Toward a Consistent Prediction of Defect Chemistry in CeO2

Composition-dependent morphologies of CeO2 nanoparticles in the presence of Co-adsorbed H2O and CO2: a density functional theory study

Catalytic activity is affected by surface morphology, and specific surfaces display greater activity than others. A key challenge is to define synthetic strategies to enhance the expression of more active surfaces and to maintain their stability during the lifespan of the catalyst. In this work, we outline an ab initio approach, based on density functional theory, to predict surface composition and particle morphology as a function of environmental conditions, and we apply this to CeO2 nanoparticles in the presence of co-adsorbed H2O and CO2 as an industrially relevant test case. We find that dissociative adsorption of both molecules is generally the most favourable, and that the presence of H2O can stabilise co-adsorbed CO2. We show that changes in adsorption strength with temperature and adsorbate partial pressure lead to significant changes in surface stability, and in particular that co-adsorption of H2O and CO2 stabilizes the {100} and {110} surfaces over the {111} surface. Based on the changes in surface free energy induced by the adsorbed species, we predict that cuboidal nanoparticles are favoured in the presence of co-adsorbed H2O and CO2, suggesting that cuboidal particles should experience a lower thermodynamic driving force to reconstruct and thus be more stable as catalysts for processes involving these species.

Environment-Driven Variability in Absolute Band Edge Positions and Work Functions of Reduced Ceria

The absolute band edge positions and work function (Φ) are the key electronic properties of metal oxides that determine their performance in electronic devices and photocatalysis. However, experimental measurements of these properties often show notable variations, and the mechanisms underlying these discrepancies remain inadequately understood. In this work, we focus on ceria (CeO2), a material renowned for its outstanding oxygen storage capacity, and combine theoretical and experimental techniques to demonstrate environmental modifications of its ionization potential (IP) and Φ. Under O-deficient conditions, reduced ceria exhibits a decreased IP and Φ with significant sensitivity to defect distributions. In contrast, the IP and Φ are elevated in O-rich conditions due to the formation of surface peroxide species. Surface adsorbates and impurities can further augment these variabilities under realistic conditions. We rationalize the shifts in energy levels by separating the individual contributions from bulk and surface factors, using hybrid quantum mechanical/molecular mechanical (QM/MM) embedded-cluster and periodic density functional theory (DFT) calculations supported by interatomic-potential-based electrostatic analyses. Our results highlight the critical role of on-site electrostatic potentials in determining the absolute energy levels in metal oxides, implying a dynamic evolution of band edges under catalytic conditions.

Chemical Potential Analysis as an Alternative to the van't Hoff Method: Hypothetical Limits of Solar Thermochemical Hydrogen

The van't Hoff method is a standard approach for determining reaction enthalpies and entropies, e.g., in the thermochemical reduction of oxides, which is an important process for solar thermochemical fuels and numerous other applications. However, by analyzing the oxygen partial pressure pO2, e.g., as measured by thermogravimetric analysis (TGA), this method convolutes the properties of the probe gas with the solid-state properties of the examined oxides, which define their suitability for specific applications. The "chemical potential method" is here proposed as an alternative. Using the oxygen chemical potential ΔμO instead of pO2 for the analysis, this method does not only decouple gas-phase and solid-state contributions but also affords a simple and transparent approach to extracting the temperature dependence of the reduction enthalpy and entropy, which carries important information about the defect mechanism. For demonstration of the approach, this work considers three model systems; (1) a generic oxide with noninteracting, charge-neutral oxygen vacancy defects, (2) Sr0.86Ce0.14MnO3(1-δ) alloys with interacting vacancies, and (3) a model for charged vacancy formation in CeO2, which reproduces the extensive experimental TGA data available in the literature. The reduction behavior of these model systems obtained from the chemical potential method is correlated with simulated results for the thermochemical water splitting cycle, highlighting the exceptional behavior of CeO2, which originates from defect ionization. The theoretical performance limits for solar thermochemical hydrogen within the charged defect mechanism are assessed by considering hypothetical materials described by a variation of the CeO2 model parameters within a plausible range.

