Properties of real metallic surfaces: Effects of density functional semilocality and van der Waals nonlocality

Engineering MOF/carbon nitride heterojunctions for effective dual photocatalytic CO2 conversion and oxygen evolution reactions

Photocatalysis appears as one of the most promising avenues to shift towards sustainable sources of energy, owing to its ability to transform solar light into chemical energy, e.g. production of chemical fuels via oxygen evolution (OER) and CO2 reduction (CO2RR) reactions. Ti metal-organic frameworks (MOFs) and graphitic carbon nitride derivatives, i.e. poly-heptazine imides (PHI) are appealing CO2RR and OER photo-catalysts respectively. Engineering of an innovative Z-scheme heterojunction by assembling a Ti-MOF and PHI offers an unparalleled opportunity to mimick an artificial photosynthesis device for dual CO2RR/OER catalysis. Along this path, understanding of the photophysical processes controlling the MOF/PHI interfacial charge recombination is vital to fine tune the electronic and chemical features of the two components and devise the optimum heterojunction. To address this challenge, we developed a modelling approach integrating force field Molecular Dynamics (MD), Time-Dependent Density Functional Theory (TD-DFT) and Non-Equilibrium Green Function DFT (NEGF-DFT) tools with the aim of systematically exploring the structuring, the opto-electronic and transport properties of MOF/PHI heterojunctions. We revealed that the nature of the MOF/PHI interactions, the interfacial charge transfer directionality and the absorption energy windows of the resulting heterojunctions can be fine tuned by incorporating Cu species in the MOF and/or doping PHI with mono- or divalent cations. Interestingly, we demonstrated that the interfacial charge transfer can be further boosted by engineering MOF/PHI device junctions and application of negative bias. Overall, our generalizable computational methodology unravelled that the performance of CO2RR/OER photoreactors can be optimized by chemical and electronic tuning of the components but also by device design based on reliable structure-property rules, paving the way towards practical exploitation.

Metal-water interface formation: Thermodynamics from ab initio molecular dynamics simulations

Metal-water interfaces are central to many electrochemical, (electro)catalytic, and materials science processes and systems. However, our current understanding of their thermodynamic properties is limited by the scarcity of accurate experimental and computational data and procedures. In this work, thermodynamic quantities for metal-water interface formation are computed for a range of FCC(111) surfaces (Pd, Pt, Au, Ag, Rh, and PdAu) through extensive density functional theory based molecular dynamics and the two-phase entropy model. We show that metal-water interface formation is thermodynamically favorable and that most metal surfaces studied in this work are completely wettable, i.e., have contact angles of zero. Interfacial water has higher entropy than bulk water due to the increased population of low-frequency translational modes. The entropic contributions also correlate with the orientational water density, and the highest solvation entropies are observed for interfaces with a moderately ordered first water layer; the entropic contributions account for up to ∼25% of the formation free energy. Water adsorption energy correlates with the water orientation and structure and is found to be a good descriptor of the internal energy part of the interface formation free energy, but it alone cannot satisfactorily explain the interfacial thermodynamics; the interface formation is driven by the competition between energetic and entropic contributions. The obtained results and insight can be used to develop, parameterize, and benchmark theoretical and computational methods for studying metal-water interfaces. Overall, our study yields benchmark-quality data and fundamental insight into the thermodynamic forces driving metal-water interface formation.

Structure and Reactivity of Active Oxygen Species on Silver Surfaces for Ethylene Epoxidation

The epoxidation of ethylene stands as one of the most important industrial catalytic reactions, and silver-based catalysts show superior activity and selectivity. Oxygen is activated on the surface of silver during the reaction and exerts a substantial impact on product selectivity. Notably, the oxygen species residing in the topmost atomic layers profoundly influence the reactivity of a catalyst. However, their characterization under in situ reaction conditions remains a huge challenge, and specific structures have not been identified yet. In this study, we employ in situ X-ray photoelectron spectroscopy and density functional theory calculations to determine the oxygen species formed at the topmost atomic layers of a silver foil and to assign them a structure. Three different groups of oxygen species activated on silver are identified: (i) surface lattice oxygen and two oxygen species originating from associatively adsorbed dioxygen and (ii) top and (iii) subsurface oxygen. Transient in situ photoelectron spectroscopy experiments are carried out to reveal the dynamic evolution and thus reactivity of the different oxygen species under ethylene epoxidation reaction environments. The top oxygen atom from the adsorbed associated dioxygen is the most active. Meanwhile, a frequency-selective data analysis method, developed to process time-resolved data, provides insights into the evolving trends of peak intensities for different oxygen species. The versatility of this method suggests its potential application in future time-resolved characterization studies.

Surface Segregation Studies in Ternary Noble Metal Alloys: Comparing DFT and Machine Learning with Experimental Data

Surface segregation, whereby the surface composition of an alloy differs systematically from the bulk, has historically been hard to study, because it requires experimental and modeling methods that span alloy composition space. In this work, we study surface segregation in catalytically relevant noble and platinum-group metal alloys with a focus on three ternary systems: AgAuCu, AuCuPd, and CuPdPt. We develop a data set of 2478 fcc slabs with those compositions including all three low-index crystallographic orientations relaxed with Density Functional Theory using the PBEsol functional with D3 dispersion corrections. We fine-tune a machine learning model on this data and use the model in a series of 1800 Monte Carlo simulations spanning ternary composition space for each surface orientation and ternary chemical system. The results of these simulations are validated against prior experimental surface segregation data collected using composition spread alloy films for AgAuCu and AuCuPd. Our findings reveal that simulations conducted using the (110) orientation most closely match experimentally observed surface segregation trends, and while predicted trends qualitatively match observation, biases in the PBEsol functional limit numeric accuracy. This study advances understanding of surface segregation and the utility of computational studies and highlights the need for further improvements in simulation accuracy.

