Structural characterization of rare intramolecularly (1,4-Te· · ·N) bonded diorganotellurides and their monomeric complexes with mercury(II) halides: metal assisted C-H· · ·X (Hg) interactions leading to supramolecular architecture

Monomeric tellurides 4-RC₆H₄(SB)Te [SB = 2-(4,4'-N0₂C₆H₄CH=NC₆H₃-Me); R = H, 1a; Me,1b; OMe, 1c], which incidentally represent the first example of a telluride with 1,4-Te···N intramolecular interaction, have been prepared and characterized by solution and solid-state ¹²⁵Te NMR, ¹³C NMR and X-ray crystallography. Interplay of weak C-H···O and C-H-··π{ interactions in the crystal lattice of 1b and1c are responsible for the formation of supramolecular motifs. These tellurides undergo expected oxidative addition reactions with halogens and interhalogens and also interact coordinatively with mercury(II) halides to give 1:2 complexes, HgX₂[4-RC₆H₄(SB)Te]₂ (X = CI, R = H, 2a; Me, 2b; OMe, 2c and X = Br, R = H, 3a; Me, 3b; and OMe, 3c) with no sign of Te-C bond cleavage, as has been reported for some 1,5-Te·· ·N(O) intramolecularly bonded tellurides. The complexes 2a and 3c are the first structurally characterized monomeric 1:2 adducts of mercury(II) halides with Te ligands. The 1,4-Te···N intramolecular interactions in the solid-state are retained in the complexes highlighting simultaneously the Lewis acid and base character of the Te(lI) atom. Packing of molecules in the crystal lattice of 2a
and 3c reveals that non-covalent C-H· . ·Cl/Br interactions involving metal-bound halogen atoms possess significant directionality and in
combination with coordinative covalent interactions may be of potential use in creating inorganic supramolecular synthons.

Analytic prediction of structural stress-strain relations of microstructured metal

Nanostructured and ultra-fine grained metals have higher strength but extremely limited ductility compared to coarse grained metals. However, their ductility can be greatly improved by introducing a specific range of grain sizes in the microstructures. In the paper, multiscale unit cell approach (UCA) is developed and applied to predict the averaged stress-strain relations of the multiscale microstructure metals. The unit cell models are three-phase structured at different scale lengths of 100 nm, 1 μm and 10 μm with different volume fractions and periodic boundary conditions. The contributions of multi-scale microstructures to the macroscopic structural properties of metals are also studied using a analytic approach—two-step mean-field method (TSMF), where three microstructural parameters are introduced and thus mechanical properties such as strength and ductility are presented as a function of these parameters. For verification of these proposed numerical and theoretical algorithms, the structural properties of the pure nickel with three-grain microstructures are studied and the results from FEA and the proposed theory have good agreement.

The Influence of water and metal salt on the transport and structural properties of 1-Octyl-3-methylimidazolium Chloride

The addition of diluents to ionic liquids (ILs) has recently been shown to enhance the transport properties of ILs. In the context of electrolyte design, this enhancement allows the realisation of IL-based electrolytes for metal-air batteries and other storage devices. It is likely that diluent addition not only impacts the viscosity of the IL, but also the ion-ion interactions and structure. Here, we investigate the nano-structured 1-methyl-3-octylimidazolium chloride (OMImCl) with varying water concentrations in the presence of two metal salts, zinc chloride and magnesium chloride. We find that the choice of metal salt has a significant impact on the structure and transport properties of the system; this is explained by the water structuring and destructing properties of the metal salt.

Metal and metalloid containing natural products and a brief overview of their applications in biology, biotechnology and biomedicine

Bioinorganic natural product chemistry is a relatively unexplored but rapidly developing field with enormous potential for applications in biology, biotechnology (especially in regards to nanomaterial development, synthesis and environmental cleanup) and biomedicine. In this review the occurrence of metals and metalloids in natural products and their synthetic derivatives are reviewed. A broad overview of the area is provided followed by a discussion on the more common metals and metalloids found in natural sources, and an overview of the requirements for future research. Special attention is given to metal hyperaccumulating plants and their use in chemical synthesis and bioremediation, as well as the potential uses of metals and metalloids as therapeutic agents. The potential future applications and development in the field are also discussed.

