Low-Temperature ALD of SbOx /Sb2 Te3 Multilayers with Boosted Thermoelectric Performance

Nanoscale superlattice (SL) structures have proven to be effective in enhancing the thermoelectric (TE) properties of thin films. Herein, the main phase of antimony telluride (Sb2 Te3 ) thin film with sub-nanometer layers of antimony oxide (SbOx ) is synthesized via atomic layer deposition (ALD) at a low temperature of 80 °C. The SL structure is tailored by varying the cycle numbers of Sb2 Te3 and SbOx . A remarkable power factor of 520.8 µW m-1 K-2 is attained at room temperature when the cycle ratio of SbOx and Sb2 Te3 is set at 1:1000 (i.e., SO:ST = 1:1000), corresponding to the highest electrical conductivity of 339.8 S cm-1 . The results indicate that at the largest thickness, corresponding to ten ALD cycles, the SbOx layers act as a potential barrier that filters out the low-energy charge carriers from contributing to the overall electrical conductivity. In addition to enhancing the scattering of the mid-to-long-wavelength at the SbOx /Sb2 Te3 interface, the presence of the SbOx sub-layer induces the confinement effect and strain forces in the Sb2 Te3 thin film, thereby effectively enhancing the Seebeck coefficient and reducing the thermal conductivity. These findings provide a new perspective on the design of SL-structured TE materials and devices.

Metameric Inpainting for Image Warping

Image-warping, a per-pixel deformation of one image into another, is an essential component in immersive visual experiences such as virtual reality or augmented reality. The primary issue with image warping is disocclusions, where occluded (and hence unknown) parts of the input image would be required to compose the output image. We introduce a new image warping method, Metameric image inpainting - an approach for hole-filling in real-time with foundations in human visual perception. Our method estimates image feature statistics of disoccluded regions from their neighbours. These statistics are inpainted and used to synthesise visuals in real-time that are less noticeable to study participants, particularly in peripheral vision. Our method offers speed improvements over the standard structured image inpainting methods while improving realism over colour-based inpainting such as push-pull. Hence, our work paves the way towards future applications such as depth image-based rendering, 6-DoF 360 rendering, and remote render-streaming.

Fermi surface chirality induced in a TaSe2 monosheet formed by a Ta/Bi2Se3 interface reaction

Spin-momentum locking in topological insulators and materials with Rashba-type interactions is an extremely attractive feature for novel spintronic devices and is therefore under intense investigation. Significant efforts are underway to identify new material systems with spin-momentum locking, but also to create heterostructures with new spintronic functionalities. In the present study we address both subjects and investigate a van der Waals-type heterostructure consisting of the topological insulator Bi₂Se₃ and a single Se-Ta-Se triple-layer (TL) of H-type TaSe₂ grown by a method which exploits an interface reaction between the adsorbed metal and selenium. We then show, using surface x-ray diffraction, that the symmetry of the TaSe₂-like TL is reduced from D_3h to C_3v resulting from a vertical atomic shift of the tantalum atom. Spin- and momentum-resolved photoemission indicates that, owing to the symmetry lowering, the states at the Fermi surface acquire an in-plane spin component forming a surface contour with a helical Rashba-like spin texture, which is coupled to the Dirac cone of the substrate. Our approach provides a route to realize chiral two-dimensional electron systems via interface engineering in van der Waals epitaxy that do not exist in the corresponding bulk materials.

Current limitations of spintronics devices based on bulk topological materials stimulate the search for new materials and structures with interesting spin properties. Here the authors report a chiral spin texture around the Fermi level related to structural symmetry breaking in a TaSe₂ layer grown on a Bi2Se3 surface.

Hidden Charge Order in an Iron Oxide Square-Lattice Compound

Since the discovery of charge disproportionation in the FeO_{2} square-lattice compound Sr_{3}Fe_{2}O_{7} by Mössbauer spectroscopy more than fifty years ago, the spatial ordering pattern of the disproportionated charges has remained "hidden" to conventional diffraction probes, despite numerous x-ray and neutron scattering studies. We have used neutron Larmor diffraction and Fe K-edge resonant x-ray scattering to demonstrate checkerboard charge order in the FeO_{2} planes that vanishes at a sharp second-order phase transition upon heating above 332 K. Stacking disorder of the checkerboard pattern due to frustrated interlayer interactions broadens the corresponding superstructure reflections and greatly reduces their amplitude, thus explaining the difficulty of detecting them by conventional probes. We discuss the implications of these findings for research on "hidden order" in other materials.

