Discharging of Ramsdellite MnO Cathode in a Lithium-Ion Battery.

We report an application of our unbiased Monte Carlo approach to investigate thermodynamic and electrochemical properties of lithiated manganese oxide in the ramsdellite phase (R-MnO) to uncover the mechanism of lithium intercalation and understand charging/discharging of R-MnO as a cathode material in lithium-ion batteries. The lithium intercalation reaction was computationally explored by modeling thermodynamically significant distributions of lithium and reduced manganese in the R-MnO framework for a realistic range of lithium molar fractions 0 < < 1 in Li MnO. We employed interatomic potentials and analyzed the thermodynamics of the resultant grand canonical ensemble.

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.

Nucleation of zeolitic imidazolate frameworks: from molecules to nanoparticles.

We have studied the clusters involved in the initial stages of nucleation of Zeolitic Imidazolate Frameworks, employing a wide range of computational techniques. In the pre-nucleating solution, the prevalent cluster is the ZnIm cluster (formed by a zinc cation, Zn, and four imidazolate anions, Im), although clusters such as ZnIm, ZnIm, ZnIm, ZnIm, ZnIm, or ZnIm have energies that are not much higher, so they would also be present in solution at appreciable quantities. All these species, except ZnIm, have a tetrahedrally coordinated Zn cation.

The Interplay of Interstitial and Substitutional Copper in Zinc Oxide.

Cu impurities are reported to have significant effects on the electrical and optical properties of bulk ZnO. In this work, we study the defect properties of Cu in ZnO using hybrid quantum mechanical/molecular mechanical (QM/MM)-embedded cluster calculations based on a multi-region approach that allows us to model defects at the true dilute limit, with polarization effects described in an accurate and consistent manner. We compute the electronic structure, energetics, and geometries of Cu impurities, including substitutional and interstitial configurations, and analyze their effects on the electronic structure.

Structure prediction of crystals, surfaces and nanoparticles.

We review the current techniques used in the prediction of crystal structures and their surfaces and of the structures of nanoparticles. The main classes of search algorithm and energy function are summarized, and we discuss the growing role of methods based on machine learning. We illustrate the current status of the field with examples taken from metallic, inorganic and organic systems.

Structure and Properties of Nanosilicates with Olivine (MgSiO) and Pyroxene (MgSiO) Compositions.

Magnesium-rich silicates are ubiquitous both terrestrially and astronomically, where they are often present as small particles. Nanosized Mg-rich silicate particles are likely to be particularly important for understanding the formation, processing, and properties of cosmic dust grains. Although astronomical observations and laboratory studies have revealed much about such silicate dust, our knowledge of this hugely important class of nanosolids largely rests on top-down comparisons with the properties of bulk silicates.

Are octahedral clusters missing on the carbon energy landscape?

We report a new class of carbon nanostructures at a lower sub-nano end of the size scale with a surprising stability, as compared to the well-known carbon fullerenes. The octahedral carbon clusters contain tetragonal rings, which, in spite of a common belief, prove to be an energy efficient means of plying graphene sheets to make three-dimensional spheroid shapes, similar to fullerenes. The two families of structures are shown to be competitive at small sizes (∼20 atoms) at room temperature, and for higher temperatures, at both small and large sizes (>200 atoms).

What is the best or most relevant global minimum for nanoclusters? Predicting, comparing and recycling cluster structures with WASP@N.

To address the question posed in the title, we have created, and now report details of, an open-access database of cluster structures with a web-assisted interface and toolkit as part of the WASP@N project. The database establishes a map of connectivities within each structure, the information about which is coded and kept as individual labels, called hashkeys, for the nanoclusters. These hashkeys are the basis for structure comparison within the database, and for establishing a map of connectivities between similar structures (topologies).

Thermodynamically accessible titanium clusters Ti, N = 2-32.

We have performed a genetic algorithm search on the tight-binding interatomic potential energy surface (PES) for small TiN (N = 2-32) clusters. The low energy candidate clusters were further refined using density functional theory (DFT) calculations with the PBEsol exchange-correlation functional and evaluated with the PBEsol0 hybrid functional. The resulting clusters were analysed in terms of their structural features, growth mechanism and surface area.

An efficient genetic algorithm for structure prediction at the nanoscale.

We have developed and implemented a new global optimization technique based on a Lamarckian genetic algorithm with the focus on structure diversity. The key process in the efficient search on a given complex energy landscape proves to be the removal of duplicates that is achieved using a topological analysis of candidate structures. The careful geometrical prescreening of newly formed structures and the introduction of new mutation move classes improve the rate of success further.

