Structure and spectra of dichloro(hydroxy-methoxy-di(2-pyridyl)methane)copper(II)

The non-electrolyte dichloro(hydroxy-methoxy-di(2-pyridylmethane)copper(II), resulting from the reaction of di(2-pyridyl)ketone and copper(II) chloride in methanol solution, was isolated and characterized and its structure was determined by X-ray diffraction. The pyridyl nitrogens and the chloride anions virtually from a basal plane in which lies the copper atom, while the oxygen of the methoxy group is in an apical position at a distance of 2.497 (3)Å. The nitrogenous base adopts the boat conformation with the pyridyl rings forming a dihedral angle of 108.72 (14)°. The nearest interatomic copper distance of 3.940(3)Å precludes copper-copper interactions, while the proximity of copper to the out-of-plane chlorine atoms [3.109(3)Å] suggests weakly bound chloro-bridged dimers. Spectral changes indicate that protic molecules displace the methoxy group and water affords the corresponding 1,1-diol.

Synthesis and X-ray crystal structure of the copper(I) dicarboxylic acid complex [Cu(η1-bdoaH)(PPh3)3] (bdoaH2 = benzene-1,2- dioxyacetic acid)

The copper(II) complex [Cu(bdoa)(H2O)2] (bdoaH2 = benzene-1,2-dioxyacetic acid) reacts with triphenylphosphine (1:4 mol ratio) to give the colourless copper(I) complex [Cu(η1-bdoaH)(PPh3)3] (1) in good yield. The X-ray crystal structure of the complex shows the copper atom at the centre of a distorted tetrahedron, and is ligated by the phosphorus atoms of the three triphenylphosphines and one carboxylate oxygen atom of the bdoaH− ligand. Significant intermolecular hydrogen-bonding exists between the pendant carboxylate OH function of one molecule and the uncoordinated “ketonic” oxygen of a neighbouring molecule. Complex 1 is non-conducting in chloroform but ionizes readily in acetonitrile. The cyclic voltammogram of an acetonitrile solution of 1 shows a single irreversible anodic peak for the oxidation of the PPh3 ligands and the copper(I) centre, and a single irreversible cathodic peak for the reduction of the bdoaH− ion. IR and mass spectral data for 1 are given.

Influence of hydrogen bonding in the structure of mixed-ligand copper(II) chelates. Spectra and structure of [aquo((2,2'-dipyridylamine)-(3-chloro-2,4-pentanedionato)copper(II)] nitrate

The IR, the ligand field spectra and the crystal structure of the mixed-ligand compound [(aquo)2,2P1 , a = 8.718(5), b = 9.407(5), c = 13.484 (7) Å, = 94.17(4)°, = 105.12(5)°, = 119.75(5)°, Z = 2, R = 0.0332, R W = 0.0869).

Copper(II) complexes of benzene-1,2-dioxyacetic acid (bdoaH2): X-ray crystal structure of [Cu2(bdoa)(phen)4]bdoa·13H2O (phen = 1,10-phenanthroline)

Copper(II) acetate reacts with benzene-1,2-dioxyacetic acid (bdoaH2) in aqueous media to give [Cu(bdoa)(H2O)2] (1). Complex 1 reacts with the N-donor ligands pyridine (py), ammonia and 1,10-phenanthroline (phen) to give [Cu(bdoa)(NH3)2]·H2O (2), [Cu(bdoa)(py)2]·H2O (3) and [Cu2(bdoa)(phen)4]bdoa·13H2O (4), respectively. The X-ray crystal structure of the dicopper(II,II) complex 4 shows each copper atom at the centre of a distorted trigonal bipyramid comprising four nitrogen atoms from two chelating phen ligands and a single oxygen atom from one of the carboxylate moieties of the bridging bdoa2− ligand. The cyclic voltammogram of 4 shows a single reversible wave for the Cu2+/Cu+ couple at E = + 115 mV (vs Ag/AgCl). Spectroscopic and magnetic data for the complexes are given.