Structure-driven tuning of catalytic properties of core-shell nanostructures

The annual increase in demand for renewable energy is driving the development of catalysis-based technologies that generate, store and convert clean energy by splitting and forming chemical bonds. Thanks to efforts over the last two decades, great progress has been made in the use of core-shell nanostructures to improve the performance of metallic catalysts. The successful preparation and application of a large number of bimetallic core-shell nanocrystals demonstrates the wide range of possibilities they offer and suggests further advances in this field. Here, we have reviewed recent advances in the synthesis and study of core-shell nanostructures that are promising for catalysis. Particular attention has been paid to the structural tuning of the catalytic properties of core-shell nanostructures and to theoretical methods capable of describing their catalytic properties in order to efficiently search for new catalysts with desired properties. We have also identified the most promising areas of research in this field, in terms of experimental and theoretical studies, and in terms of promising materials to be studied.

Insight into Controllable Metal-Support Interactions in Metal/Metal Electrocatalysts for Efficient Energy-Saving Hydrogen Production

Controllable metal-support interaction (MSI) modulations have long been studied for improving the performance of catalysts supported on metal oxides. However, the corresponding in-depth study for metal1-metal2 (M1-M2) composited configurations is rarely achieved due to the lack of reliable models and manipulation mechanisms of MSI modifications. We modeled ruthenium on copper support (Ru-Cu) metal catalysts with negligible interfacial contact potential (e0.06 V) and investigated MSI-dependent hydrogen evolution reaction (HER) catalysis kinetics induced by an electronic hydroxyl (HO-) modifier. Comprehensive simulations and characterizations confirmed that adjusting the HO- coverage can readily realize the tailorable improvement of MSI, facilitating charge migration at the Ru-Cu interface and optimizing the overall HER pathway on active Ru. As a result, a 5/10 monolayer (ML) HO-modified catalyst (5/10 ML) exhibits superior HER activity and durability owing to the relatively stronger MSI. This catalyst also ensured sustainable and efficient hydrogen generation in a urea electrolyzer with significant energy savings. Our work provides a valuable reference for optimizing the MSI-activity relationship in M1-M2 catalysts that target more than just HER.

Adiabatic connection interaction strength interpolation method made accurate for the uniform electron gas

The adiabatic connection interaction strength interpolation (ISI)-like method provides a high-level expression for the correlation energy, being, in principle, exact not only in the weak-interaction limit, where it recovers the second-order Görling-Levy perturbation term, but also in the strong-interaction limit that is described by the strictly correlated electron approach. In this work, we construct a genISI functional made accurate for the uniform electron gas, a solid-state physics paradigm that is a very difficult test for ISI-like correlation functionals. We assess the genISI functional for various jellium spheres with the number of electrons Z ≤ 912 and for the non-relativistic noble atoms with Z ≤ 290. For the jellium clusters, the genISI is remarkably accurate, while for the noble atoms, it shows a good performance, similar to other ISI-like methods. Then, the genISI functional can open the path using the ISI-like method in solid-state calculations.

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.

Structural, electronic and magnetic properties of greigite Fe3S4by GGA and GGA+Uversus SCAN meta-GGA density functionals

The performance of exchange-correlation functional of density functional theory represented in generalized gradient approximation (GGA) and in the strongly constrained and appropriately normed (SCAN) meta-GGA scheme to study structural, electronic, and magnetic properties of greigite (Fe3S4) was investigated. The effects of inclusion of strong electron correlations represented by on-site Hubbard correctionU, and nonlocality of the long-range van der Waals (vdW) interactions were also considered. Geometry optimization yielded the inverse spinel structure and lattice parameter of greigite in good agreement with experimental data. Calculated electronic structure revealed a half-metallic nature of the greigite bands for the applied functionals except for GGA, which predicts metallic behavior. Antiferromagnetic coupling of iron ions in tetrahedral and octahedral coordinations makes the overall crystal structure ferrimagnetic. In general the GGA+Uand SCAN show comparable performance in prediction physical properties of greigite. Inclusion of the vdW correction does not change the character of the bands.

Machine Learning Density Functionals from the Random-Phase Approximation

Kohn-Sham density functional theory (DFT) is the standard method for first-principles calculations in computational chemistry and materials science. More accurate theories such as the random-phase approximation (RPA) are limited in application due to their large computational cost. Here, we use machine learning to map the RPA to a pure Kohn-Sham density functional. The machine learned RPA model (ML-RPA) is a nonlocal extension of the standard gradient approximation. The density descriptors used as ingredients for the enhancement factor are nonlocal counterparts of the local density and its gradient. Rather than fitting only RPA exchange-correlation energies, we also include derivative information in the form of RPA optimized effective potentials. We train a single ML-RPA functional for diamond, its surfaces, and liquid water. The accuracy of ML-RPA for the formation energies of 28 diamond surfaces reaches that of state-of-the-art van der Waals functionals. For liquid water, however, ML-RPA cannot yet improve upon the standard gradient approximation. Overall, our work demonstrates how machine learning can extend the applicability of the RPA to larger system sizes, time scales, and chemical spaces.

Minimum Free-Energy Shapes of Ag Nanocrystals: Vacuum vs Solution

We use two variants of replica-exchange molecular dynamics (MD) simulations, parallel tempering MD and partial replica exchange MD, to probe the minimum free-energy shapes of Ag nanocrystals containing 100-200 atoms in a vacuum, ethylene glycol (EG) solvent, and EG solvent with a PVP polymer containing 100 repeat units. Our simulations reveal a shape intermediate between a Dh and an Ih, a Dh-Ih, that has distinct structural signatures and magic sizes. We find several prominent features associated with entropy: pure FCC nanocrystals are less common than FCC crystals containing stacking faults, and crystals with the minimum potential energy are not always preferred over the range of relevant temperatures. The shapes of the nanocrystals in solution are influenced by the chemical identities of the solution-phase molecules. Comparing Ag nanocrystal shapes in EG to those in an EG+PVP solution, we find more icosahedra in EG and more decahedra in EG+PVP across all of the nanocrystal sizes probed in this study. At certain critical sizes, nanocrystal shapes can change dramatically with the addition and removal of a single atom or with a change in temperature at a fixed size. The information in our study could be useful in efforts to devise processing routes to achieve selective nanocrystal shapes.