Cleavage of Ru-C(aryl) bond of a four-membered ortho-metalated ruthenium(II) organometallics by mercaptopyrimidine and pyridine-2,6-dicarboxylate ligands: spectroscopic, structural and computational studies

The heterogeneous phase reaction of Ru(η2-RL)(PPh3)2(CO)Cl (1) with 2-mercaptopyrimidine(pymSH) and pyridine-2,6-dicarboxylate(dipic) ligands afforded the complexes of the type Ru(PPh3)(CO)(pymS)2 (2) and Ru(PPh3)2(CO)(dipic) (3) in excellent yield respectively. The chelation of pymS/dipic is attended with the cleavage of Ru-O, Ru-Cl and Ru-C(aryl) bonds and the RL ligand is no longer coordinated with the metal center in the products. The spectral (UV-Vis, IR, 1H NMR) and electrochemical data of the complexes are included. In dichloromethane solution both 2 and 3 display one quasi-reversible RuIII/RuII cyclic voltammetric response with E1/2 in the range 1.15-1.50 V vs Ag/AgCl. Structure determinations of 2 and the solvate 3·CH3CN have revealed distorted octahedral RuCN2S2P coordination sphere for 2 and RuCNO2P2 coordination sphere for 3·CH3CN. For 2 the pairs (P, N), (S, S) and (C, N) define the three trans directions whereas for 3·CH3CN those pairs are (P, P), (C, N) and (O, O). The electronic structures and the absorption spectra of 2 and 3 are also scrutinized by the density functional theory (DFT) and time-dependent density functional theory (TD-DFT) analysis.

Arsenic and heavy metal contamination of vegetables grown in Samta village, Bangladesh

Drinking of arsenic (As) contaminated well water has become a serious threat to the health of many millions in Bangladesh. However, the implications of contamination of agricultural soils from long-term irrigation with As-contaminated groundwater for phyto-accumulation in food crops, and thence dietary exposure to As, and other metals, has not been assessed previously in Bangladesh. Various vegetables were sampled in Samta village in the Jessore district of Bangladesh, and screened for As, Cd, Pb, Cu and Zn by inductively coupled plasma emission spectrometry (ICP-AES) and inductively coupled plasma mass spectrometry (ICP-MS). These local food products are the basis of human nutrition in this region and of great relevance to human health. The results revealed that the individual vegetables containing the highest mean As concentrations (μg g⁻¹) are snake gourd (0.489), ghotkol (0.446), taro (0.440), green papaya (0.389), elephant foot (0.338) and Bottle ground leaf (0.306), respectively. The As concentration in fleshy vegetable material is low. In general, the data show the potential for some vegetables to accumulate heavy metals with concentrations of Pb greater than Cd. Some vegetables such as bottle ground leaf, ghotkol, taro, eddoe and elephant foot had much higher concentrations of Pb. Other leafy and root vegetables, contained higher concentrations of Zn and Cu. Bioconcentration factors (BCF) values, based on dry weight, were below 1 for all metals. In most cases, BCF values decreased with increasing metal concentrations in the soil. From the heavily As-contaminated village in Samta, BCF values for As in ladies finger, potato, ash gourd, brinjal, green papaya, ghotkol and snake gourd were 0.001, 0.006, 0.006, 0.014, 0.030, 0.034 and 0.038, respectively. Considering the average daily intake of fresh vegetables per person per day is only 130 g, all the vegetables grown at Samta had Pb concentrations that would be a health hazard for human consumption. Although the total As in the vegetables was less than the recommended maximum intake of As, it still provides a significant additional source of As in the diet.

The effect of clamping sequence on dimensional variability in sheet metal assembly

Finite element (FE) modelling techniques have become a popular tool for exploring welding and clamping sequence dependence in sheet metal assemblies. In the current paper, the dimensional variability associated with different assembly clamping sequences is investigated with a FE contact modelling approach implemented in the commercial code Abaqus. A simplified channel section assembly consisting of a top hat and bottom plate is the case study investigated. Expected variation modes of bow and twist were used to simulate key variability sources in the main structural component under investigation; the top hat of the channel section. It was found that final assembly variability can change considerably depending on clamp sequence selection. It was also found that different clamp sequences can control particular modes of variation better than others, and that there is not one particular clamping sequence that is the best for containing all variation modes. An adaptable assembly process is therefore suggested, where given the shape of input components the best available clamping sequence is selected. Comparison of the performance of the proposed adaptable clamping sequence to traditional fixed clamping sequences shows improvements for the dimensional control of variability in non-rigid components. While introducing such a method in production would require inspection of each component being assembled and investigation of the alternative clamping sequences, given access to fast and detailed dimensional inspection technology such as optical coordinate measuring machines (OCMM's), the approach shows promise for future application.

Green products and corporate strategy : an empirical investigation

Purpose – The purpose of the study is to examine the influence of multiple factors on the green purchase intention of customers in Australia.

Design/methodology/approach – A conceptual model is proposed and was subjected to empirical verification with the use of a survey of metropolitan and regional households in Victoria, Australia. The data were analyzed using both descriptive measures and exploratory factor analysis to identify and validate the items contributing to each component in the model. AMOS structural modeling was used to estimate the measure of respondents' overall perception of green products and their intention to purchase.