PhaseGAN: a deep-learning phase-retrieval approach for unpaired datasets

Phase retrieval approaches based on deep learning (DL) provide a framework to obtain phase information from an intensity hologram or diffraction pattern in a robust manner and in real-time. However, current DL architectures applied to the phase problem rely on i) paired datasets, i. e., they are only applicable when a satisfactory solution of the phase problem has been found, and ii) the fact that most of them ignore the physics of the imaging process. Here, we present PhaseGAN, a new DL approach based on Generative Adversarial Networks, which allows the use of unpaired datasets and includes the physics of image formation. The performance of our approach is enhanced by including the image formation physics and a novel Fourier loss function, providing phase reconstructions when conventional phase retrieval algorithms fail, such as ultra-fast experiments. Thus, PhaseGAN offers the opportunity to address the phase problem in real-time when no phase reconstructions but good simulations or data from other experiments are available.

Transition from a uni- to a bimodal interfacial charge distribution in [Formula: see text]/[Formula: see text] upon cooling

We present a combined resonant soft X-ray reflectivity and electric transport study of [Formula: see text]/[Formula: see text] field effect devices. The depth profiles with atomic layer resolution that are obtained from the resonant reflectivity reveal a pronounced temperature dependence of the two-dimensional electron liquid at the [Formula: see text]/[Formula: see text] interface. At room temperature the corresponding electrons are located close to the interface, extending down to 4 unit cells into the [Formula: see text] substrate. Upon cooling, however, these interface electrons assume a bimodal depth distribution: They spread out deeper into the [Formula: see text] and split into two distinct parts, namely one close to the interface with a thickness of about 4 unit cells and another centered around 9 unit cells from the interface. The results are consistent with theoretical predictions based on oxygen vacancies at the surface of the [Formula: see text] film and support the notion of a complex interplay between structural and electronic degrees of freedom.

Reflectance and Natural Illumination from Single-Material Specular Objects Using Deep Learning

In this paper, we present a method that estimates reflectance and illumination information from a single image depicting a single-material specular object from a given class under natural illumination. We follow a data-driven, learning-based approach trained on a very large dataset, but in contrast to earlier work we do not assume one or more components (shape, reflectance, or illumination) to be known. We propose a two-step approach, where we first estimate the object's reflectance map, and then further decompose it into reflectance and illumination. For the first step, we introduce a Convolutional Neural Network (CNN) that directly predicts a reflectance map from the input image itself, as well as an indirect scheme that uses additional supervision, first estimating surface orientation and afterwards inferring the reflectance map using a learning-based sparse data interpolation technique. For the second step, we suggest a CNN architecture to reconstruct both Phong reflectance parameters and high-resolution spherical illumination maps from the reflectance map. We also propose new datasets to train these CNNs. We demonstrate the effectiveness of our approach for both steps by extensive quantitative and qualitative evaluation in both synthetic and real data as well as through numerous applications, that show improvements over the state-of-the-art.

Perceptual Real-Time 2D-to-3D Conversion Using Cue Fusion

We propose a system to infer binocular disparity from a monocular video stream in real-time. Different from classic reconstruction of physical depth in computer vision, we compute perceptually plausible disparity, that is numerically inaccurate, but results in a very similar overall depth impression with plausible overall layout, sharp edges, fine details and agreement between luminance and disparity. We use several simple monocular cues to estimate disparity maps and confidence maps of low spatial and temporal resolution in real-time. These are complemented by spatially-varying, appearance-dependent and class-specific disparity prior maps, learned from example stereo images. Scene classification selects this prior at runtime. Fusion of prior and cues is done by means of robust MAP inference on a dense spatio-temporal conditional random field with high spatial and temporal resolution. Using normal distributions allows this in constant-time, parallel per-pixel work. We compare our approach to previous 2D-to-3D conversion systems in terms of different metrics, as well as a user study and validate our notion of perceptually plausible disparity.