Prediction of the Effective Work Function of Aspirin and Paracetamol Crystals by Density Functional Theory-A First-Principles Study

Crystals of active pharmaceutical ingredients (API) are prone to triboelectric charging due to their dielectric nature. This characteristic, coupled with their typically low density and often large aspect ratio, poses significant challenges in the manufacturing process. The pharmaceutical industry frequently encounters issues during the secondary processing of APIs, such as particle adhesion to walls, clump formation, unreliable flow, and the need for careful handling to mitigate the risk of fire and explosions. These challenges are further intensified by the limited availability of powder quantities for testing, particularly in the early stages of drug development. Therefore, it is highly desirable to develop predictive tools that can assess the triboelectric propensity of APIs. In this study, Density Functional Theory calculations are employed to predict the effective work function of different facets of aspirin and paracetamol crystals, both in a vacuum and in the presence of water molecules on their surfaces. The calculations reveal significant variations in the work function across different facets and materials. Moreover, the adsorption of water molecules induces a shift in the work function. These findings underscore the considerable impact of distinct surface terminations and the presence of molecular water on the calculated effective work function of pharmaceuticals. Consequently, this approach offers a valuable predictive tool for determining the triboelectric propensity of APIs.

High-Throughput First-Principles Prediction of Interfacial Adhesion Energies in Metal-on-Metal Contacts

Adhesion energy, a measure of the strength by which two surfaces bind together, ultimately dictates the mechanical behavior and failure of interfaces. As natural and artificial solid interfaces are ubiquitous, adhesion energy represents a key quantity in a variety of fields ranging from geology to nanotechnology. Because of intrinsic difficulties in the simulation of systems where two different lattices are matched, and despite their importance, no systematic, accurate first-principles determination of heterostructure adhesion energy is available. We have developed robust, automatic high-throughput workflow able to fill this gap by systematically searching for the optimal interface geometry and accurately determining adhesion energies. We apply it here for the first time to perform the screening of around a hundred metallic heterostructures relevant for technological applications. This allows us to populate a database of accurate values, which can be used as input parameters for macroscopic models. Moreover, it allows us to benchmark commonly used, empirical relations that link adhesion energies to the surface energies of its constituent and to improve their predictivity employing only quantities that are easily measurable or computable.

Molecular Insights into the Effect of Crystal Planes on Droplet Wetting

Dynamic wetting by liquids on solid surfaces depends on several aspects such as surface energy, roughness, and interfacial tension, among many others. Copper (Cu), gold (Au), aluminum (Al), and silicon (Si) are a few of the most important metals that are used extensively as substrates in various industrial and biomedical applications. Metals are etched frequently on different crystal planes for fabrication purposes. Etching exposes distinct crystal planes that may come in contact with the liquids when used for different applications. The interaction of the crystal planes with the liquid that comes in contact with the solid dictates the wetting behavior of the surface. This necessitates the importance of understanding how various crystal planes of the same metals behave under similar conditions. Herein, three specific crystal planes, namely, (1 0 0), (1 1 0), and (1 1 1), are investigated at a molecular scale for the above-mentioned metals. The dynamic contact angle and contact diameter trends revealed that the relatively hydrophobic surfaces (Cu, Si) tend to reach their equilibrium contact angle faster compared to the hydrophilic substrates (Al, Au). Molecular kinetic theory is used to estimate the three-phase contact line friction which is found to be higher for (1 1 1) planes. Further, a consistent potential energy distribution variation is observed for the crystal lattice of (1 0 0), (1 1 0), and (1 1 1). These findings can be used as a guideline to determine the factors needed to completely describe a dynamic wetting phenomenon of the droplet over the different crystal planes. The understanding will be of great use in deciding experimental strategies where fabricated different crystal planes would be required to have a liquid contact.

Performance of Screened-Exchange Functionals for Band Gaps and Lattice Constants of Crystals

Kohn-Sham density functional theory is the most widely used method for electronic structure calculations of solid-state systems. The screened-exchange functionals developed following the influential work of Scuseria and co-workers in 2003-2006 have significantly improved the accuracy of the predictions of solid-state properties. This work assesses six screened-exchange density functionals for the prediction of 60 band gaps (database BG60) and 68 lattice constants (database LC68). The band gaps are calculated with both consistently calculated lattice constants and experimental lattice constants. Results for the nonlocal screened-exchange functionals are compared with those for six widely used or recently developed local functionals. The results show that all the screened-exchange functionals have smaller mean absolute errors (MAEs) than any of the local functionals. All the functionals except HLE17 overestimate (on average) the lattice constants, and M06-SX gives the best performance among the compared functionals, with a MAE of 0.051 Å. All the functionals underestimate (on average) the band gaps, and M06-SX outperforms all other functionals, with a MAE of 0.47 eV. M06-SX also has the lowest root-mean-squared error for both LC68 and BG60. For the subdatabases of BG60, M06-SX shows better performance for ionic crystals and systems with large band gaps, while HSE12s gives better results for semiconductors and systems with small band gaps. Overall, M06-SX shows the best performance for solid-state systems, followed by N12-SX and HSE12s. The best-performing local functionals are M06-L, revM06-L, and HLE17 for band gaps and M06-L and revM06-L for lattice constants. We found that M06-SX, revM06-L, and N12-SX not only are well optimized for a broad array of chemical properties but also have very good performance for the databases in this paper, making them well-suited for applications involving heterogeneous chemistry.