Findings – The results indicate that customers' corporate perception with respect to companies placing higher priority on profitability than on reducing pollution and regulatory protection were the significant predictors of customers' negative overall perception toward green products. The only positive contribution to customers' perception was their past experience with the product. Other factors including the perception of green products, product labels, packaging, and product ingredients did not appear to influence customers' perception. The results also indicate that customers are not tolerant of lower quality and higher prices of green products.

Research limitations/implications – The knowledge of the overall perception formation about green products and its predictors provides management with the facility to identify and implement strategies that may better influence the change of attitude by customers. Corporations can also benefit from the identification of the types of information required to enable management to influence this process of perception formation.

Originality/value – The present findings contributes to an understanding of the antecedents of green purchasing and highlight that green customers rely more on personal experience with the product than the information provided by the marketer.

Focusing in on structural genomics : the University of Queensland structural biology pipeline

The flood of new genomic sequence information together with technological innovations in protein structure determination have led to worldwide structural genomics (SG) initiatives. The goals of SG initiatives are to accelerate the process of protein structure determination, to fill in protein fold space and to provide information about the function of uncharacterized proteins. In the long-term, these outcomes are likely to impact on medical biotechnology and drug discovery, leading to a better understanding of disease as well as the development of new therapeutics. Here we describe the high throughput pipeline established at the University of Queensland in Australia. In this focused pipeline, the targets for structure determination are proteins that are expressed in mouse macrophage cells and that are inferred to have a role in innate immunity. The aim is to characterize the molecular structure and the biochemical and cellular function of these targets by using a parallel processing pipeline. The pipeline is designed to work with tens to hundreds of target gene products and comprises target selection, cloning, expression, purification, crystallization and structure determination. The structures from this pipeline will provide insights into the function of previously uncharacterized macrophage proteins and could lead to the validation of new drug targets for chronic obstructive pulmonary disease and arthritis.

Electrochemical and spectroscopic investigation of redox processes for labile metal dithiocarbamate complexes

Although metal dithiocarbamate complexes have been studied extensively, there is in sate cases a distinct lack of data concerning redox properties and the products thereof. This is particularly true for complexes of the late transition and main group metals which are important in agriculture, industry, and chemical analysis. Hence, using electrochemical techniques, the redox behaviour of dithiocarbamate complexes of zinc, cadmium, mercury, lead, and tellurium has been examined. The products of oxidation and reduction have also been characterized by spectroscopic techniques (NMR, EPR, UV, and IR), mass spectrometry, conductivity, and Where possible, crystallographic study of an isolated compound. The species studied were without exception labile with the result that electrochemistry at mercury electrodes was influenced by the great stability of the mercury dithiocarbamate (Hg(RR’dtc) 2) complexes. Investigation of the latter showed that oxidative processes in the presence of mercury led to a new class of expounds: polymeric mercury dithiocarbamato cations. Oily one of these could be isolated as a solid, with the formula [Hg5(RR’dtc) 8](C104)2 For R=R’=ethyl the crystal structure was determined. For other metal dithiocarbamates the electrochemical behaviour at mercury electrodes in many ways paralleled that of the mercury analogues. Thus oxidative processes involved oxidation of electrode mercury to form mixed metal cationic species. Polarographic reduction led to the metal amalgam, usually via formation of mercury dithiocarbamate. Electrochemical studies at inert electrode materials such as platinum yielded distinctly different responses, with both oxidation and reduction being more difficult. Oxidation products at platinum electrodes gave identical polarographic responses to those firm mercury electrodes due to rapid interaction of the former with electrode mercury. The results are in sharp contrast to much of the previous work on transition metal dithiocarbamates for which electrochemical redox processes are often metal based arid not explicated by interaction with the electrode material.

Methionine regulates copper/hydrogen peroxide oxidation products of Aβ

Metal-catalysed oxidation (MCO) may play a causative role in the pathogenesis of Alzheimer's disease (AD). Amyloid peptide (A), the major biomarker of AD, in the presence of copper ions reduces Cu2+ to Cu+ and catalyses the formation of H2O2 that subsequently induces radicals through Fenton chemistry. A is also subject to attack by free radicals, where the presence of Cu2+ in conjunction with H2O2 catalyses oxygenation, primarily at the methionine sulfur atom. This work investigates MCO of A, to gain further insight into the role of oxidative stress in AD. By combining a fluorescence assay with gel electrophoresis to monitor MCO reactions of A (1-28) in the presence and absence of methionine it was determined that methionine can both protect some residues against MCO and promote the oxidation of Tyr(10) specifically. Electrospray ionization mass spectrometric analysis of methionine MCO products indicated the formation of methionine sulfoxide, methionine sulfone and related hydroxylated products. Similar products could be formed from the oxidation of Met(35) of A and may relate to changes in properties of the peptide following MCO.

