Synthesis and Microstructural Investigations of Organometallic Pd(II) Thiol-Gold Nanoparticles Hybrids

In this work the synthesis and characterization of gold nanoparticles functionalized by a novel thiol-organometallic complex containing Pd(II) centers is presented. Pd(II) thiol, trans, trans-[dithiolate-dibis(tributylphosphine)dipalladium(II)-4,4′-diethynylbiphenyl] was synthesized and linked to Au nanoparticles by the chemical reduction of a metal salt precursor. The new hybrid made of organometallic Pd(II) thiol-gold nanoparticles, shows through a single S bridge a direct link between Pd(II) and Au nanoparticles. The size-control of the Au nanoparticles (diameter range 2–10 nm) was achieved by choosing the suitable AuCl₄ ⁻/thiol molar ratio. The size, strain, shape, and crystalline structure of these functionalized nanoparticles were determined by a full-pattern X-ray powder diffraction analysis, high-resolution TEM, and X-ray photoelectron spectroscopy. Photoluminescence spectroscopy measurements of the hybrid system show emission peaks at 418 and 440 nm. The hybrid was exposed to gaseous NO _x with the aim to evaluate the suitability for applications in sensor devices; XPS measurements permitted to ascertain and investigate the hybrid –gas interaction.     

FUNCTION AND ACTION OF OPACIFIERS1

The causes of opacification and the function of opacifiers in white ware glazes are discussed briefly. The relative covering power of tin oxide is shown to be greater than that of zircon oxide under the same conditions. The fluidity of the glaze is affected by the amount of opacifier used and can be controlled in commercial practice by the use of a simple inclined testing block.     

A numerical study of flow boiling in a microchannel using the local front reconstruction method

The rapid advances in performance and miniaturization of electronic devices require a cooling technology that can remove the produced heat at a high rate with small temperature variations, as is obtained in flow boiling. To obtain insight in flow boiling, we performed numerical simulations in a 200 μm square microchannel using the local front reconstruction method. Besides validation with literature results, a parametric study shows an increasing heat removal rate and bubble growth rate with increasing wall temperature, liquid mass density, and liquid heat capacity and decreasing inlet velocity indicating the importance of phase change compared to convective transport. Finally, the heat transfer in the liquid film is studied using a Nusselt number defined with the film thickness, which is comparable to Nusselt number for falling films on hot surfaces. It is observed that convective effects are more pronounced at the bubble rear compared to the bubble front.     

On Codes, Matroids, and Secure Multiparty Computation From Linear Secret-Sharing Schemes

Error-correcting codes and matroids have been widely used in the study of ordinary secret sharing schemes. In this paper, the connections between codes, matroids, and a special class of secret sharing schemes, namely, multiplicative linear secret sharing schemes (LSSSs), are studied. Such schemes are known to enable multiparty computation protocols secure against general (nonthreshold) adversaries. Two open problems related to the complexity of multiplicative LSSSs are considered in this paper. The first one deals with strongly multiplicative LSSSs. As opposed to the case of multiplicative LSSSs, it is not known whether there is an efficient method to transform an LSSS into a strongly multiplicative LSSS for the same access structure with a polynomial increase of the complexity. A property of strongly multiplicative LSSSs that could be useful in solving this problem is proved. Namely, using a suitable generalization of the well-known Berlekamp-Welch decoder, it is shown that all strongly multiplicative LSSSs enable efficient reconstruction of a shared secret in the presence of malicious faults. The second one is to characterize the access structures of ideal multiplicative LSSSs. Specifically, the considered open problem is to determine whether all self-dual vector space access structures are in this situation. By the aforementioned connection, this in fact constitutes an open problem about matroid theory, since it can be restated in terms of representability of identically self-dual matroids by self-dual codes. A new concept is introduced, the flat-partition, that provides a useful classification of identically self-dual matroids. Uniform identically self-dual matroids, which are known to be representable by self-dual codes, form one of the classes. It is proved that this property also holds for the family of matroids that, in a natural way, is the next class in the above classification: the identically self-dual bipartite matroids.     

Effective feature construction by maximum common subgraph sampling

The standard approach to feature construction and predictive learning in molecular datasets is to employ computationally expensive graph mining techniques and to bias the feature search exploration using frequency or correlation measures. These features are then typically employed in predictive models that can be constructed using, for example, SVMs or decision trees. We take a different approach: rather than mining for all optimal local patterns, we extract features from the set of pairwise maximum common subgraphs. The maximum common subgraphs are computed under the block-and-bridge-preserving subgraph isomorphism from the outerplanar examples in polynomial time. We empirically observe a significant increase in predictive performance when using maximum common subgraph features instead of correlated local patterns on 60 benchmark datasets from NCI. Moreover, we show that when we randomly sample the pairs of graphs from which to extract the maximum common subgraphs, we obtain a smaller set of features that still allows the same predictive performance as methods that exhaustively enumerate all possible patterns. The sampling strategy turns out to be a very good compromise between a slight decrease in predictive performance (although still remaining comparable with state-of-the-art methods) and a significant runtime reduction (two orders of magnitude on a popular medium size chemoinformatics dataset). This suggests that maximum common subgraphs are interesting and meaningful features.     

Kraftstoffersparnis durch Hochleistungswerkstoffe

Fuel Saving by the Use of High‐Performance Materials Due to new European regulations efficiency of modern automobiles has to be increased. Two possible ways to achieve a reduction of fuel consumption are weight reduction by light metals like aluminium and use of coatings to reduce friction losses and enable new efficient working points. An example which combines both ways is the engine of a modern automobile. More and more light alloys like AlSi are used to reduce the engine weight. Furthermore, coatings are used to maximise the weight reduction and to increase the efficiency. Thus, thermal spraying is used to avoid wear on the aluminium bores and thin coatings on piston rings deposited by means of Physical Vapour Deposition (PVD) decrease the friction losses and allow low wear within this tribological contact.