SBH17: Benchmark Database of Barrier Heights for Dissociative Chemisorption on Transition Metal Surfaces

Accurate barriers for rate controlling elementary reactions on metal surfaces are key to understanding, controlling, and predicting the rate of heterogeneously catalyzed processes. While barrier heights for gas phase reactions have been extensively benchmarked, dissociative chemisorption barriers for the reactions of molecules on metal surfaces have received much less attention. The first database called SBH10 and containing 10 entries was recently constructed based on the specific reaction parameter approach to density functional theory (SRP-DFT) and experimental results. We have now constructed a new and improved database (SBH17) containing 17 entries based on SRP-DFT and experiments. For this new SBH17 benchmark study, we have tested three algorithms (high, medium, and light) for calculating barrier heights for dissociative chemisorption on metals, which we have named for the amount of computational effort involved in their use. We test the performance of 14 density functionals at the GGA, GGA+vdW-DF, and meta-GGA rungs. Our results show that, in contrast with the previous SBH10 study where the BEEF-vdW-DF2 functional seemed to be most accurate, the workhorse functional PBE and the MS2 density functional are the most accurate of the GGA and meta-GGA functionals tested. Of the GGA+vdW functionals tested, the SRP32-vdW-DF1 functional is the most accurate. Additionally, we found that the medium algorithm is accurate enough for assessing the performance of the density functionals tested, while it avoids geometry optimizations of minimum barrier geometries for each density functional tested. The medium algorithm does require metal lattice constants and interlayer distances that are optimized separately for each functional. While these are avoided in the light algorithm, this algorithm is found not to give a reliable description of functional performance. The combination of relative ease of use and demonstrated reliability of the medium algorithm will likely pave the way for incorporation of the SBH17 database in larger databases used for testing new density functionals and electronic structure methods.

Anionic Flow Valve Across Oxide Heterointerfaces by Remote Electron Doping

As an analogue of charged electron flows, the ionic flow could be controlled by the electronic band alignment due to the ambipolar nature of diffusion in the ionic crystal. Here, we demonstrate the active control of the anionic diffusion across heterointerfaces through remote electron doping in the capping layers. In contrast to the spontaneous ionic flux from the underlying VO₂ layers to the undoped TiO₂ capping layers, the activated Nb dopants in the TiO₂ capping layers substantially restrict the ionic flux, despite identical growth conditions. The increase of Fermi level by Nb donors in TiO₂ prevents electron flux from being generated across the interfaces by the heightening of a Schottky barrier; this electron shortage generates a kinetic close valve for the flow of negatively charged oxygen ions. Thus, these results demonstrate the importance of electron supply on charged ionic flow, thereby suggesting an unprecedented strategy for ionic-defect-induced emergent properties at interfaces.

Mapping the Binding Energy of Layered Crystals to Macroscopic Observables

Van der Waals (vdW) integration of two dimensional (2D) crystals into functional heterostructures emerges as a powerful tool to design new materials with fine-tuned physical properties at an unprecedented precision. The intermolecular forces governing the assembly of vdW heterostructures are investigated by first-principles models, yet translating the outcome of these models to macroscopic observables in layered crystals is missing. Establishing this connection is, therefore, crucial for ultimately designing advanced materials of choice-tailoring the composition to functional device properties. Herein, components from both vdW and non-vdW forces are integrated to build a comprehensive framework that can quantitatively describe the dynamics of these forces in action. Specifically, it is shown that the optical band gap of layered crystals possesses a peculiar ionic character that works as a quantitative indicator of non-vdW forces. Using these two components, it is then described why only a narrow range of exfoliation energies for this class of materials is observed. These findings unlock the microscopic origin of universal binding energy in layered crystals and provide a general protocol to identify and synthesize new crystals to regulate vdW coupling in the next generation of heterostructures.

Efficient and improved prediction of the band offsets at semiconductorheterojunctions from meta-GGA density functionals: a benchmark study

Accurate theoretical prediction of the band offsets at interfaces of semiconductor heterostructures can of-ten be quite challenging. Although density functional theory has been reasonably successful to carry outsuch calculations and efficient and accurate semilocal functionals are desirable to reduce the computational cost. In general, the semilocal functionals based on the generalized gradient approximation (GGA) significantly underestimate the bulk band gaps. This, in turn, results in inaccurate estimates of the band offsets at the heterointerfaces. In this paper, we investigate the performance of several advanced meta-GGA functionals in the computational prediction of band offsets at semiconductor heterojunctions. In particular, we investigate the performance of r 2 SCAN (revised strongly-constrained and appropriately-normed functional), rMGGAC (revised semilocal functional based on cuspless hydrogen model and Pauli kinetic energy density functional), mTASK (modified Aschebrock and Kümmel meta-GGA functional), and LMBJ (local modified Becke-Johnson) exchange-correlation functionals. Our results strongly suggest that these meta-GGA functionals for supercell calculations perform quite well, especially, when compared to computationally more demanding GW calculations. We also present band offsets calculated using ionization potentials and electron affinities, as well as band alignment via the branch point energies. Overall, our study shows that the aforementioned meta-GGA functionals can be used within the DFT framework to estimate the band offsets in semiconductor heterostructures with predictive accuracy.

Elucidating the Initial Steps in α-Uranium Hydriding Using First-Principles Calculations

Hydrogen embrittlement of uranium, which arises due to the formation of a structurally weak pyrophoric hydride, poses a major safety risk in material applications. Previous experiments have shown that hydriding begins on the top or near the surface (i.e., subsurface) of α-uranium. However, the fundamental molecular-level mechanism of this process remains unknown. In this work, starting from pristine α-U bulk and surfaces, we present a systematic investigation of possible mechanisms for the formation of metal hydride. Specifically, we address this problem by examining the individual steps of hydrogen embrittlement, including surface adsorption, subsurface absorption, and the interlayer diffusion of atomic hydrogen. Furthermore, by examining these processes across different facets, we highlight the importance of both (1) hydrogen monolayer coverage and (2) applied tensile strain on hydriding kinetics. Taken together, by studying previously overlooked phenomena, this study provides foundational insights into the initial steps of this overall complex process. We anticipate that this work will guide near-term future development of multiscale kinetic models for uranium hydriding and subsequently identify potential strategies to mitigate this undesired process.

Solid-state performance of a meta-GGA screened hybrid density functional constructed from Pauli kinetic enhancement factor dependent semilocal exchange hole

The semilocal form of the exchange hole is highly useful in developing non-local range-separated hybrid density functionals for finite and extended systems. The way to construct the conventional exact exchange hole model is based on either the Taylor series expansion or the reverse engineering technique from the corresponding exchange energy functional. Although the latter technique is quite popular in context of generalized gradient approximation (GGA) functionals, the same for the meta-GGA functionals is not so much explored. Thus, in this study, we propose a reverse-engineered semilocal exchange hole of a meta-GGA functional, that depends only on the meta-GGA ingredient α (also known as the Pauli kinetic energy enhancement factor). The model is used subsequently to design the short-range-separated meta-GGA hybrid density functional. We show that the present method can be successfully applied for several challenging problems in the context of solids, especially for which the GGA based hybrid fails drastically. This assessment proves that the present functional is quite useful for materials sciences. Finally, we also use this method for several molecular test cases, where the results are also as comparative as its base semilocal functional.