Impact of Atomic Defects on Ceria Surfaces on Chemical Mechanical Polishing of Silica Glass Surfaces

This study investigates the impact of atomic defects, such as oxygen vacancies and Ce3+ ions, on cerium oxide (ceria) surfaces during chemical mechanical polishing (CMP) for silica glass finishing. Using density functional theory (DFT) and reactive molecular dynamics simulations, the interaction of orthosilicic molecules and silica glass with dry and wet ceria surfaces is explored. Defects alter the surface reactivity, leading to the dissociation of orthosilicic acid on oxygen vacancies, forming a strong Si-O-Ce bond. Hydroxylated surfaces exhibit easier oxygen vacancy formation and thermodynamically favored substitution of hydroxyl groups with orthosilicic acid. A new ReaxFF library for silica/ceria interfaces with defects is validated using DFT outcomes. Reactive MD simulations demonstrate that ceria surfaces with 30% Ce3+ ions on (111) planes exhibit higher polishing efficiency, attributed to increased Si-O-Ce bond formation. The simultaneous presence of oxygen vacancies and various acidic and basic sites on ceria surfaces enhances the polishing efficiency, involving acid-base reactions with silica. Defective surfaces show superior efficiency by removing silicate chains, contrasting with nondefective surfaces removing isolated orthosilicate units. This study provides insights into optimizing CMP processes for high-precision glass industry surface finishing.

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.

Many-Body Methods for Surface Chemistry Come of Age: Achieving Consensus with Experiments

The adsorption energy of a molecule onto the surface of a material underpins a wide array of applications, spanning heterogeneous catalysis, gas storage, and many more. It is the key quantity where experimental measurements and theoretical calculations meet, with agreement being necessary for reliable predictions of chemical reaction rates and mechanisms. The prototypical molecule-surface system is CO adsorbed on MgO, but despite intense scrutiny from theory and experiment, there is still no consensus on its adsorption energy. In particular, the large cost of accurate many-body methods makes reaching converged theoretical estimates difficult, generating a wide range of values. In this work, we address this challenge, leveraging the latest advances in diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] to obtain accurate predictions for CO on MgO. These reliable theoretical estimates allow us to evaluate the inconsistencies in published temperature-programed desorption experiments, revealing that they arise from variations in employed pre-exponential factors. Utilizing this insight, we derive new experimental estimates of the (electronic) adsorption energy with a (more) precise pre-exponential factor. As a culmination of all of this effort, we are able to reach a consensus between multiple theoretical calculations and multiple experiments for the first time. In addition, we show that our recently developed cluster-based CCSD(T) approach provides a low-cost route toward achieving accurate adsorption energies. This sets the stage for affordable and reliable theoretical predictions of chemical reactions on surfaces to guide the realization of new catalysts and gas storage materials.

Bulk and Surface Contributions to Ionisation Potentials of Metal Oxides

Determining the absolute band edge positions in solid materials is crucial for optimising their performance in wide-ranging applications including photocatalysis and electronic devices. However, obtaining absolute energies is challenging, as seen in CeO2 , where experimental measurements show substantial discrepancies in the ionisation potential (IP). Here, we have combined several theoretical approaches, from classical electrostatics to quantum mechanics, to elucidate the bulk and surface contributions to the IP of metal oxides. We have determined a theoretical bulk contribution to the IP of stoichiometric CeO2 of only 5.38 eV, while surface orientation results in intrinsic IP variations ranging from 4.2 eV to 8.2 eV. Highly tuneable IPs were also found in TiO2 , ZrO2 , and HfO2 , in which surface polarisation plays a pivotal role in long-range energy level shifting. Our analysis, in addition to rationalising the observed range of experimental results, provides a firm basis for future interpretations of experimental and computational studies of oxide band structures.

Multiscale QM/MM modelling of catalytic systems with ChemShell

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods are a powerful computational tool for the investigation of all forms of catalysis, as they allow for an accurate description of reactions occurring at catalytic sites in the context of a complicated electrostatic environment. The scriptable computational chemistry environment ChemShell is a leading software package for QM/MM calculations, providing a flexible, high performance framework for modelling both biomolecular and materials catalysis. We present an overview of recent applications of ChemShell to problems in catalysis and review new functionality introduced into the redeveloped Python-based version of ChemShell to support catalytic modelling. These include a fully guided workflow for biomolecular QM/MM modelling, starting from an experimental structure, a periodic QM/MM embedding scheme to support modelling of metallic materials, and a comprehensive set of tutorials for biomolecular and materials modelling.