Reaction of (±)-1,1′-binaphthyl-2,2′-diyl hydrogen phosphate {(±)-phosH} with copper(II), cobalt(II) and iron(II) compounds; Identification by x-ray diffraction of [Co(CH3OH)4(H2O)2][(+)-phos][(−)-phos]. 2CH3OH·H2O

[Cu2(μO2CCH3)4(H2O)2], [CuCO3·Cu(OH)2], [CoSO4·7H2O], [Co((+)-tartrate)], and [FeSO4·7H2O] react with excess racemic (±)- 1,1′-binaphthyl-2,2′-diyl hydrogen phosphate {(±)-PhosH} to give mononuclear CuII, CoII and FeII products. The cobalt product, [Co(CH3OH)4(H2O)2]((+)-Phos)((−)-Phos) ·2CH3OH·H2O (7), has been identified by X-ray diffraction. The high-spin, octahedral CoII atom is ligated by four equatorial methanol molecules and two axial water molecules. A (+)- and a (−)-Phos− ion are associated with each molecule of the complex but are not coordinated to the metal centre. For the other CoII, CuII and FeII samples of similar formulation to (7) it is also thought that the Phos− ions are not bonded directly to the metal. When some of the CuII and CoII samples are heated under high vacuum there is evidence that the Phos− ions are coordinated directly to the metals in the products.

Understanding the early stages of the innovation diffusion process: awareness, influence and communication networks

The themes of awareness and influence within the innovation diffusion process are addressed. The innovation diffusion process is typically represented as stages, yet awareness and influence are somewhat under-represented in the literature. Awareness and influence are situated within the contextual setting of individual actors but also within the broader institutional forces. Understanding how actors become aware of an innovation and then how their opinion is influenced is important for creating a more innovation-active UK construction sector. Social network analysis is proposed as one technique for mapping how awareness and influence occur and what they look like as a network. Empirical data are gathered using two modes of enquiry. This is done through a pilot study consisting of chartered professionals and then through a case study organization as it attempted to diffuse an innovation. The analysis demonstrates significant variations across actors’ awareness and influence networks. It is argued that social network analysis can complement other research methods in order to present a richer picture of how actors become aware of innovations and where they draw their influences regarding adopting innovations. In summarizing the findings, a framework for understanding awareness and influence associated with innovation within the UK construction sector is presented. Finally, with the UK construction sector continually being encouraged to be innovative, understanding and managing an actor’s awareness and influence network will be beneficial. The overarching conclusion thus describes the need not only to build research capacity in this area but also to push the boundaries related to the research methods employed.

Attention through self-synchronisation in the spiking neuron stochastic diffusion network

The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusin on Search, SDS, a non-deterministic search algorithm able to rapidly locate the best instantiation of a target pattern within a noisy search space ([3], [5]). In SNSDN, relevant information is encoded in the length of interspike intervals. Although every neuron operates in its own time, ‘attention’ to a pattern in the search space results in self-synchronised activity of a large population of neurons. When multiple patterns are present in the search space, ‘switching of at- tention’ results in a change of the synchronous activity. The qualitative effect of attention on the synchronicity of spiking behaviour in both time and frequency domain will be discussed.

Time complexity analysis of the stochastic diffusion search

The Stochastic Diffusion Search algorithm -an integral part of Stochastic Search Networks is investigated. Stochastic Diffusion Search is an alternative solution for invariant pattern recognition and focus of attention. It has been shown that the algorithm can be modelled as an ergodic, finite state Markov Chain under some non-restrictive assumptions. Sub-linear time complexity for some settings of parameters has been formulated and proved. Some properties of the algorithm are then characterised and numerical examples illustrating some features of the algorithm are presented.

Dynamic analysis of house price diffusion across Asian financial centres

The aim of this paper is to explore effects of macroeconomic variables on house prices and also, the lead-lag relationships of real estate markets to examine house price diffusion across Asian financial centres. The analysis is based on the Global Vector Auto-Regression (GVAR) model estimated using quarterly data for six Asian financial centres (Hong Kong, Tokyo, Seoul, Singapore, Taipei and Bangkok) from 1991Q1 to 2011Q2. The empirical results indicate that the global economic conditions play significant roles in shaping house price movements across Asian financial centres. In particular, a small open economy that heavily relies on international trade such as – Singapore and Tokyo - shows positive correlations between economy’s openness and house prices, consistent with the Balassa-Samuelson hypothesis in international trade. However, region-specific conditions do play important roles as determinants of house prices, partly due to restrictive housing policies and demand-supply imbalances, as found in Singapore and Bangkok.

