 2D growth, or whether new islands nucleate on top of existing islands resulting in 3D growth. In some cases, the path of lowest activation energy for the descent of an adatom, i.e. interlayer transport, turns out to take place near, but not at, a kink site on a step. The energy barrier for the adatom to subsequently round the corner and enter the kink site is significantly higher. This near-kink-descent mechanism promotes the formation of a new row of step atoms and leads to the introduction of additional kink sites, thereby opening up new low activation energy paths for descent and promoting 2D growth. The sites adjacent and above the step edge can provide large binding energy for the adatom, and form a trough along which the adatom can migrate before descending, thereby increasing the probability that an adatom finds a kink site. These features of the energy landscape for an adatom point to the possibility of re-entrant layer-by-layer growth mode and have, for example, been found for Pt(111) and Au(111) surfaces.

Metal–organic framework-derived Co@NMPC as efficient electrocatalyst for hydrogen evolution reaction: Revealing the synergic effect of pyridinic N–Co

Developing hydrogen economy is one of the feasible routes to reduce carbon emission in response to the energy crisis and global warming. The hydrogen generation by electrochemical water splitting has received widespread attention, but it is still challenging to fabricate high-efficient electrocatalysts to decrease the kinetic energy barrier of hydrogen evolution reaction (HER). Loading transition metal (TM) nanoparticles (NPs) into heteroatom-doped carbon materials (HCM) has been reported as a capable scheme to increase the electrochemical activity and stability, but the synergic effect between TM surface and HCM is still worth exploring. Ascertaining that, we used metal-organic frameworks (MOFs) as the sacrificial precursor to synthesis a series of Co NPs encapsulated in N-doped microporous carbon (NMPC) nanocatalysts (denoted as Co@NMPC) with different N species (such as pyrrolic, pyridinic and graphitic N). The nanocatalyst prepared at an appropriate condition displayed an outstanding HER activity with an overpotential of 193 mV in 1 M KOH solution and 132 mV in 0.5 M H2SO4 solution to reach 10 mA cm−2 current density. Furthermore, the results of in situ shielding tests indicate that the synergy of pyridinic N–Co site owing to the intimate contact between Co surface and NMPC play the pivotal role in boosting HER performance. Density functional theory (DFT) calculations were employed to obtain an in-depth mechanism of synergic effect between Co and NMPC.