Synthesis and structural diversity of rare earth anthranilate complexes

Four structural classes have been established for rare earth anthranilates, which have been prepared from the lanthanoid chloride or triflate and anthranilic acid (anthH) followed by pH adjustment to 4. [La(anth)3]n is a polymeric complex with nine coordinate lanthanum and bridging tridentate (O,O,O′) anthranilate ligands, whereas [Nd(anth)3(H2O)3] · 3H2O is monomeric with nine coordinate neodymium and solely chelating (O,O) anthranilate groups. Both chelating (O,O) and bridging bidentate (O,O′) ligands are observed in dimeric [Er2(anth)6(H2O)4] · 2H2O, in which erbium is eight coordinate and the water ligands are in a trans arrangement. A polymer is observed for [Yb(anth)3(H2O)]n with solely bridging bidentate (O,O′) ligands and seven coordination for ytterbium. The NH2 groups of the anthranilate ligands are not coordinated to the metal but is unusually involved in hydrogen-bond networks with water molecules for Ln = Er, Yb.

An investigation into transition metal ion binding properties of silk fibers and particles using radioisotopes

Silk is a structural protein fiber that is stable over a wide pH range making it attractive for use in medical and environmental applications. Variation in amino acid composition has the potential for selective binding for ions under varying conditions. Here we report on the metal ion separation potential of Mulberry and Eri silk fibers and powders over a range of pH. Highly sensitive radiotracer probes, ⁶⁴Cu²⁺, ¹⁰⁹Cd²⁺, and ⁵⁷Co²⁺ were used to study the absorption of their respective stable metal ions Cu²⁺, Cd²⁺, and Co²⁺ into and from the silk sorbents. The total amount of each metal ion absorbed and time taken to reach equilibrium occurred in the following order: Cu²⁺ > Cd²⁺ > Co ²⁺. In all cases the silk powders absorbed metal ions faster than their respective silk fibers. Intensive degumming of the fibers and powders significantly reduced the time to absorb respective metal ions and the time to reach equilibrium was reduced from hours to 5-15 min at pH 8. Once bound, 45-100% of the metal ions were released from the sorbents after exposure to pH 3 buffer for 30 min. The transition metal ion loading capacity for the silk sorbents was considerably higher than that found for commercial ion exchange resins (AG MP-50 and AG 50W-X2) under similar conditions. Interestingly, total Cu²⁺ bound was found to be higher than theoretically predicted values based on known specific Cu²⁺ binding sites (AHGGYSGY), suggesting that additional (new) sites for transition metal ion binding sites are present in silk fibers.

Characterising material and process variation effects on springback robustness for a semi-cylindrical sheet metal forming process

Variation in the incoming sheet material and fluctuations in the press setup is unavoidable in many stamping plants. The effect of these variations can have a large influence on the quality of the final stamping, in particular, unpredictable springback of the sheet when the tooling is removed. While stochastic simulation techniques have been developed to simulate this problem, there has been little research that connects the influence of the noise sources to springback. This paper characterises the effect of material and process variation on the robustness of springback for a semi-cylindrical channel forming operation, which shares a similar cross-section profile as many automotive structural components. The study was conducted using the specialised sheet metal forming package AutoForm^TM Sigma, for which a series of stochastic simulations were performed with each of the noise sources incrementally introduced. The effective stress and effective strain scatter in a critical location of the part was examined and a response window, which indicates the respective process robustness, was defined. The incremental introduction of the noise sources allows the change in size of the stressstrain response window to be tracked. The results showed that changes to process variation parameters, such as BHP and friction coefficient, directly affect the strain component of the stressstrain response window by altering the magnitude of external work applied to forming system. Material variation, on the other hand, directly affected the stress component of the response window. A relationship between the effective stressstrain response window and the variation in springback was also established.

Predicting amount of saleable products using neural network metamodels of casthouses

This study aims at developing abstract metamodels for approximating highly nonlinear relationships within a metal casting plant. Metal casting product quality nonlinearly depends on many controllable and uncontrollable factors. For improving the productivity of the system, it is vital for operation planners to predict in advance the amount of high quality products. Neural networks metamodels are developed and applied in this study for predicting the amount of saleable products. Training of metamodels is done using the Levenberg-Marquardt and Bayesian learning methods. Statistical measures are calculated for the developed metamodels over a grid of neural network structures. Demonstrated results indicate that Bayesian-based neural network metamodels outperform the Levenberg-Marquardt-based metamodels in terms of both prediction accuracy and robustness to the metamodel complexity. In contrast, the latter metamodels are computationally less expensive and generate the results more quickly.