University of Stuttgart

About: University of Stuttgart is a education organization based out in Stuttgart, Germany. It is known for research contribution in the topics: Laser & Finite element method. The organization has 27715 authors who have published 56370 publications receiving 1363382 citations. The organization is also known as: Universität Stuttgart.

Spatially Selective Nucleation of Metal Clusters on the Tobacco Mosaic Virus

Abstract: Tobacco mosaic virus (TMV) is a very stable nanotube complex of a helical RNA and 2130 coat proteins. The special shape makes it an interesting nano-object, especially as a template for chemical reactions. Here we use TMV as a chemically functionalized template for binding metal ions. Different chemical groups of the coat protein can be used as ligands or to electrostatically bind metal ions. Following this activation step, chemical reduction and electroless plating produces metal clusters of several nanometers in diameter. The clusters are attached to the virion without destroying its structure. Gold clusters generated from an ascorbic acid bath bind to the exterior surface as well as to the central channel of the hollow tube. Very high selectivity is reached by tuning PdII and PtII activations with phosphate: When TMV is first activated with PdII, and thereafter metallized with a nickel–phosphinate bath, 3 nm nickel clusters grow in the central channel; when TMV from phosphate-buffered suspensions is employed, larger nickel clusters grow on the exterior surface. Phosphate buffers have to be avoided when 3 nm nickel and cobalt wires of several 100 nm in length are synthesized from borane-based baths inside the TMV channel. The results are discussed with respect to the inorganic complex chemistry of precursor molecules and the distribution of binding sites in TMV.

Selective Catalytic Oxidation of CH Bonds with Molecular Oxygen

Abstract: Although catalytic reductions, cross-couplings, metathesis, and oxidation of CC double bonds are well established, the corresponding catalytic hydroxylations of CH bonds in alkanes, arenes, or benzylic (allylic) positions, particularly with O2, the cheapest, “greenest”, and most abundant oxidant, are severely lacking. Certainly, some promising examples in homogenous and heterogenous catalysis exist, as well as enzymes that can perform catalytic aerobic oxidations on various substrates, but these have never achieved an industrial-scale, owing to a low space-time-yield and poor stability. This review illustrates recent advances in aerobic oxidation catalysis by discussing selected examples, and aims to stimulate further exciting work in this area. Theoretical work on catalyst precursors, resting states, and elementary steps, as well as model reactions complemented by spectroscopic studies provide detailed insight into the molecular mechanisms of oxidation catalyses and pave the way for preparative applications. However, O2 also poses a safety hazard, especially when used for large scale reactions, therefore sophisticated methodologies have been developed to minimize these risks and to allow convenient transfer onto industrial scale.

Convolutional Neural Network for Paraphrase Identification

Abstract: We present a new deep learning architecture Bi-CNN-MI for paraphrase identification (PI). Based on the insight that PI requires comparing two sentences on multiple levels of granularity, we learn multigranular sentence representations using convolutional neural network (CNN) and model interaction features at each level. These features are then the input to a logistic classifier for PI. All parameters of the model (for embeddings, convolution and classification) are directly optimized for PI. To address the lack of training data, we pretrain the network in a novel way using a language modeling task. Results on the MSRP corpus surpass that of previous NN competitors.

Efficient memory representation of XML documents

Abstract: Implementations that load XML documents and give access to them via, e.g., the DOM, suffer from huge memory demands: the space needed to load an XML document is usually many times larger than the size of the document. A considerable amount of memory is needed to store the tree structure of the XML document. Here a technique is presented that allows to represent the tree structure of an XML document in an efficient way. The representation exploits the high regularity in XML documents by “compressing” their tree structure; the latter means to detect and remove repetitions of tree patterns. The functionality of basic tree operations, like traversal along edges, is preserved in the compressed representation. This allows to directly execute queries (and in particular, bulk operations) without prior decompression. For certain tasks like validation against an XML type or checking equality of documents, the representation allows for provably more efficient algorithms than those running on conventional representations.

Self-propulsion of a catalytically active particle near a planar wall: from reflection to sliding and hovering.

Abstract: Micron-sized particles moving through a solution in response to self-generated chemical gradients serve as model systems for studying active matter. Their far-reaching potential applications will require the particles to sense and respond to their local environment in a robust manner. The self-generated hydrodynamic and chemical fields, which induce particle motion, probe and are modified by that very environment, including confining boundaries. Focusing on a catalytically active Janus particle as a paradigmatic example, we predict that near a hard planar wall such a particle exhibits several scenarios of motion: reflection from the wall, motion at a steady-state orientation and height above the wall, or motionless, steady “hovering.” Concerning the steady states, the height and the orientation are determined both by the proportion of catalyst coverage and the interactions of the solutes with the different “faces” of the particle. Accordingly, we propose that a desired behavior can be selected by tuning these parameters via a judicious design of the particle surface chemistry.