170 research outputs found

    Cobalt-Catalyzed Dehydrogenative C−H Silylation of Alkynylsilanes

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    Herein, we report that a cobalt catalyst permits the general synthesis of substituted alkynylsilanes through dehydrogenative coupling of alkynylsilanes and hydrosilanes. Several silylated alkynes, including di‐ and trisubstituted ones, were prepared in a one‐step procedure. Thirty‐seven compounds were synthesized for the first time by applying our catalyst system. The alkynylsilanes bearing hydrosilyl moieties provide an opportunity for further functionalization (e. g., hydrosilylation). The use of primary silanes as substrates and precatalyst activators permits the use of inexpensive and easily accessible 3d metal precatalysts, and avoids the presence of additional activators

    Zeitliche und rĂ€umliche Prognose der StabilitĂ€t von Braunkohletagebaukippen im Nordraum Lausitz mit kĂŒnstlichen neuronalen Netzen

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    Mittels kĂŒnstlichen neuronalen Netzen wurden die in den rekultivierten Tagebaukippen im Nordraum Lausitz (Tagebaue Schlabendorf und Seese) auftretenden GelĂ€ndedeformationen infolge BodenverflĂŒssigung fĂŒr die Jahre 2009 - 2013 als Zeitreihe modelliert. Das Modell ist in der Lage, grob die zeitliche Entwicklung und exakt die rĂ€umliche Lage des in den Kippen auftretenden GefĂ€hrdungspotenzials nachzuvollziehen und als Funktion des sich Ă€ndernden Grundwasserspiegels und der sich Ă€ndernden OberflĂ€chenmorphologie in die Zukunft zu prognostizieren. Das Modell zeigt dynamisch das Entstehen neuer RisikoflĂ€chen in bisher scheinbar stabilen Bereichen des Untersuchungsgebietes. Die Korrektheit des Modells wurde mittels verschiedener Tests geprĂŒft sowie anhand einer Prognoserechnung fĂŒr das Jahr 2014 und des Vergleichs mit den real in 2014/2015 gegangenen Ereignissen nachgewiesen. Folgende GefĂ€hrdungsfaktoren wurden ermittelt: Destabilisierend wirken eine möglichst einförmige Lithologie folgender Zusammenset-zung: 31 % Feinsand, 34 % Mittelsand, 31 % Grobsand, 3 % Schluff, < 1 % Kies, < 1 % Kalk, < 1 % Ton, < 1 % Kohle, kf-Werte zwischen 10-4 und 10-4,5 m/s, ein Grundwasserflurabstand bei 3,45 m (Medianwert), möglichst hohe Gradienten der nicht lithologisch kontrollierten Parameter: TagebauoberflĂ€che, GrundwasseroberflĂ€che, Grundwasserflurabstand und MĂ€chtigkeit der gesĂ€ttigten Kippe. Stabilisierend wirken vor allem eine möglichst große HeterogenitĂ€t der Lithologie auf kleinem Raum (möglichst hohe Gradienten der lithologisch kontrollierten Parameter (z.B. Kiesgehalt, Sandgehalt, Tongehalt, Kohlegehalt)), ein möglichst geringer Sandanteil, möglichst hohe Anteile an Kies, Schluff, Ton, Kalk, bzw. Kohle, ein möglichst großer Grundwasserflurabstand sowie möglichst geringe Gradienten der nicht lithologisch kontrollierten Parameter: TagebauoberflĂ€che, GrundwasseroberflĂ€che, Grundwasserflurabstand, MĂ€chtigkeit der gesĂ€ttigten Kippe sowie wechselnde kf-Werte 10-7 bzw. >10-2 m/s. FĂŒr die Bearbeitung wurden ausschließlich die bei der LMBV vorhandenen bzw. laufend flĂ€chendeckend erhobenen Daten genutzt: Lage des Grundwasserspiegels, Relief der TagebauoberflĂ€che, Liegendes der Kippe, geologische Daten der Vorfeldbohrungen. Das Modell kann als dynamisches Instrument zum Risikomanagement vor bzw. wĂ€hrend der Sanierungsmaßnahmen genutzt werden. Mittels der Variation der prozesskontrollie-renden Parameter können die geotechnischen Auswirkungen verschiedener Sanierungsszenarien (z.B. Gestaltung der TagebauoberflĂ€che, SchĂŒttung der Kippen, Grundwasseranstieg) auf die StabilitĂ€t der Kippen prognostiziert werden.Geotechnical events (terrain deformation due to soil liquefaction) in lignite mining waste rock piles of the northern Lausitz area (opencast pits Schlabendorf and Seese), have been modeled as time series for the years 2009 – 2013 by using artificial neural networks. The model has clearly recognized the influences of various lithological and non-lithological controlled parameters on the occurrence of geotechnical events, and these have been quantified and weighted in terms of their importance. The model is able to predict the tem-poral evolution and the exact spatial location of the events occurring in the dumps as a function of changing groundwater levels and surface morphology. The model shows dynamically the emergence of new risk areas in hitherto seemingly stable areas. The correctness of the model was confirmed by means of various tests and its predictive success was demonstrated through forecasting of events for the years 2014 and 2015 and their comparison with the observed events of those years. The following main risk factors were identified: Important destabilizing factors are a monotonous lithology with the following composition: 31% fine sand, 34% medium sand, 31% coarse sand, 3% silt, <1% gravel, <1% lime, <1% clay, <1% coal, kf-values between 10-4 and 10-4.5 m/s, a surface to groundwater distance of 3.45 meters (median value), high gradients of non-lithological controlled parameters: waste dump surface, groundwater level, depth to groundwater and thickness of saturated dump. 2. Important stabilizing factors are a high heterogeneity of lithology (high gradients of the lithological controlled parameters: e.g. gravel content, sand content, clay content, carbon content), a low proportion of sand in the dump composition, high proportions of gravel, silt, clay, lime, or coal, a high depth to groundwater, low gradients of non-lithological controlled parameters: open pit surface, groundwater surface, depth to groundwater, thickness of saturated dump, strongly changing kf values between 10-7 and 10-2 m/s. The model can be used as a dynamic tool for risk management before and during the re-habilitation of lignite waste dumps, and for constructing stable waste dumps. By means of varying the model parameters (e.g. design of the dump surface, composition of dumped rocks, rising groundwater) the geotechnical effects of dump design and remediation scenarios can be predicted

