11 research outputs found

    Controlled CO release using photochemical, thermal and electrochemical approaches from the amino carbene complex [(CO)5CrC(NC4H8)CH3]

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    Multimodal photo, thermal and electrochemical approaches toward CO release from the amino carbene complex [(CO)5CrC(NC4H8)CH3] is reported. Picosecond time resolved infrared spectroscopy was used to probe the photo-induced early state dynamics leading to CO release, and DFT calculations confirmed that CO release occurs from a singlet excited state

    New synthetic pathways to the preparation of near-blue emitting heteroleptic Ir(III) N-6 coordinated compounds with microsecond lifetimes

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    A high yield synthetic route for the preparation of N-6 coordinated heteroleptic Ir(III) complexes using bidentate polypyridyl type ligands is described. The complexes are near-blue emitters and showmicrosecond emission lifetimes, high emission quantum yields and have two quasi-reversible reduction processes between -1.0 and -1.3 V vs. Ag/AgCl

    Wavelength dependent photocatalytic H 2 generation using iridium-Pt/Pd complexes

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    Novel cyclometallated iridium-Pt/Pd dinuclear complexes containing the bridging ligand 2,2′:5′,2′′-terpyridine (BPP) and the peripheral phenylpyridine (ppy) ligand produced hydrogen under both visible (470 nm) and UV (350 nm) irradiation. The turnover numbers using visible light were found to be significantly higher, indicating an interplay between two independent excited states, only one of which produces H 2 efficiently. © 2012 The Royal Society of Chemistry

    CCDC 993309: Experimental Crystal Structure Determination

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    Related Article: Suraj Soman, Jennifer C. Manton, Jane L. Inglis, Yvonne Halpin, Brendan Twamley, Edwin Otten, Wesley R. Browne, Luisa De Cola, Johannes G. Vos, Mary T. Pryce|2014|Chem.Commun.|50|6461|doi:10.1039/C4CC02249A,An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

    Multiple imputation of cognitive performance as a repeatedly measured outcome

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    BACKGROUND: Longitudinal studies of cognitive performance are sensitive to dropout, as participants experiencing cognitive deficits are less likely to attend study visits, which may bias estimated associations between exposures of interest and cognitive decline. Multiple imputation is a powerful tool for handling missing data, however its use for missing cognitive outcome measures in longitudinal analyses remains limited. METHODS: We use multiple imputation by chained equations (MICE) to impute cognitive performance scores of participants who did not attend the 2011-2013 exam of the Atherosclerosis Risk in Communities Study. We examined the validity of imputed scores using observed and simulated data under varying assumptions. We examined differences in the estimated association between diabetes at baseline and 20-year cognitive decline with and without imputed values. Lastly, we discuss how different analytic methods (mixed models and models fit using generalized estimate equations) and choice of for whom to impute result in different estimands. RESULTS: Validation using observed data showed MICE produced unbiased imputations. Simulations showed a substantial reduction in the bias of the 20-year association between diabetes and cognitive decline comparing MICE (3-4% bias) to analyses of available data only (16-23% bias) in a construct where missingness was strongly informative but realistic. Associations between diabetes and 20-year cognitive decline were substantially stronger with MICE than in available-case analyses. CONCLUSIONS: Our study suggests when informative data are available for non-examined participants, MICE can be an effective tool for imputing cognitive performance and improving assessment of cognitive decline, though careful thought should be given to target imputation population and analytic model chosen, as they may yield different estimands
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