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Institution

Vienna University of Technology

EducationVienna, Austria
About: Vienna University of Technology is a education organization based out in Vienna, Austria. It is known for research contribution in the topics: Laser & Context (language use). The organization has 16723 authors who have published 49341 publications receiving 1302168 citations.


Papers
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Journal ArticleDOI
TL;DR: A modular synthetic strategy with which the steric, electronic, and stereochemical properties of the ligands can be varied systematically is developed, which has resulted in the preparation of a range of new pincer complexes, including various iron complexes.
Abstract: Transition metal complexes are indispensable tools for any synthetic chemist. Ideally, any metal-mediated process should be fast, clean, efficient, and selective and take place in a catalytic manner. These criteria are especially important considering that many of the transition metals employed in catalysis are rare and expensive. One of the ways of modifying and controlling the properties of transition metal complexes is the use of appropriate ligand systems, such as pincer ligands. Usually consisting of a central aromatic backbone tethered to two two-electron donor groups by different spacers, this class of tridentate ligands have found numerous applications in various areas of chemistry, including catalysis, due to their combination of stability, activity, and variability. As we focused on pincer ligands featuring phosphines as donor groups, the lack of a general method for the preparation of both neutral (PNP) and anionic (PCP) pincer ligands using similar precursor compounds as well as the difficulty of introducing chirality into the structure of pincer ligands prompted us to investigate the use of amines as spacers between the aromatic ring and the phosphines. By introduction of aminophosphine and phosphoramidite moieties into their structure, the synthesis of both PNP and PCP ligands can be achieved via condensation reactions between aromatic diamines and electrophilic chlorophosphines (or chlorophosphites). Moreover, chiral pincer complexes can be easily obtained by using building blocks obtained from the chiral pool. Thus, we have developed a modular synthetic strategy with which the steric, electronic, and stereochemical properties of the ligands can be varied systematically. With the ligands in hand, we studied their reactivity towards different transition metal precursors, such as molybdenum, ruthenium, iron, nickel, palladium, and platinum. This has resulted in the preparation of a range of new pincer complexes, including various iron complexes, as well as the first heptacoordinated molybdenum pincer complexes and several pentacoordinated nickel complexes by using a controlled ligand decomposition pathway. In addition, we have investigated the use of some of the complexes as catalysts in different C-C coupling reactions: for example, the palladium PNP and PCP pincer complexes can be employed as catalysts in the well known Suzuki-Miyaura coupling, while the iron PNP complexes catalyze the coupling of aromatic aldehydes with ethyl diazoacetate under very mild reaction conditions to give selectively 3-hydroxyacrylates, which are otherwise difficult to prepare. While this Account presents an overview of current research on the chemistry of P-N bond containing pincer ligands and complexes, we believe that further investigations will give deeper insights into the reactivity and applicability of aminophosphine-based pincer complexes.

440 citations

Journal ArticleDOI
TL;DR: Bartalis et al. as mentioned in this paper presented the first results of deriving relative surface soil moisture from the METOP-A Advanced Scatterometer (ASCAT) using model parameters derived from eight years of ERS scatterometer data.
Abstract: [1] This article presents first results of deriving relative surface soil moisture from the METOP-A Advanced Scatterometer. Retrieval is based on a change detection approach which has originally been developed for the Active MicrowaveInstrument flownonboardtheEuropeansatellites ERS-1 and ERS-2. Using model parameters derived from eight years of ERS scatterometer data, first global soil moisture maps have been produced from ASCAT data. The ASCAT data were distributed by EUMETSAT for validation purposes during the ASCAT product commissioning activities. Several recent cases of drought and excessive rainfall are clearly visible in the soil moisture data. The results confirm that seamless soil moisture time series can be expected from the series of two ERS and three METOP scatterometers, providing global coverage on decadal time scales (from 1991 to about 2021). Thereby, operational, nearreal-time ASCAT soil moisture products will become available for weather prediction and hydrometeorological applications. Citation: Bartalis, Z., W. Wagner, V. Naeimi, S. Hasenauer, K. Scipal, H. Bonekamp, J. Figa, and C. Anderson (2007), Initial soil moisture retrievals from the METOP-A Advanced Scatterometer (ASCAT), Geophys. Res. Lett., 34, L20401, doi:10.1029/2007GL031088.

438 citations

Journal ArticleDOI
04 Mar 2020-Nature
TL;DR: It is demonstrated that an image sensor can itself constitute an ANN that can simultaneously sense and process optical images without latency, and is trained to classify and encode images with high throughput, acting as an artificial neural network.
Abstract: Machine vision technology has taken huge leaps in recent years, and is now becoming an integral part of various intelligent systems, including autonomous vehicles and robotics. Usually, visual information is captured by a frame-based camera, converted into a digital format and processed afterwards using a machine-learning algorithm such as an artificial neural network (ANN)1. The large amount of (mostly redundant) data passed through the entire signal chain, however, results in low frame rates and high power consumption. Various visual data preprocessing techniques have thus been developed2-7 to increase the efficiency of the subsequent signal processing in an ANN. Here we demonstrate that an image sensor can itself constitute an ANN that can simultaneously sense and process optical images without latency. Our device is based on a reconfigurable two-dimensional (2D) semiconductor8,9 photodiode10-12 array, and the synaptic weights of the network are stored in a continuously tunable photoresponsivity matrix. We demonstrate both supervised and unsupervised learning and train the sensor to classify and encode images that are optically projected onto the chip with a throughput of 20 million bins per second.

436 citations

Journal ArticleDOI
TL;DR: Sensitivity analysis showed that gasification temperature and fuel oxygen content were the most significant parameters determining the chemical efficiency of the gasification.

434 citations

Journal ArticleDOI
TL;DR: In this paper, the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment, are highlighted, highlighting how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as searches for physics beyond the Standard Model.
Abstract: We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.

433 citations


Authors

Showing all 16934 results

NameH-indexPapersCitations
Krzysztof Matyjaszewski1691431128585
Wolfgang Wagner1562342123391
Marco Zanetti1451439104610
Sridhara Dasu1401675103185
Duncan Carlsmith1381660103642
Ulrich Heintz136168899829
Matthew Herndon133173297466
Frank Würthwein133158494613
Alain Hervé132127987763
Manfred Jeitler132127889645
David Taylor131246993220
Roberto Covarelli131151689981
Patricia McBride129123081787
David Smith1292184100917
Lindsey Gray129117081317
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023171
2022379
20212,530
20202,811
20192,846
20182,650