    Catalytic (de)hydrogenation promoted by non-precious metals – Co, Fe and Mn: recent advances in an emerging field

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    Manganese-catalyzed one-pot conversion of nitroarenes into N-methylarylamines uising methanol

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    A manganese‐catalyzed one‐pot conversion of nitroarenes into N‐methylarylamines has been developed. This transfer hydrogenation method employs a well‐defined bench stable Mn PN3P pincer precatalyst in combination with methanol as both the reductant and the C1 source. A selection of commercially available nitroarenes was converted into N‐methylarylamines in synthetically useful yields

    Molecular studies of luteinizing hormone-releasing hormones in the brain of domestic fowl

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    Available from British Library Document Supply Centre- DSC:DX98387 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

    Iridium Catalyzed Synthesis of Tetrahydro-1H-Indoles by Dehydrogenative Condensation

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    Novel synthetic routes to the commonly encountered indole motif are highly sought after. Tetrahydro-1H-indoles were synthesized for the first time from secondary alcohols and 2-aminocyclohexanol in the presence of a well-established iridium catalyst using a modified synthetic procedure recently developed for the synthesis of hydrocarbazoles. The catalyst is stabilized by an inexpensive and easy-to-synthesize triazine based PN5P pincer ligand. The reaction proceeds through acceptorless dehydrogenative condensation (ADC) and yields the title compound, dihydrogen, and water and can thus be classified as sustainable synthesis. Overall, five examples, three of which were previously unknown compounds, were prepared. The propitious isolated yields and the mild reaction conditions show the synthetic value of this approach. These tetrahydroindoles can be quantitatively dehydrogenated over a heterogeneous Pd catalyst to yield the corresponding indoles
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