Describing Excited State Relaxation and Localization in TiO2 Nanoparticles Using TD-DFT.

We have investigated the description of excited state relaxation in naked and hydrated TiO2 nanoparticles using Time-Dependent Density Functional Theory (TD-DFT) with three common hybrid exchange-correlation (XC) potentials: B3LYP, CAM-B3LYP and BHLYP. Use of TD-CAM-B3LYP and TD-BHLYP yields qualitatively similar results for all structures, which are also consistent with predictions of coupled-cluster theory for small particles. TD-B3LYP, in contrast, is found to make rather different predictions; including apparent conical intersections for certain particles that are not observed with TD-CAM-B3LYP nor with TD-BHLYP.

From monomer to monolayer: a global optimisation study of (ZnO)n nanoclusters on the Ag surface.

We employ global optimisation to investigate how oxide nanoclusters of increasing size can best adapt their structure to lower the system energy when interacting with a realistic extended metal support. Specifically, we focus on the (ZnO)@Ag(111) system where experiment has shown that the infinite Ag(111)-supported ZnO monolayer limit corresponds to an epitaxially 7 : 8 matched graphene-like (Zn(3)O(3))-based hexagonal sheet. Using a two-stage search method based on classical interatomic potentials and then on more accurate density functional theory, we report global minina candidate structures for Ag-supported (ZnO)n cluster with sizes ranging from n = 1-24.

Interlayer cation exchange stabilizes polar perovskite surfaces.

Global optimization is used to study the structure of the polar KTaO3 (001) surface. It is found that cation exchange near the surface leads to the most stable structure. This mechanism is likely to be general to metal oxides containing cations of differing charge.

Modeling Excited States in TiO Nanoparticles: On the Accuracy of a TD-DFT Based Description.

We have investigated the suitability of Time-Dependent Density Functional Theory (TD-DFT) to describe vertical low-energy excitations in naked and hydrated titanium dioxide nanoparticles. Specifically, we compared TD-DFT results obtained using different exchange-correlation (XC) potentials with those calculated using Equation-of-Motion Coupled Cluster (EOM-CC) quantum chemistry methods. We demonstrate that TD-DFT calculations with commonly used XC potentials (e.

Band alignment of rutile and anatase TiO₂.

The most widely used oxide for photocatalytic applications owing to its low cost and high activity is TiO₂. The discovery of the photolysis of water on the surface of TiO₂ in 1972 launched four decades of intensive research into the underlying chemical and physical processes involved. Despite much collected evidence, a thoroughly convincing explanation of why mixed-phase samples of anatase and rutile outperform the individual polymorphs has remained elusive.

Microscopic origin of the optical processes in blue sapphire.

Al2O3 changes from transparent to a range of intense colours depending on the chemical impurities present. In blue sapphire, Fe and Ti are incorporated; however, the chemical process that gives rise to the colour has long been debated. Atomistic modelling identifies charge transfer from Ti(III) to Fe(III) as being responsible for the characteristic blue appearance.

From ergodicity to extended phase diagrams.

Structure prediction of stable and metastable phases is put on equal footing for the first time, with a solid thermodynamical background. How to estimate the lifetime of metastable phases is demonstrated by recent groundbreaking work of Jansen, Pentin, and Schön. At the heart lies the exploration of the Gibbs free-energy landscapes and the extended phase diagrams for complex systems.

Exploration of multiple energy landscapes for zirconia nanoclusters.

We have predicted the stable and low-energy metastable structures for (ZrO(2))(n) clusters, where n = 1 to 12, employing Density Functional Theory (DFT) at the PBEsol0 level. A process of data mining and the application of an evolutionary algorithm to three different energy landscapes, as defined by interatomic potentials, for each cluster size, was used to generated the plausible structures for refinement using DFT at the PBEsol level. The structures for zirconia were found to be similar to that predicted for titania except that the order, with respect to the binding energies, of the configurations for the two compounds were different for the larger sized clusters.

On the problem of cluster structure diversity and the value of data mining.

Data mining, involving cross examination of cluster structure pools collected for ZnO, GaN, LiF and AgI, has been applied to predict plausible cluster structures of related binary materials. We consider the energy landscapes of (MX)(12) clusters for materials that possess tetrahedral bulk phases, wurtzite or sphalerite, including LiF, BeO, BN, AlN, SiC, CuF, ZnO, GaN, GeC and AgI. The energy is evaluated using the hybrid PBEsol0 density functional for structures optimised at the PBEsol level.