A computational study of direct CO2 hydrogenation to methanol on Pd surfaces

The reaction mechanism of direct CO₂ hydrogenation to methanol is investigated in detail on Pd (111), (100) and (110) surfaces using density functional theory (DFT), supporting investigations into emergent Pd-based catalysts. Hydrogen adsorption and surface mobility are firstly considered, with high-coordination surface sites having the largest adsorption energy and being connected by diffusion channels with low energy barriers. Surface chemisorption of CO₂, forming a partially charged CO₂^δ-, is weakly endothermic on a Pd (111) whilst slightly exothermic on Pd (100) and (110), with adsorption enthalpies of 0.09, -0.09 and -0.19 eV, respectively; the low stability of CO₂^δ- on the Pd (111) surface is attributed to negative charge accumulating on the surface Pd atoms that interact directly with the CO₂^δ- adsorbate. Detailed consideration for sequential hydrogenation of the CO₂ shows that HCOOH hydrogenation to H₂COOH would be the rate determining step in the conversion to methanol, for all surfaces, with activation barriers of 1.41, 1.51, and 0.84 eV on Pd (111), (100) and (110) facets, respectively. The Pd (110) surface exhibits overall lower activation energies than the most studied Pd (111) and (100) surfaces, and therefore should be considered in more detail in future Pd catalytic studies.

Best practices for first-principles simulations of epitaxial inorganic interfaces

At an interface between two materials physical properties and functionalities may be achieved, which would not exist in either material alone. Epitaxial inorganic interfaces are at the heart of semiconductor, spintronic, and quantum devices. First principles simulations based on density functional theory (DFT) can help elucidate the electronic and magnetic properties of interfaces and relate them to the structure and composition at the atomistic scale. Furthermore, DFT simulations can predict the structure and properties of candidate interfaces and guide experimental efforts in promising directions. However, DFT simulations of interfaces can be technically elaborate and computationally expensive. To help researchers embarking on such simulations, this review covers best practices for first principles simulations of epitaxial inorganic interfaces, including DFT methods, interface model construction, interface structure prediction, and analysis and visualization tools.

Alteration of Electronic Band Structure via a Metal-Semiconductor Interfacial Effect Enables High Faradaic Efficiency for Electrochemical Nitrogen Fixation

The interface engineering strategy has been an emerging field in terms of material improvisation that not only alters the electronic band structure of a material but also induces beneficial effects on electrochemical performances. Particularly, it is of immense importance for the environmentally benign electrochemical nitrogen reduction reaction (NRR), which is potentially impeded by the competing hydrogen evolution reaction (HER). The main problem lies in the attainment of the desired current density at a negotiable potential where the NRR would dominate over the HER, which in turn hampers the Faradaic efficiency for the NRR. To circumvent this issue, catalyst development becomes necessary, which would display a weak affinity for H-adsorption suppressing the HER at the catalyst surface. Herein, we have adopted the interfacial engineering strategy to synthesize our electrocatalyst NPG@SnS₂, which not only suppressed the HER on the active site but yielded 49.3% F.E. for the NRR. Extensive experimental work and DFT calculations regarded that due to the charge redistribution, the Mott-Schottky effect, and the band bending of SnS₂ across the contact layer at the interface of NPG, the d-band center for the surface Sn atoms in NPG@SnS₂ lowered, which resulted in favored adsorption of N₂ on the Sn active site. This phenomenon was driven even forward by the upshift of the Fermi level, and eventually, a decrease was seen in the work function of the heterostructure that increased the conductivity of the material as compared to pristine SnS₂. This strategy thus provides a field to methodically suppress the HER in the realm of improving the Faradaic efficiency for the NRR.

Towards tuning the modality of hierarchical macro-nanoporous metals by controlling the dealloying kinetics of close-to-eutectic alloys

Largely inspired by nature, hierarchical porous materials are attractive for a wide range of applications as they provide a unique combination of transport and interfacial properties. Hierarchical macro-nanoporous metals (HMNPM) are of particular interest due to their high thermal and electrical conductivities, high volumetric macroporosity as well as their strong capillary forces, and large surface area due to their nanopores. However, tuning the porosity of HMNPMs remains challenging and often requires complex multi-step synthesis methods. Here we demonstrate that controlling the dealloying kinetics of close-to-eutectic alloys allows the selective tuning of the porosity of a hierarchical metal from tens of nanometers to hundreds of micrometers. This was demonstrated by dealloying the Cu-Mg-Zn alloy of close-to-eutectic composition to develop trimodal hierarchical macro-nanoporous copper with an impressive porosity of 94 vol% in the form of macroscopic self-supporting bulk samples. A combination of dealloying experiments and density functional theory calculations indicate that while selective corrosion of chemical phases in the Cu-Mg-Zn alloy is triggered according to their Volta potential, the kinetics can be altered by confinement and non-homogeneity effects. The obtained insights into the kinetics of close-to-eutectic alloy dealloying can be used to develop other hierarchical porous metals with tunable porosity and controlled shape.

vdW-DF-ahcx: a range-separated van der Waals density functional hybrid

Hybrid density functionals replace a fraction of an underlying generalized-gradient approximation (GGA) exchange description with a Fock-exchange component. Range-separated hybrids (RSHs) also effectively screen the Fock-exchange component and thus open the door for characterizations of metals and adsorption at metal surfaces. The RSHs are traditionally based on a robust GGA, such as PBE (Perdew J Pet al1996Phys. Rev. Lett.773865), for example, as implemented in the HSE design (Heyd Jet al2003J. Chem. Phys.1188207). Here we define an analytical-hole (Henderson T Met al2008J. Chem. Phys.128194105) consistent-exchange RSH extension to the van der Waals density functional (vdW-DF) method (Berland Ket al2015Rep. Prog. Phys.78066501), launching vdW-DF-ahcx. We characterize the GGA-type exchange in the vdW-DF-cx version (Berland K and Hyldgaard P 2014Phys. Rev. B89035412), isolate the short-ranged exchange component, and define the new vdW-DF hybrid. We find that the performance vdW-DF-ahcx compares favorably to (dispersion-corrected) HSE for descriptions of bulk (broad molecular) properties. We also find that it provides accurate descriptions of noble-metal surface properties, including CO adsorption.

