Concepts, models, and methods in computational heterogeneous catalysis illustrated through CO 2 conversion

Single-Atom-Based Nanoenzyme in Tissue Repair

Since the discovery of ferromagnetic nanoparticles Fe3O4 that exhibit enzyme-like activity in 2007, the research on nanoenzymes has made significant progress. With the in-depth study of various nanoenzymes and the rapid development of related nanotechnology, nanoenzymes have emerged as a promising alternative to natural enzymes. Within nanozymes, there is a category of metal-based single-atom nanozymes that has been rapidly developed due to low cast, convenient preparation, long storage, less immunogenicity, and especially higher efficiency. More importantly, single-atom nanozymes possess the capacity to scavenge reactive oxygen species through various mechanisms, which is beneficial in the tissue repair process. Herein, this paper systemically highlights the types of metal single-atom nanozymes, their catalytic mechanisms, and their recent applications in tissue repair. The existing challenges are identified and the prospects of future research on nanozymes composed of metallic nanomaterials are proposed. We hope this review will illuminate the potential of single-atom nanozymes in tissue repair, encouraging their sequential clinical translation.

Level-Shifted Embedded Cluster Method for Modeling the Chemistry of Metal Oxides

The embedded cluster method has been used extensively in the study of the chemical and physical properties of metal oxides. This method has been a popular tool due to its relatively high accuracy and low computational cost. An even more promising option may entail integrating the embedded cluster method with the combined quantum mechanical and molecular mechanical (QM/MM) approach, thereby enabling further consideration of interactions within the entire system for superior results. We aim to accurately model the chemistry of metal oxides using this combined scheme. Here, using the prototypical MgO(100) surface as a test system, with Mg9O14 as the cluster in the quantum mechanical region, we show that the embedded cluster with untailored boundary effective core potentials (ECPs) can have frontier orbital energy levels that substantially deviate from the quantum mechanical reference results. This occurs even when Mg9O9, which retains the stoichiometry of MgO, is used as the cluster in the quantum mechanical region. As a result, the chemical properties of the embedded cluster models differ from those of the quantum mechanical reference model. To address this issue, we propose a new variant of the embedded cluster method called the level-shifted embedded cluster (LSEC) method, which allows the energy levels to be shifted to match the reference levels by tuning the boundary ECPs. Our validation calculations on the adsorption of various adsorbates with different properties on the MgO(100) surface show that the overall performance of QM/MM with the LSEC method is excellent for the adsorption energies, geometries, and charge properties. The excellent performance holds for both the nonstoichiometric and stoichiometric clusters (i.e., Mg9O14 and Mg9O9, respectively), demonstrating the robustness of the LSEC method. We expect that the LSEC method can be combined with QM/MM or used separately for future chemical studies of metal oxides and other ionically bonded systems.

Metal-Support Interactions in Heterogeneous Catalysis: DFT Calculations on the Interaction of Copper Nanoparticles with Magnesium Oxide

Oxide supports play an important role in enhancing the catalytic properties of transition metal nanoparticles in heterogeneous catalysis. How extensively interactions between the oxide support and the nanoparticles impact the electronic structure as well as the surface properties of the nanoparticles is hence of high interest. In this study, the influence of a magnesium oxide support on the properties of copper nanoparticles with different size, shape, and adsorption sites is investigated using density functional theory (DFT) calculations. By proposing simple models to reduce the cost of the calculations while maintaining the accuracy of the results, we show using the nonreducible oxide support MgO as an example that there is no significant influence of the MgO support on the electronic structure of the copper nanoparticles, with the exception of adsorption directly at the Cu-MgO interface. We also propose a simplified methodology that allows us to reduce the cost of the calculations, while the accuracy of the results is maintained. We demonstrate in addition that the Cu nanowire model corresponds well to the nanoparticle model, which reduces the computational cost even further.

Simple Approximation for the Ideal Reference State of Gases Adsorbed on Solid-State Surfaces

Reference states are useful as models for facilitating calculations of equilibrium constants, and they may also serve as standard states that are convenient for organizing and tabulating thermodynamic data; however, standard state conventions and appropriate reference states for adsorbed species have received less attention than those for pure substances and solutes. Here, we compare seven choices of reference states for calculations of equilibrium constants and transition state theory rate constants for flat surfaces, in particular (1) an ideal 2D harmonic oscillator, (2) an ideal rigid-molecule harmonic oscillator, (3) an ideal 2D harmonic oscillator with separable surface modes, (4) a 2D ideal gas, (5) an ideal 2D hindered translator, (6) an ideal 2D hindered translator with lowest-order barriers, and (7) a simple ideal 2D hindered translator proposed in this work. The advantage of models 5-7 is that they can treat both mobile and localized adsorbates in a consistent way, whereas models 1-3 are only appropriate for localized adsorbates, and model 4 is only appropriate for a freely translating adsorbate. Furthermore, models 6 and 7 reduce the computational cost without the user having to calculate barrier heights for diffusion. An advantage of the simple ideal 2D hindered translator is that it has a physical high-temperature limit. We also propose a reference state for nonflat surfaces. The user is encouraged to choose a reference state based on the appropriateness of the model and the practicality of the calculations.

