2 resultados para 13C NMR compilation

em Digital Commons - Michigan Tech


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A new series of chiral ferrosalen ligands was designed and synthesized. The special feature of the ferrosalen ligands is that the chirality originated from the planar chiral ferrocenyl structure. For most known salen ligands, chirality comes from central and axial chiral centers. The key building block for the construction of these ferrosalen ligands was synthesized stereoselectively by a chiral auxiliary approach. This approach does not consume any chiral material, and does not require chiral HPLC resolution. Using this method, nine ligands were prepared using ferrocene as the starting material. In addition, the steric hindrance was modulated by changing the cyclopentadienyl group to the more bulky pentamethylcyclopentadienyl- and pentaphenylcyclopentadienyl- groups. The structure of these ligands was established by 1H and 13C NMR. The structure of a ferrosalen-Cu (II) complex was determined by single crystal X-ray diffraction analysis. All the chiral ferrosalen ligands were tested in catalytic asymmetric reactions including enantioselective carbonyl-ene reaction, enantioselective Strecker-type reaction and enantioselective silylcyanation. For the carbonyl-ene reaction, up to 99% yield and 29% enantiomeric excess (ee) were obtained using ligand-Co (III) as the catalysts; For the Strecker-type reaction, a maximum of 20% ee was obtained using ligand-AlCl as the catalyst; For the silylcyanation reaction, up to 99% yield and 26% ee were obtained using ligand-AlCl as the catalyst.

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Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.