Molecular electronics behaviour of L-aspartic acid using symmetrical metal electrodes

Protein-based electronics is one of the growing areas of bio-nanoelectronics, where novel electronic devices possessing distinctive properties are being fabricated using specific proteins. Furthermore, if the bio-molecule is analysed amidst different electrodes, intriguing properties are elucidated. This research article investigates the electron transport properties of L-aspartic acid (i.e. L-amino acid) bound to symmetrical electrodes of gold, silver, copper, platinum and palladium employing NEGF-DFT approach using self-consistent function. The theoretical work function of different electrodes is calculated using local density approximation and generalized gradient approximation approach. The calculated work function correlates well with the hole tunneling barrier and conductance of the molecular device, which further authenticate the coupling strength between molecule and electrode. Molecule under consideration also exhibits negative differential resistance region and rectification ratio with all the different electrodes, due to its asymmetrical structure. The molecular device using platinum electrodes exhibits the highest peak to valley ratio of 1.38 and rectification ratio of 3.20, at finite bias. The switching characteristics of different molecular device are justified with detailed transmission spectra and MPSH. These results indicate that L-aspartic acid and similar biomolecule can be vital to the growth of Proteotronics.

Benchmark test of a dispersion corrected revised Tao-Mo semilocal functional for thermochemistry, kinetics, and noncovalent interactions of molecules and solids

In the density functional theory, dispersion corrected semilocal approximations are often used to benchmark weekly interacting finite and extended systems. Here, the focus is on providing a broad overview of the performance of D3 dispersion corrected revised Tao-Mo (revTM) semilocal functionals [A. Patra et al., J. Chem. Phys. 153, 084 117 (2020)] for thermochemistry and kinetics of molecules, molecular crystals, ice polymorphs, metal-organic systems, atom/molecular adsorption on solids, water interacting with nano-materials, binding energies of layered materials, and properties of weekly and strongly bonded solids. We show that the most suitable "optimized power" function for the revTM functional needs a modification to make it suitable for properties related to the diverse nature of finite and extended systems. The present work is an extension of the previously proposed revTM+D3 method with the motivation to design and benchmark the dispersion corrected cost-effective method based on this semilocal approximation. We show that the revised revTM+D3 functional provides various general purpose molecular and solid properties with the closest to experimental findings than its predecessor. The present assessment and benchmarking can be practically useful for performing cost-effective method based simulations of various molecular and solid-state properties.

Accurate density functional made more versatile

We propose a one-electron self-interaction-free correlation energy functional compatible with the order-of-limit problem-free Tao-Mo (TM) semilocal functional (regTM) [J. Tao and Y. Mo, Phys. Rev. Lett. 117, 073001 (2016) and Patra et al., J. Chem. Phys. 153, 184112 (2020)] to be used for general purpose condensed matter physics and quantum chemistry. The assessment of the proposed functional for large classes of condensed matter and chemical systems shows its improvement in most cases compared to the TM functional, e.g., when applied to the relative energy difference of MnO₂ polymorphs. In this respect, the present exchange-correction functional, which incorporates the TM technique of the exchange hole model combined with the slowly varying density correction, can achieve broad applicability, being able to solve difficult solid-state problems.

Evaluation of Force Fields for Molecular Dynamics Simulations of Platinum in Bulk and Nanoparticle Forms

Understanding the size- and shape-dependent properties of platinum nanoparticles is critical for enabling the design of nanoparticle-based applications with optimal and potentially tunable functionality. Toward this goal, we evaluated nine different empirical potentials with the purpose of accurately modeling faceted platinum nanoparticles using molecular dynamics simulation. First, the potentials were evaluated by computing bulk and surface properties-surface energy, lattice constant, stiffness constants, and the equation of state-and comparing these to prior experimental measurements and quantum mechanics calculations. Then, the potentials were assessed in terms of the stability of cubic and icosahedral nanoparticles with faces in the {100} and {111} planes, respectively. Although none of the force fields predicts all the evaluated properties with perfect accuracy, one potential-the embedded atom method formalism with a specific parameter set-was identified as best able to model platinum in both bulk and nanoparticle forms.

Study of the Rate-Determining Step of Rh Catalyzed CO2 Reduction: Insight on the Hydrogen Assisted Molecular Dissociation

In the context of climate change mitigation, CO2 methanation is an important option for the production of synthetic carbon-neutral fuels and for atmospheric CO2 recycling. While being highly exothermic, this reaction is kinetically unfavorable, requiring a catalyst to be efficiently activated. Recently Rh nanoparticles gained attention as effective photocatalyst, but the rate-determining step of this reaction on Rh surface has not been characterized yet. In this work, Density Functional Theory and Nudged Elastic Band calculations were performed to study the Rh-catalyzed rate-determining step of the CO2 methanation, which concerns the hydrogen assisted cleavage of the CO* molecule and subsequent formation of CH* and O* (* marks adsorbed species), passing through the CHO* key intermediate. The configurations of the various adsorbates on the Rh (100) surface were investigated and the reaction mechanism was studied exploiting different exchange-correlation functionals (PBE, RPBE) and the PBE+U technique. The methanation rate-determining step consists of two subprocesses which subsequently generate and dissociate the CHO* species. The energetics and the dynamics of such processes are extensively studied and described. Interestingly, PBE and PBE+U calculated activation barriers are in good agreement with the available experimental data, while RPBE largely overestimate the CHO* dissociation barrier.

