DECOMPOSITION PRODUCTS OF TRINUCLEAR RUTHENIUM COMPLEXES AS EFFECTIVE CATALYSTS OF WATER OXIDATION

Ruthenium red, a di-mu-oxo-bridged ruthenium complex, and its oxidised form, ruthenium brown, have been studied as possible homogeneous redox catalysts for the oxidation of water to O2 by Ce(IV) ions in H2SO4 and HCIO4. In both media the Ce(IV) ions oxidised the ruthenium red to brown and, with excess of Ce(IV), decomposed the ruthenium brown irreversibly to product(s) with three weak absorption bands at 390, 523 and 593 nm. Only in HCIO4 did the decomposition product(s) appear to act as a stable O2 catalyst. Spectral evidence tentatively suggests that the active catalyst may be a hydrolysed Ru(IV) polymeric species. The rate of catalysis was proportional to the initial concentration of ruthenium red/brown and the activation energy was determined as 36 +/- 1 kJ mol-1 over the temperature range ambient to ca. 50-degrees-C. At temperatures greater than 50-degrees-C the O2 catalyst undergoes an irreversible thermal decomposition reaction.

Automatic decomposition and efficient semi-structured meshing of complex solids

In this paper, a novel approach to automatically sub-divide a complex geometry and apply an efficient mesh is presented. Following the identification and removal of thin-sheet regions from an arbitrary solid using the thick/thin decomposition approach developed by Robinson et al. [1], the technique here employs shape metrics generated using local sizing measures to identify long-slender regions within the thick body. A series of algorithms automatically partition the thick region into a non-manifold assembly of long-slender and complex sub-regions. A structured anisotropic mesh is applied to the thin-sheet and long-slender bodies, and the remaining complex bodies are filled with unstructured isotropic tetrahedra. The resulting semi-structured mesh possesses significantly fewer degrees of freedom than the equivalent unstructured mesh, demonstrating the effectiveness of the approach. The accuracy of the efficient meshes generated for a complex geometry is verified via a study that compares the results of a modal analysis with the results of an equivalent analysis on a dense tetrahedral mesh.

Epitaxial Magnetic Oxide Nanocrystals Via Phase Decomposition of Bismuth Perovskite Precursors

The phase instability of bismuth perovskite (BiMO₃), where M is a ferromagnetic cation, is exploited to create self-assembled magnetic oxide nanocrystal arrays on oxide supports. Conditions during pulsed laser deposition are tuned so as to induce complete breakdown of the perovskite precursor into bismuth oxide (Bi₂ O₃ ) and metal oxide (M-O_x ) pockets. Subsequent cooling in vacuum volatizes the Bi₂ O₃ leaving behind an array of monodisperse nanocrystals. In situ reflective high energy electron diffraction beam is exploited to monitor the synthesis in real-time. Analysis of the patterns confi rms the phase separation and volatization process. Successful synthesis of M-O_x, where M = Mn, Fe, Co, and Cr, is shown using this template-free facile approach. Detailed magnetic characterization of nanocrystals is carried out to reveal the functionalities such as magnetic anisotropy as well as larger than bulk moments, as expected in these oxide nanostructures.

DRIFTS/MS/Isotopic Labeling Study on the NO-Moderated Decomposition of a Silica-Supported Nickel Nitrate Catalyst Precursor

In the preparation of silica-supported nickel oxide from nickel nitrate impregnation and drying, the replacement of the traditional air calcination step by a thermal treatment in 1% NO/Ar prevents agglomeration, resulting in highly dispersed NiO. The mechanism by which NO prevents agglomeration was investigated by using combined in situ diffuse reflectance infrared fourier transform (DRIFT) spectroscopy and mass spectrometry (MS). After impregnation and drying, a supported nickel hydroxynitrate phase with composition Ni(3)(NO(3))(2)(OH)(4) had been formed. Comparison of the evolution of the decomposition gases during the thermal decomposition of Ni(3)(NO(3))(2)(OH)(4) in labeled and unlabeled NO and O(2) revealed that NO scavenges oxygen radicals, forming NO(2). The DRIFT spectra revealed that the surface speciation evolved differently in the presence of NO as compared with in O(2) or Ar. It is proposed that oxygen scavenging by NO depletes the Ni(3)(NO(3))(2)(OH)(4) phase of nitrate groups, creating nucleation sites for the formation of NiO, which leads to very small (similar to 4 nm) NiO particles and prevents agglomeration.

Chemisorption and decomposition of pyrrole on Pd{111}

XPS, TPD and HREEL results indicate that molecular pyrrole is a fragile adsorbate on clean Pd{111}. At 200 K and for low coverages, the molecule remains intact and adopts an almost flat-lying geometry. With increasing coverage, pyrrole molecules tilt away from the surface and undergo N-H bond cleavage to form strongly tilted pyrrolyl (C4H4N) species. In addition, a weakly bound, strongly tilted form of molecular pyrrole is observed at coverages approaching saturation. Heating pyrrole monolayers results in desorption of similar to 15% of the overlayer as molecular pyrrole and N-a+ C4H4Na recombination with formation of hat-lying pyrrole molecules. This strongly bound species undergoes decomposition to adsorbed CN, CHx and H, leading ultimately to desorption of HCN and H-2. The implications of these results for the production of pyrrole by a heterogeneously catalysed route are discussed.

The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results. © 1964-2012 IEEE.

The Forgiving Graph: a distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick “repairs,” which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions, without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been l in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most l log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degree would have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network.

The Forgiving Graph:A distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick "repairs," which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions,without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been - in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most - log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degreewould have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network. © Springer-Verlag 2012.