Establishing a connection between knowledge transfer and innovation diffusion

Successful innovation diffusion process may well take the form of knowledge transfer process. Therefore, the primary objectives of this paper include: first, to evaluate the interrelations between transfer of knowledge and diffusion of innovation; and second to develop a model to establish a connection between the two. This has been achieved using a four-step approach. The first step of the approach is to assess and discuss the theories relating to knowledge transfer (KT) and innovation diffusion (ID). The second step focuses on developing basic models for KT and ID, based on the key theories surrounding these areas. A considerable amount of literature has been written on the association between knowledge management and innovation, the respective fields of KT and ID. The next step, therefore, explores the relationship between innovation and knowledge management in order to identify the connections between the latter, i.e. KT and ID. Finally, step four proposes and develops an integrated model for KT and ID. As the developed model suggests the sub-processes of knowledge transfer can be connected to the innovation diffusion process in several instances as discussed and illustrated in the paper.

Mixed copper, silver, and gold cyanides, (MxM′1–x)CN: tailoring chain structures to influence physical properties

Binary mixed-metal variants of the one-dimensional MCN compounds (M = Cu, Ag, and Au) have been prepared and characterized using powder X-ray diffraction, vibrational spectroscopy, and total neutron diffraction. A solid solution with the AgCN structure exists in the (CuxAg1–x)CN system over the range (0 ≤ x ≤ 1). Line phases with compositions (Cu1/2Au1/2)CN, (Cu7/12Au5/12)CN, (Cu2/3Au1/3)CN, and (Ag1/2Au1/2)CN, all of which have the AuCN structure, are found in the gold-containing systems. Infrared and Raman spectroscopies show that complete ordering of the type [M–C≡N–M′–N≡C−]n occurs only in (Cu1/2Au1/2)CN and (Ag1/2Au1/2)CN. The sense of the cyanide bonding was determined by total neutron diffraction to be [Ag–NC–Au–CN−]n in (Ag1/2Au1/2)CN and [Cu–NC–Au–CN−]n in (Cu1/2Au1/2)CN. In contrast, in (Cu0.50Ag0.50)CN, metal ordering is incomplete, and strict alternation of metals does not occur. However, there is a distinct preference (85%) for the N end of the cyanide ligand to be bonded to copper and for Ag–CN–Cu links to predominate. Contrary to expectation, aurophilic bonding does not appear to be the controlling factor which leads to (Cu1/2Au1/2)CN and (Ag1/2Au1/2)CN adopting the AuCN structure. The diffuse reflectance, photoluminescence, and 1-D negative thermal expansion (NTE) behaviors of all three systems are reported and compared with those of the parent cyanide compounds. The photophysical properties are strongly influenced both by the composition of the individual chains and by how such chains pack together. The NTE behavior is also controlled by structure type: the gold-containing mixed-metal cyanides with the AuCN structure show the smallest contraction along the chain length on heating.

Copper deposition on TiO2 from copper(II)hexafluoroacetylacetonate

The authors have studied the adsorption of CuII(hfac)2 on the surface of a model oxide system, TiO2(110), and probed the molecular stability with respect to thermal cycling, using atomic scale imaging by scanning tunneling microscopy supported by x-ray photoemission spectroscopy. They find that at 473 K, the adsorbed metal-organic molecules begin to dissociate and release Cu atoms which aggregate and form Cu nanoparticles. These Cu nanoparticles ripen over time and the size (height) distribution develops into a bimodal distribution. Unlike other organometallic systems, which show a bimodal distribution due to enhanced nucleation or growth at surface step edges, the nanoparticles do not preferentially form at steps. The reduced mobility of the Cu islands may be related to the co-adsorbed ligands that remain in very small clusters on the surface.