Alkaline earth atom doping-induced changes in the electronic and magnetic properties of graphene: a density functional theory study

Density functional theory was used to investigate the effects of doping alkaline earth metal atoms (beryllium, magnesium, calcium and strontium) on graphene. Electron transfer from the dopant atom to the graphene substrate was observed and was further probed by a combined electron localization function/non-covalent interaction (ELF/NCI) approach. This approach demonstrates that predominantly ionic bonding occurs between the alkaline earth dopants and the substrate, with beryllium doping having a variant characteristic as a consequence of electronegativity equalization attributed to its lower atomic number relative to carbon. The ionic bonding induces spin-polarized electronic structures and lower workfunctions for Mg-, Ca-, and Sr-doped graphene systems as compared to the pristine graphene. However, due to its variant bonding characteristic, Be-doped graphene exhibits non-spin-polarized p-type semiconductor behavior, which is consistent with previous works, and an increase in workfunction relative to pristine graphene. Dirac half-metal-like behavior was predicted for magnesium doped graphene while calcium doped and strontium doped graphene were predicted to have bipolar magnetic semiconductor behavior. These changes in the electronic and magnetic properties of alkaline earth doped graphene may be of importance for spintronic and other electronic device applications.

Theoretical understanding of the properties of stepped iron surfaces with van der Waals interaction corrections

The stepped surfaces in nanoscale zero-valent iron (nZVI) play an essential role for environmental application. However, there is still currently a deficiency in the atomic understanding of stepped surface properties due to the limitation of the computational methodology. In this study, stepped Fe(210) and (211) surfaces were theoretically investigated using density functional theory (DFT) computations in terms of the flat Fe(110) surface. Our results suggest that the consideration of van der Waals (vdW) interaction correction is beneficial for the DFT study on Fe-based systems. The DF-cx method is found to be the most promising vdW correction method. The DF-cx results reveal that the stepped Fe(210) and Fe(211) surfaces experience significant surface relaxation and abnormal trends in their work function. Their electronic properties and reactivities of the surface atoms are strongly affected by the Fe coordination numbers and the strong adsorption strengths of oxygen on the surfaces are dependent on both the coordination number of the adsorbed atoms and the geometry of the adsorption sites.

A computational study of the properties of low- and high-index Pd, Cu and Zn surfaces

We report a detailed Density Functional Theory (DFT) based investigation of the structure and stability of bulk and surface structures for the Group 10-12 elements Pd, Cu and Zn, considering the effect of the choice of exchange-correlation density functional and computation parameters. For the initial bulk structures, the lattice parameter and cohesive energy are calculated, which are then augmented by calculation of surface energies and work functions for the lower-index surfaces. Of the 22 density functionals considered, we highlight the mBEEF density functional as providing the best overall agreement with experimental data. The optimal density functional choice is applied to the study of higher index surfaces for the three metals, and Wulff constructions performed for nanoparticles with a radius of 11 nm, commensurate with nanoparticle sizes commonly employed in catalytic chemistry. For Pd and Cu, the low-index (111) facet is dominant in the constructed nanoparticles, covering ∼50% of the surface, with (100) facets covering a further 10 to 25%; however, non-negligible coverage from higher index (332), (332) and (210) facets is also observed for Pd, and (322), (221) and (210) surfaces are observed for Cu. In contrast, only the (0001) and (10-10) facets are observed for Zn. Overall, our results highlight the need for careful validation of computational settings before performing extensive density functional theory investigations of surface properties and nanoparticle structures of metals.

A high-throughput assessment of the adsorption capacity and Li-ion diffusion dynamics in Mo-based ordered double-transition-metal MXenes as anode materials for fast-charging LIBs

Utilizing the latest SCAN-rVV10 density functional, we thoroughly assess the electrochemical properties of 35 Mo-based ordered double transition metal MXenes, including clean Mo2MC2 (M = Sc, Ti, V, Zr, Nb, Hf, Ta) and surface functionalized structures Mo2MC2T2 (T = H, O, F and OH), for the potential use as anode materials in lithium ion batteries (LIBs). The first principles molecular dynamics simulations in combination with the calculations of the site adsorption preferences for Li atoms on all investigated MXenes reveal that both Li-saturated adsorption structures and theoretical capacities of Mo-based MXenes are fundamentally influenced by the surface terminations. We find that the adsorption of Li atoms on either -OH or -F functionalized MXenes is chemically unstable. In particular, the F-groups prefer to form a separate fluoride layer with Li atoms, detaching from the Mo2MC2 substrates. The Li atoms could form a stable single adsorption layer on the -H, -O and intrinsic MXenes surface, exhibiting theoretical capacities in the range from 121 mA h g-1 to 195 mA h g-1. Besides -F and -OH terminations, the remaining Mo-based MXenes also possess superior flat open circuit voltage (OCV) profiles with the most reversible storage capacity below 1.0 V during the charging/discharging cycles. We further predict the low barrier heights of Li-ion diffusion, at a range of 0.03-0.06 eV for most Mo-based MXenes except -O and -H terminations, exceeding that of graphene or Ti3C2. Furthermore, combining the Vineyard transition state theory (TST) with the phonon spectra obtained from density functional perturbation theory (DFPT), the mean planar diffusion coefficient is calculated to be 2 × 10-8 m2 s-1 at 300 K for intrinsic Mo2MC2 monolayers. Although the overall specific capacity is fundamentally restricted with the relatively heavy molecular mass of MXenes, we conclude that Mo-based structures, especially the intrinsic Mo2MC2 (M = Sc, Ti, V) monolayers, might be promising anode materials from the aspect of fast charging/discharging application for LIBs.

