Abstract: Hidden, sub-surface paint layers and features contain valuable information for the art-historical investigation of a painting's past and for its conservation for coming generations. The number of techniques available for the study of these features has been considerably extended in the last decades and established techniques have been refined. This review focuses on mobile non-destructive subsurface imaging and depth profiling techniques, which allow for the in-situ investigation of easel paintings, i.e. paintings on a portable support. Among the techniques discussed are: X-ray radiography and infrared reflectography, which are long established methods and are in use for several decades. Their capabilities of element/species specific imaging have been extended by the introduction of energy/wavelength resolved measurements. Scanning macro-X-ray fluorescence analysis made it for the first time possible to acquire elemental distribution images in-situ and optical coherence tomography allows for the non-destructive study the surface paint layers in virtual cross-sections. These techniques and their variants are presented next to other techniques, such as Terahertz imaging, Nuclear Magnetic Resonance depth profiling and established techniques for non destructive testing (thermography, ultrasonic imaging and laser based interference methods) applied in the conservation of historical paintings. Next to selected case studies the capabilities and limitations of the techniques are discussed. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: Gielis curves (GC) can represent a wide range of shapes and patterns ranging from star shapes to symmetric and asymmetric polygons, and even self intersecting curves. Such patterns appear in natural objects or phenomena, such as flowers, crystals, pollen structures, animals, or even wave propagation. Gielis curves and surfaces are an extension of Lamé curves and surfaces (superquadrics) which have benefited in the last two decades of extensive researches to retrieve their parameters from various data types, such as range images, 2D and 3D point clouds, etc. Unfortunately, the most efficient techniques for superquadrics recovery, based on deterministic methods, cannot directly be adapted to Gielis curves. Indeed, the different nature of their parameters forbids the use of a unified gradient descent approach, which requires initial pre-processings, such as the symmetry detection, and a reliable pose and scale estimation. Furthermore, even the most recent algorithms in the literature remain extremely sensitive to initialization and often fall into local minima in the presence of large missing data. We present a simple evolutionary algorithm which overcomes most of these issues and unifies all of the required operations into a single though efficient approach. The key ideas in this paper are the replacement of the potential fields used for the cost function (closed form) by the shortest Euclidean distance (SED, iterative approach), the construction of cost functions which minimize the shortest distance as well as the curve length using R-functions, and slight modifications of the evolutionary operators. We show that the proposed cost function based on SED and R-function offers the best compromise in terms of accuracy, robustness to noise, and missing data.

Abstract: Nowadays, X-ray fluorescence spectrometry (XRF) is a well-established analytical technique for qualitative and quantitative elemental analysis (sometimes from Be to U) of a wide variety of samples. In particular, the truly multi-element character, acceptable speed and economy, ease of automation and the possibility to directly analyse solid samples are the most important features among the many that have made it a very mature analytical tool for routine quality controls in many industries, as well as for analytical support for the research laboratory.e recent technological advances, including the design of low-power micro-focus tubes and the novel X-ray optics and detectors have made it possible to extend XRF to the determination of low-Z elements and to obtain 2D or 3D information on a micrometre-scale. Furthermore, the recent development and commercialisation of benchtop and portable instrumentation, that offer extreme simplicity of operation in a low-cost design, have promoted even more the approach of XRF for many analytical problems.is article highlights this state-of-the art technique with regards to currently available XRF instrumentation on the market as well as recent applications in environmental and industrial fields.

Abstract: A (LaVO3)6/(SrVO3)(3) superlattice is studied with a combination of sub-A resolved scanning transmission electron microscopy and monochromated electron energy-loss spectroscopy. The V oxidation state is mapped with atomic spatial resolution enabling us to investigate electronic reconstruction at the LaVO3/SrVO3 interfaces. Surprisingly, asymmetric charge distribution is found at adjacent chemically symmetric interfaces. The local structure is proposed and simulated with a double channeling calculation which agrees qualitatively with our experiment. We demonstrate that local strain asymmetry is the likely cause of the electronic asymmetry of the interfaces. The electronic reconstruction at the interfaces extends much further than the chemical composition, varying from 0.5 to 1.2 nm. This distance corresponds to the length of charge transfer previously found in the (LaVO3)./(SrVO3). metal/insulating and the (LaAlO3)./(SrTiO3). insulating/insulating interfaces.

