41 resultados para tin bioaccumulation
Resumo:
The monomeric tin(II) species SnR2{R = C(SiMe3)2C5H4N-2} reacts with [Os3(H)2(CO)10] in hexane to give [Os3(µ-H)SnR(CO)10]1 quantitatively; 1 is the first formal stannyne complex of the triosmium nucleus, in which the picoline nitrogen is coordinated to the tin atom, and which is itself also reactive, being a potential precursor to high nuclearity SnOs clusters.
Resumo:
The title compound is the first µ-η2-peroxodimetallic species to be characterised for a main group metal, possessing a long peroxo O–O bond, and large C–Sn–C angles, and is an unexpected product from the oxidation of [SnR2][R = CH(SiMe3)2], with a structure analogous to an organic ozonide.
Resumo:
The stannylene [SnR2] (R = CH(SiMe3)2) reacts in different ways with the three dodecacarbonyls of the iron triad: [Fe3(CO)12] gives [Fe2(CO)8(μ-SnR2)], [Ru3(CO)12] gives the planar pentametallic cluster [Ru3(CO)10(μ-SnR2)2], for which a full structural analysis is reported, while [Os3(CO)12] fails to react. Different products are also obtained from three nitrile derivatives: [Fe3-(CO)11(MeCN)] gives [Fe2(CO)6(μ-SnR2)2], which has a structure significantly different from that of known Fe2Sn2 clusters, [Ru3(CO)10(MeCN)2] gives the pentametallic cluster described above, while [Os3(CO)10(MeCN)2] gives the isostructural osmium analogue, which shows the unusual feature of a CO group bridging two osmium atoms.
Resumo:
Cluster expansion of [Os3H2(CO)10] with [SnR2][R = CH(SiMe3)2] take place in high yield to give [Os3SnH2(CO)10R2], the first closed triosmium–main-group metal cluster to be structurally characterized; a novel feature is the presence of a hydrogen atom bridging the tin atom and one of the osmium atoms.
Resumo:
Reaction of Li(CPhCMe2) with SnCl4 or CrCl3·3thf (thf = tetrahydrofuran) affords the isoleptic compounds Sn(CPhCMe2)4 or [Cr(CPhCMe2)4] respectively. The mode of formation and chemical properties are reported for the chromium species, and the structures of the new compounds, both of which have been determined by single-crystal X-ray analysis, are described.
Resumo:
Reaction of tin(II) chloride with Li(CPhCPh2) at –78 °C in diethyl ether–hexane–tetrahydrofuran affords a deep red solution whose colour fades on warming, and which we believe contains the (unstable) first dialkenyltin(II) species. The latter survives long enough at low temperatures to undergo intermolecular oxidative addition, and one such adduct leads ultimately to the formation of Sn(CPhCPh2)3Bun, which has been fully characterised including a crystal and molecular structure study. The mechanism of formation of the final product has been examined and results are reported.
Resumo:
Two novel, monomeric heteroleptic tin(II) derivatives, [Sn{2-[(Me3Si)2C]C5H4N}R] [R = C6H2Pri3-2,4,6 1 or CH(PPh2)2 2], have been prepared, characterised by multinuclear NMR spectroscopies and their molecular structures determined by single crystal X-ray diffraction. Both compounds were prepared from the corresponding heteroleptic tin(II) chloro-analogue, [Sn{2-[(Me3Si)2C]C5H4N}Cl], and thus demonstrate the utility of this compound as a precursor to further examples of heteroleptic tin(II) derivatives: such compounds are often unstable with respect to ligand redistribution. In each case, the central tin(II) is three-co-ordinate. Crystals of trimeric [{Sn(C6H2Pri3-2,4,6)2}3] 3 were found to undergo a solid state phase transition, which may be ascribed to ordering of the ligand isopropyl groups. At 220 K the unit cell is orthorhombic, space group Pna21, compared with monoclinic, space group P21/c, for the same crystals at 298 K, in which there is an effective tripling of the now b (originally c) axis. This result illustrates the extreme crowding generated by this bulky aryl ligand.
Resumo:
Reactions of [Fe3(CO)12] with diaryltin species SnR2(R1= 2,4,6-triisopropylphenyl, R2= 2,6-diethylphenyl, R3= pentamethylphenyl) and with Sn[CH(PPh2)2]2 have been investigated. The tin reagents SnR2(R = R1 or R2) reacted under mild conditions to give in moderate yields the trinuclear species [Fe2(CO)8(µ-SnR12)]1 or [Fe2(CO)8(µ-SnR22)]2, as orange-red crystalline solids, which decompose in air on prolonged exposure. The compound [Fe2(CO)8(µ-SnR42)]3(R4= 2,4,6-triphenylphenyl) can be similarly obtained. Prolonged treatment of the carbonyl with the novel tin reagent SnR32, by contrast, afforded the known compound spiro-[(OC)8Fe2SnFe2(CO)8]4 for which data are briefly reported. Reactions with tin or lead reagents M[CH(PPh2)2]2(M = Sn or Pb) afforded [Fe2(CO)6(µ-CO)(µ-dppm)][dppm = 1,2-bis(diphenylphosphino)methane] rapidly and almost quantitatively. Full crystal and molecular structural data are reported for [Fe2(CO)8(µ-SnR12)] and [Fe2(CO)8(µ-SnR22)]. Mössbauer data are also presented for compounds 1–3, and interpreted in terms of the structural data for these and other systems.
Resumo:
Barium ferrites substituted by Mn–Sn, Co–Sn, and Mn–Co–Sn with general formulae BaFe12−2xMnxSnxO19 (x=0.2–1.0), BaFe12−2xCoxSnxO19 (x=0.2–0.8), and BaFe12−2xCox/2Mnx/2SnxO19 (x=0.1–0.6), respectively, have been prepared by a previously reported co-precipitation method. The efficiency of the method was refined by lowering the reaction temperature and shortening the required reaction time, due to which crystallinity improved and the value of saturated magnetization increased as well. Low coercivity temperature coefficients, which are adjustable by doping, were achieved by Mn–Sn and Mn–Co–Sn doping. Synthesis efficiency and the effect of doping are discussed taking into account accumulated data concerning the synthesis and crystal structure of ferrites.
Resumo:
Polychaete worms are abundant in many mudflats but their importance to coastal food web Hg biomagnification is not known. We sampled sediments and polychaete worms from mudflats in the Bay of Fundy to investigate the bioaccumulation of mercury (Hg) and methylmercury (MeHg) in the coastal invertebrate food web. Hg concentrations in the sediments were low (<20 μg kg−1). Labile Hg (methanol/KOH sediment extraction) in surface sediments (0–1 cm) was positively correlated with Hg bioaccumulation by surface sediment-ingesting polychaetes but, surprisingly, there was a negative correlation between δ15N (i.e. trophic level) and THg bioaccumulation factors in polychaete worms. Worms feeding on deeper sediments contained the greatest MeHg concentrations (69.6 μg kg−1). Polychaetes are an important vector for Hg biomagnification to the coastal avian food web. This research demonstrates that feeding depth and method of feeding are more important than trophic position or sediment Hg concentrations for predicting Hg bioaccumulation.
Resumo:
New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.