Synthetic polymers as substrates for a DNA-sliding clamp protein

The clamp protein (gp45) of the DNA polymerase III of the bacteriophage T4 is known to bind to DNA and stay attached to it in order to facilitate the process of DNA copying by the polymerase. As part of a project aimed at developing new biomimetic data-encoding systems we have investigated the binding of gp45 to synthetic polymers, that is, rigid, helical polyisocyanopeptides. Molecular modelling studies suggest that the clamp protein may interact with the latter polymers. Experiments aimed at verifying these interactions are presented and discussed.

Novel Views of Objects from a Single Image

Taking an image of an object is at its core a lossy process. The rich information about the three-dimensional structure of the world is flattened to an image plane and decisions such as viewpoint and camera parameters are final and not easily revertible. As a consequence, possibilities of changing viewpoint are limited. Given a single image depicting an object, novel-view synthesis is the task of generating new images that render the object from a different viewpoint than the one given. The main difficulty is to synthesize the parts that are disoccluded; disocclusion occurs when parts of an object are hidden by the object itself under a specific viewpoint. In this work, we show how to improve novel-view synthesis by making use of the correlations observed in 3D models and applying them to new image instances. We propose a technique to use the structural information extracted from a 3D model that matches the image object in terms of viewpoint and shape. For the latter part, we propose an efficient 2D-to-3D alignment method that associates precisely the image appearance with the 3D model geometry with minimal user interaction. Our technique is able to simulate plausible viewpoint changes for a variety of object classes within seconds. Additionally, we show that our synthesized images can be used as additional training data that improves the performance of standard object detectors.

Insight into the complete substrate-binding pocket of ThiT by chemical and genetic mutations

Energy-coupling factor (ECF) transporters are involved in the uptake of micronutrients in bacteria. The transporters capture the substrate by high-affinity binding proteins, the so-called S-components. Here, we present the analysis of two regions of the substrate-binding pocket of the thiamine-specific S-component in Lactococcus lactis, ThiT. First, interaction of the thiazolium ring of thiamine with residues Trp34, His125 and Glu84 by π-π-stacking and cation-π is studied, and second, the part of the binding pocket that extends from the hydroxyl group. We mutated either the transported ligand (chemically) or the protein (genetically). Surprisingly, modifications in the thiazolium ring by introducing substituents with opposite electronic effects had similar effects on the binding affinity. We hypothesize that the electronic effects are superseeded by steric effects of the added substituents, which renders the study of isolated interactions difficult. Amino acid substitutions in ThiT indicate that the electrostatic interaction facilitated by residue Glu84 of ThiT and thiamine is necessary for picomolar affinity. Deazathiamine derivatives that explore the subpocket of the binding site extending from the hydroxyl group of thiamine bind with high affinity to ThiT and may be developed into selective inhibitors of thiamine transport by ECF transporters. Molecular-dynamics simulations suggest that two of these derivatives may not only bind to ThiT, but could also be transported.

Real-time screen-space scattering in homogeneous environments

The proposed screen-space algorithm approximates light scattering in homogeneous participating environments, such as water. Instead of simulating full global illumination, this method models scattering by a physically based point spread function. A discrete hierarchical convolution in a texture MIP map makes the algorithm efficient, and a custom anisotropic incremental filter prevents illumination leaking.

Electronic confinement and ordering instabilities in colossal magnetoresistive bilayer manganites

We present angle-resolved photoemission studies of (La{1-z}Pr{z}){2-2x}Sr{1+2x}Mn{2}O{7} with x=0.4 and z=0.1, 0.2, and 0.4 along with density functional theory calculations and x-ray scattering data. Our results show that the bilayer splitting in the ferromagnetic metallic phase of these materials is small, if not completely absent. The charge carriers are therefore confined to a single MnO{2} layer, which in turn results in a strongly nested Fermi surface. In addition to this, the spectral function also displays clear signatures of an electronic ordering instability well below the Fermi level. The increase of the corresponding interaction strength with z and its magnitude of ∼400  meV make the coupling to a bare phonon highly unlikely. Instead we conclude that fluctuating order, involving electronic and lattice degrees of freedom, causes the observed renormalization of the spectral features.