Abstract: We report a method to reliably count the number of atoms from high-angle annular dark field scanning transmission electron microscopy images. A model-based analysis of the experimental images is used to measure scattering cross sections at the atomic level. The high sensitivity of these measurements in combination with a thorough statistical analysis enables us to count atoms with single-atom sensitivity. The validity of the results is confirmed by means of detailed image simulations. We will show that the method can be applied to nanocrystals of arbitrary shape, size, and atom type without the need for a priori knowledge about the atomic structure.

Abstract: Bogoliubov-de Gennes theory is used to investigate the effect of the size of a superconducting square on the vortex states in the quantum confinement regime. When the superconducting coherence length is comparable to the Fermi wavelength, the shape resonances of the superconducting order parameter have strong influence on the vortex configuration. Several unconventional vortex states, including asymmetric ones, giant-multivortex combinations, and states comprising giant antivortices, were found as ground states and their stability was found to be very sensitive on the value of k(F)xi(0), the size of the sample W, and the magnetic flux Phi. By increasing the temperature and/or enlarging the size of the sample, quantum confinement is suppressed and the conventional mesoscopic vortex states as predicted by the Ginzburg-Laudau (GL) theory are recovered. However, contrary to the GL results we found that the states containing symmetry-induced vortex-antivortex pairs are stable over the whole temperature range. It turns out that the inhomogeneous order parameter induced by quantum confinement favors vortex-antivortex molecules, as well as giant vortices with a rich structure in the vortex core-unattainable in the GL domain.

Abstract: Platinum-nanoparticle-based catalysts are widely used in many important chemical processes and
automobile industries. Downsizing catalyst nanoparticles to single atoms is highly desirable to maximize
their use efficiency, however, very challenging. Here we report a practical synthesis for isolated single Pt
atoms anchored to graphene nanosheet using the atomic layer deposition (ALD) technique. ALD offers the
capability of precise control of catalyst size span from single atom, subnanometer cluster to nanoparticle.
The single-atom catalysts exhibit significantly improved catalytic activity (up to 10 times) over that of the
state-of-the-art commercial Pt/C catalyst. X-ray absorption fine structure (XAFS) analyses reveal that the
low-coordination and partially unoccupied densities of states of 5d orbital of Pt atoms are responsible for the
excellent performance. This work is anticipated to form the basis for the exploration of a next generation of
highly efficient single-atom catalysts for various applications.

Abstract: A new method is developed for synthesizing Ti4O7 supported Ru@Pt core–shell catalyst (Ru@Pt/Ti4O7) through pyrolysis followed by microwave irradiation. The purpose is to improve the Ru durability of PtRu from core–shell structure and strong bonding to Ti4O7 oxide. In this method, the first step is to co-reduce the mixture of ruthenium precursor and TiO2 in a H2 reducing atmosphere under heat-treatment to obtain a Ru core on Ti4O7 support, and the second step is to create a shell of platinum via microwave irradiation. Energy dispersive X-ray spectrometry, X-ray Diffraction, High-resolution Scanning Transmission Electron Microscopy with the high-angle annular dark-field method and Electron Energy-Loss Spectroscopy are used to demonstrate that this catalyst with larger particles has a core–shell structure with a Ru core and a Pt shell. Electrochemical measurements show Ru@Pt/Ti4O7 catalyst has a higher CO-tolerance capability than that of PtRu/C alloy catalyst.

Abstract: In this work, the simultaneous iterative reconstruction technique (SIRT), the total variation minimization (TVM) reconstruction technique and the discrete algebraic reconstruction technique (DART) for electron tomography are compared and the advantages and disadvantages are discussed. Furthermore, we describe how the result of a three dimensional (3D) reconstruction based on TVM can provide objective information that is needed as the input for a DART reconstruction. This approach results in a tomographic reconstruction of which the segmentation is carried out in an objective manner.

Abstract: In the present paper, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. In order to count the number of atoms, it is assumed that the total scattered intensity scales with the number of atoms per atom column. These intensities are quantitatively determined using model-based statistical parameter estimation theory. The distribution describing the probability that intensity values are generated by atomic columns containing a specific number of atoms is inferred on the basis of the experimental scattered intensities. Finally, the number of atoms per atom column is quantified using this estimated probability distribution. The number of atom columns available in the observed STEM image, the number of components in the estimated probability distribution, the width of the components of the probability distribution, and the typical shape of a criterion to assess the number of components in the probability distribution directly affect the accuracy and precision with which the number of atoms in a particular atom column can be estimated. It is shown that single atom sensitivity is feasible taking the latter aspects into consideration.