First-principles modelling of the new generation of subnanometric metal clusters: Recent case studies

The very recent development of highly selective techniques making possible the synthesis and experimental characterization of subnanometric (subnanometer-sized) metal clusters (even single atoms) is pushing our understanding far beyond the present knowledge in materials science, driving these clusters as a new generation of quantum materials at the lower bounds of nanotechnology. When the size of the metal cluster is reduced to a small number of atoms, the d-band of the metal splits into a subnanometric d-type molecular orbitals network in which all metal atoms are inter-connected, with the inter-connections having the length of a chemical bond (1-2 Å). These molecular characteristics are at the very core of the high stability and novel properties of the smallest metal clusters, with their integration into colloidal materials interacting with the environment having the potential to further boost their performance in applications such as luminescence, sensing, bioimaging, theranostics, energy conversion, catalysis, and photocatalysis. Through the presentation of very recent case studies, this Feature Article is aimed to illustrate how first-principles modelling, including methods beyond the state-of-the-art and an interplay with cutting-edge experiments, is helping to understand the special properties of these clusters at the most fundamental level. Moreover, it will be discussed how superfluid helium droplets can act both as nano-reactors and carriers to achieve the synthesis and surface deposition of metal clusters. This concept will be illustrated with the quantum simulation of the helium droplet-assisted soft-landing of a single Au atom onto a titanium dioxide (TiO₂) surface. Next, it will be shown how the application of first-principles methods have disclosed the fundamental reasons why subnanometric Cu₅ clusters are resistant to irreversible oxidation, and capable of increasing and extending into the visible region the solar absorption of TiO₂, of augmenting its efficiency for photo-catalysis beyond a factor of four, also considering the decomposition and photo-activation of CO₂ as a prototypical (photo-) catalytic reaction. Finally, I will discuss how the modification of the same material with subnanometric Ag₅ clusters has converted it into a "reporter" of a surface polaron property as well as a novel two-dimensional polaronic material.

Kinetic Monte Carlo simulations for heterogeneous catalysis: Fundamentals, current status, and challenges

Kinetic Monte Carlo (KMC) simulations in combination with first-principles (1p)-based calculations are rapidly becoming the gold-standard computational framework for bridging the gap between the wide range of length scales and time scales over which heterogeneous catalysis unfolds. 1p-KMC simulations provide accurate insights into reactions over surfaces, a vital step toward the rational design of novel catalysts. In this Perspective, we briefly outline basic principles, computational challenges, successful applications, as well as future directions and opportunities of this promising and ever more popular kinetic modeling approach.

Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis

Autonomous computations that rely on automated reaction network elucidation algorithms may pave the way to make computational catalysis on a par with experimental research in the field. Several advantages of this approach are key to catalysis: (i) automation allows one to consider orders of magnitude more structures in a systematic and open-ended fashion than what would be accessible by manual inspection. Eventually, full resolution in terms of structural varieties and conformations as well as with respect to the type and number of potentially important elementary reaction steps (including decomposition reactions that determine turnover numbers) may be achieved. (ii) Fast electronic structure methods with uncertainty quantification warrant high efficiency and reliability in order to not only deliver results quickly, but also to allow for predictive work. (iii) A high degree of autonomy reduces the amount of manual human work, processing errors, and human bias. Although being inherently unbiased, it is still steerable with respect to specific regions of an emerging network and with respect to the addition of new reactant species. This allows for a high fidelity of the formalization of some catalytic process and for surprising in silico discoveries. In this work, we first review the state of the art in computational catalysis to embed autonomous explorations into the general field from which it draws its ingredients. We then elaborate on the specific conceptual issues that arise in the context of autonomous computational procedures, some of which we discuss at an example catalytic system.

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SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11244-021-01543-9.

Identifying the Atomic Layer Stacking of Mo2C MXene by Probe Molecule Adsorption

A density functional theory study is presented here aimed at investigating whether the atomic stacking on the new family of two-dimensional MXene materials has an influence on their adsorption properties and whether these properties can provide information about this structural feature. To this end, the Mo₂C MXene, exhibiting two nearly degenerate crystal structures with either ABC or ABA atomic stacking, is chosen as a case study. The study of the adsorption of CO, CO₂, and H₂O on both polymorphs of Mo₂C reveals substantial differences that could be used in experiments to provide information about the atomic stacking of a given sample. Particularly, we show that the asymmetric and symmetric stretching modes of the adsorbed CO₂ and the CO stretching mode are clear features that allow one to identify the stacking of atomic layers of the Mo₂C MXene. The present finding is likely to apply to other MXenes as well.

Adsorption and Activation of CO2 on Nitride MXenes: Composition, Temperature, and Pressure effects

The interaction of CO₂ with nitride MXenes of different thickness is investigated using periodic density functional theory‐based calculations and kinetic simulations carried out in the framework of transition state theory, the ultimate goal being predicting their possible use in Carbon Capture and Storage (CCS). We consider the basal (0001) surface plane of nitride MXenes with M_n+1N_n (n=1–3; M=Ti, Zr, Hf, V, Nb, Ta, Cr, Mo, and W) stoichiometry and also compare to equivalent results for extended (001) and (111) surfaces of the bulk rock‐salt transition metal nitride compounds. The present results show that the composition of MXenes has a marked influence on the CO₂‐philicity of these substrates, whereas the thickness effect is, in general, small, but not negligible. The largest exothermic activation is predicted for Ti‐, Hf‐, and Zr‐derived MXenes, making them feasible substrates for CO₂ trapping. From an applied point of view, Cr‐, Mo‐, and W‐derived MXenes are especially well suited for CCS as the interaction with CO₂ is strong enough but molecular dissociation is not favored. Newly developed kinetic phase diagrams are introduced supporting that Cr‐, Mo‐, and W‐derived MXenes are appropriate CCS substrates as they are predicted to exhibit easy capture at mild conditions and easy release by heating below 500 K.