Role of electron-electron and electron-phonon interaction effect in the optical conductivity of VO2

We have investigated the charge dynamics of VO2 by optical reflectivity measurements. Optical conductivity clearly shows a metal-insulator transition. In the metallic phase, a broad Drude-like structure is observed. On the other hand, in the insulating phase, a broad peak structure around 1.3 eV is observed. It is found that this broad structure observed in the insulating phase shows a temperature dependence. We attribute this to the electron-phonon interaction as in the photoemission spectra.Comment: 6 pages, 8 figures, accepted for publication in Phys. Rev.

Metric tensor as the dynamical variable for variable cell-shape molecular dynamics

We propose a new variable cell-shape molecular dynamics algorithm where the dynamical variables associated with the cell are the six independent dot products between the vectors defining the cell instead of the nine cartesian components of those vectors. Our choice of the metric tensor as the dynamical variable automatically eliminates the cell orientation from the dynamics. Furthermore, choosing for the cell kinetic energy a simple scalar that is quadratic in the time derivatives of the metric tensor, makes the dynamics invariant with respect to the choice of the simulation cell edges. Choosing the densitary character of that scalar allows us to have a dynamics that obeys the virial theorem. We derive the equations of motion for the two conditions of constant external pressure and constant thermodynamic tension. We also show that using the metric as variable is convenient for structural optimization under those two conditions. We use simulations for Ar with Lennard-Jones parameters and for Si with forces and stresses calculated from first-principles of density functional theory to illustrate the applications of the method.Comment: 10 pages + 6 figures, Latex, to be published in Physical Review

Photo-Stabilisation and UV Blocking Efficacy of Coated Macro and Nano-Rutile Titanium Dioxide Particles in Paints and Coatings

Surface treated macro and nanoparticle TiO2samples have been prepared, characterised and their efficiency as UV blockers evaluated in clear coatings and paints. The particle size of the ‘base’ TiO2has been optimised to block UV radiation and the surface treatment developed to deactivate the photocatalytic activity of the surface of the TiO2particles. The resultant UV blockers have been evaluated in both solvent and water-based clear coatings. Nanoparticle TiO2has been prepared from ‘seed’ and the particle size was controlled by calcination. It was found that the choice of particle size is a compromise between UVA absorption, UVB absorption, visible transmission and photoactivity. It has been demonstrated that TiO2with a crystallite size of 25 nm yields a product with the optimum properties. A range of dispersants was successfully used to disperse and mill the TiO2. Both organic and inorganic dispersants were used; 2-amino-2-methyl-1-propanol and 1-amino-2-propanol (MIPA) and P2O5and Na2SiO3respectively. The surface of the nano-TiO2was coated with mixed oxides of silicon, aluminium, zirconium and phosphorous. Addition of the resultant coated nano-rutiles to an Isocyanate Acrylic clear coating prolonged the lifetime of that coating compared to the blank. Generally, a surface treatment based on SiO2, Al2O3and P2O5was more successful than one based on ZrO2, Al2O3and P2O5. Higher addition levels of the surface treatment were beneficial for protecting the polymeric coating. The UV blocker products were also evaluated in a water-based acrylic, first a water-based dispersion of the UV blocker was prepared before addition to the acrylic. The dispersions and resultant acrylic thin films were evaluated using UV/Vis spectroscopy and durability assessed. The ratio of absorbance at 300:500 nm for the water-based dispersion was shown to be a good predictor of both the transparency of the resultant acrylic thin film and the durability of that film, in terms of weight loss. Macro grade titanium dioxide pigments were also prepared and coated with treatments of silica, alumina and siloxane and their photo-stabilising activity in alkyd paint film assessed and found to be directly related to the electron–hole pair mobility and trapping as determined by micro-wave spectroscopy

Visual Data Mining and Discovery in Multivariate Data Using Monotone n-D Structure

Visual data mining (VDM) is an emerging research area of Data Mining and Visual Analytics gaining a deep visual understanding of data. A border between patterns can be recognizable visually, but its analytical form can be quite complex and difficult to discover. VDM methods have shown benefits in many areas, but these methods often fail in visualizing highly overlapped multidimensional data and data with little variability. We address this problem by combining visual techniques with the theory of monotone Boolean functions and data monotonization. The major novelty is in visual presentation of structural relations between n-dimensional objects instead of traditional attempts to visualize each attribute value of n-dimensional objects. The method relies on n-D monotone structural relations between vectors. Experiments with real data show advantages of this approach to uncover a visual border between malignant and benign classes

HOV³ : an approach to visual cluster analysis

Clustering is a major technique in data mining. However the numerical feedback of clustering algorithms is difficult for user to have an intuitive overview of the dataset that they deal with. Visualization has been proven to be very helpful for high-dimensional data analysis. Therefore it is desirable to introduce visualization techniques with user’s domain knowledge into clustering process. Whereas most existing visualization techniques used in clustering are exploration oriented. Inevitably, they are mainly stochastic and subjective in nature. In this paper, we introduce an approach called HOV3 (Hypothesis Oriented Verification and Validation by Visualization), which projects high-dimensional data on the 2D space and reflects data distribution based on user hypotheses. In addition, HOV3 enables user to adjust hypotheses iteratively in order to obtain an optimized view. As a result, HOV3 provides user an efficient and effective visualization method to explore cluster information.12 page(s

Combining Automated and Interactive Visual Analysis of Biomechanical Motion Data

Abstract. We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data. Analyzing the complex 3D motion of, e.g., pigs chewing or bats flying, can be enhanced by providing investigators with a multi-view interface that allows interaction across multiple modalities and representations. In this paper, we employ nonlinear dimensionality reduction to automatically learn a low-dimensional representation of the data and hierarchical clustering to learn patterns inherent within the motion segments. Our multi-view framework allows investigators to simultaneously view a low-dimensional embedding, motion segment clustering, and 3D visual representation of the data side-by-side. We describe an application to a dataset containing thousands of frames of high-speed, 3D motion data collected over multiple experimental trials.