Designing new SRP density functionals including non-local vdW-DF2 correlation for H2 + Cu(111) and their transferability to H2 + Ag(111), Au(111) and Pt(111)

Specific reaction parameter density functionals (SRP-DFs) that can describe dissociative chemisorption molecular beam experiments of hydrogen (H₂) on cold transition metal surfaces with chemical accuracy have so far been shown to be only transferable among different facets of the same metal, but not among different metals. We design new SRP-DFs that include non-local vdW-DF2 correlation for the H₂ + Cu(111) system, and evaluate their transferability to the highly activated H₂ + Ag(111) and H₂ + Au(111) systems and the non-activated H₂ + Pt(111) system. We design our functionals for the H₂ + Cu(111) system since it is the best studied system both theoretically and experimentally. Here we demonstrate that a SRP-DF fitted to reproduce molecular beam sticking experiments for H₂ + Cu(111) with chemical accuracy can also describe such experiments for H₂ + Pt(111) with chemical accuracy, and vice versa. Chemically accurate functionals have been obtained that perform very well with respect to reported van der Waals well geometries, and which improve the description of the metal over current generalized gradient approximation (GGA) based SRP-DFs. From a systematic comparison of our new SRP-DFs that include non-local correlation to previously developed SRP-DFs, for both activated and non-activated systems, we identify non-local correlation as a key ingredient in the construction of transferable SRP-DFs for H₂ interacting with transition metals. Our results are in excellent agreement with experiment when accurately measured observables are available. It is however clear from our analysis that, except for the H₂ + Cu(111) system, there is a need for more, more varied, and more accurately described experiments in order to further improve the design of SRP-DFs. Additionally, we confirm that, when including non-local correlation, the sticking of H₂ on Cu(111) is still well described quasi-classically.

Pseudo-2-Fold Surface of the Al13Co4 Catalyst: Structure, Stability, and Hydrogen Adsorption

A few low-order approximants to decagonal quasicrystals have been shown to provide excellent activity and selectivity for the hydrogenation of alkenes and alkynes. It is the case for the Al₁₃Co₄ compound, for which the catalytic properties of the pseudo-2-fold orientation have been revealed to be among the best. A combination of surface science studies, including surface X-ray diffraction, and calculations based on density functional theory is used here to derive an atomistic model for the pseudo-2-fold o-Al₁₃Co₄ surface, whose faceted and columnar structure is found very similar to the one of the 2-fold surface of the d-Al-Ni-Co quasicrystal. Facets substantially stabilize the system, with energies in the range 1.19-1.31 J/m², i.e., much smaller than the ones of the pseudo-10-fold (1.49-1.68 J/m²) and pseudo-2-fold (1.66 J/m²) surfaces. Faceting is also a main factor at the origin of the Al₁₃Co₄ catalytic performances, as illustrated by the comparison of the pseudo-10-fold, pseudo-2-fold and facet potential energy maps for hydrogen adsorption. This work gives insights toward the design of complex intermetallic catalysts through surface nanostructuration for optimized catalytic performances.

Screening nature of the van der Waals density functional method: a review and analysis of the many-body physics foundation

We review the screening nature and many-body physics foundation of the van der Waals density functional (vdW-DF) method [Berland Ket al2015Rep. Prog. Phys.78066501], a systematic approach to construct truly nonlocal exchange-correlation energy density functionals. To that end we define and focus on a class of consistent vdW-DF versions that adhere to the Lindhard screening logic of the full method formulation. The consistent-exchange vdW-DF-cx version [Berland K and Hyldgaard P 2014Phys. Rev. B89035412] and its spin extension [Thonhauser Tet al2015Phys. Rev. Lett.115136402] represent the first examples of this class; in general, consistent vdW-DFs reflect a concerted expansion of a formal recast of the adiabatic-connection formula [Hyldgaard Pet al2014Phys. Rev. B90075148], an exponential summation of contributions to the local-field response, and the Dyson equation. We argue that the screening emphasis is essential because the exchange-correlation energy reflects an effective electrodynamics set by a long-range interaction. Two consequences are that (1) there are, in principle, no wiggle room in how one balances exchange and correlation, for example, in vdW-DF-cx, and that (2) consistent vdW-DFs have a formal structure that allows them to incorporate vertex-correction effects, at least in the case of levels that experience recoil-less interactions (for example, near the Fermi surface). We explore the extent to which the strictly nonempirical vdW-DF-cx formulation can serve as a systematic extension of the constraint-based semilocal functionals. For validation, we provide a complete survey of vdW-DF-cx performance for broad molecular processes, for the full set of 55 benchmarks in GMTKN55 [Goerigk Let al2017Phys. Chem. Chem. Phys.1932184] and comparing to the quantum-chemistry calculations that are summarized in that paper. We also provide new vdW-DF-cx results for metal surface energies and work functions that we compare to experiment. Finally, we use the screening insight to separate the vdW-DF nonlocal-correlation term into pure-vdW-interaction and local-field-susceptibility effects and present tools to compute and map the binding signatures.

Topological Dirac Semimetal Phase in Bismuth Based Anode Materials for Sodium-Ion Batteries

Bismuth has recently attracted interest in connection with Na-ion battery anodes due to its high volumetric capacity. It reacts with Na to form Na 3 Bi which is a prototypical Dirac semimetal with a nontrivial electronic structure. Density-functional-theory based first-principles calculations are playing a key role in understanding the fascinating electronic structure of Na 3 Bi and other topological materials. In particular, the strongly-constrained-and-appropriately-normed (SCAN) meta-generalized-gradient-approximation (meta-GGA) has shown significant improvement over the widely used generalized-gradient-approximation (GGA) scheme in capturing energetic, structural, and electronic properties of many classes of materials. Here, we discuss the electronic structure of Na 3 Bi within the SCAN framework and show that the resulting Fermi velocities and s-band shift around the Γ point are in better agreement with experiments than the corresponding GGA predictions. SCAN yields a purely spin-orbit-coupling (SOC) driven Dirac semimetal state in Na 3 Bi in contrast with the earlier GGA results. Our analysis reveals the presence of a topological phase transition from the Dirac semimetal to a trivial band insulator phase in Na 3 Bi x Sb 1 − x alloys as the strength of the SOC varies with Sb content, and gives insight into the role of the SOC in modulating conduction properties of Na 3 Bi.

Ab initio Description of Bond Breaking in Large Electric Fields

Strong (10^{10}  V/m) electric fields capable of inducing atomic bond breaking represent a powerful tool for surface chemistry. However, their exact effects are difficult to predict due to a lack of suitable tools to probe their associated atomic-scale mechanisms. Here we introduce a generalized dipole correction for charged repeated-slab models that controls the electric field on both sides of the slab, thereby enabling direct theoretical treatment of field-induced bond-breaking events. As a prototype application, we consider field evaporation from a kinked W surface. We reveal two qualitatively different desorption mechanisms that can be selected by the magnitude of the applied field.