Institution
Technical University of Berlin
Education•Berlin, Germany•
About: Technical University of Berlin is a education organization based out in Berlin, Germany. It is known for research contribution in the topics: Laser & Catalysis. The organization has 27292 authors who have published 59342 publications receiving 1414623 citations. The organization is also known as: Technische Universität Berlin & TU Berlin.
Topics: Laser, Catalysis, Quantum dot, Computer science, Context (language use)
Papers published on a yearly basis
Papers
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TL;DR: Four seemingly simple transformations related to the chemistry of methane are addressed from mechanistic and conceptual points of view: metal-mediated dehydrogenation to form metal carbene complexes, the hydrogen-atom abstraction step in the oxidative dimerization of methane, the mechanisms of the CH(4)→CH(3)OH conversion, and the initial bond scission.
Abstract: Four seemingly simple transformations related to the chemistry of methane will be addressed from mechanistic and conceptual points of view: 1) metal-mediated dehydrogenation to form metal carbene complexes, 2) the hydrogen-atom abstraction step in the oxidative dimerization of methane, 3) the mechanisms of the CH(4)→CH(3)OH conversion, and 4) the initial bond scission (C-H vs. O-H) as well as the rate-limiting step in the selective CH(3)OH→CH(2)O oxidation. State-of-the-art gas-phase experiments, in conjunction with electronic-structure calculations, permit identification of the elementary reactions at a molecular level and thus allow us to unravel detailed mechanistic aspects. Where appropriate, these results are compared with findings from related studies in solution or on surfaces.
556 citations
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TL;DR: In this article, the role of patenting and alternative instruments to protect intellectual property is analyzed against the background of the patent upsurge, based on a sample of German companies active in patenting.
556 citations
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TL;DR: The results suggest that neural activity in vivo shows a mélange of avalanches, and not temporally separated ones, and that their global activity propagation can be approximated by the principle that one spike on average triggers a little less than one spike in the next step.
Abstract: In self-organized critical (SOC) systems avalanche size distributions follow power-laws. Power-laws have also been observed for neural activity, and so it has been proposed that SOC underlies brain organization as well. Surprisingly, for spiking activity in vivo, evidence for SOC is still lacking. Therefore we analyzed highly parallel spike recordings from awake rats and monkeys, anaesthetized cats, and also local field potentials from humans. We compared these to spiking activity from two established critical models: the Bak-Tang-Wiesenfeld model, and a stochastic branching model. We found fundamental differences between the neural and the model activity. These differences could be overcome for both models through a combination of three modifications: (1) subsampling, (2) increasing the input to the model (this way eliminating the separation of time scales, which is fundamental to SOC and its avalanche definition), and (3) making the model slightly sub-critical. The match between the neural activity and the modified models held not only for the classical avalanche size distributions and estimated branching parameters, but also for two novel measures (mean avalanche size, and frequency of single spikes), and for the dependence of all these measures on the temporal bin size. Our results suggest that neural activity in vivo shows a melange of avalanches, and not temporally separated ones, and that their global activity propagation can be approximated by the principle that one spike on average triggers a little less than one spike in the next step. This implies that neural activity does not reflect a SOC state but a slightly sub-critical regime without a separation of time scales. Potential advantages of this regime may be faster information processing, and a safety margin from super-criticality, which has been linked to epilepsy.
552 citations
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Technical University of Berlin1, Indian Institute of Science2, Chalmers University of Technology3, Technical University of Denmark4, Norwegian University of Science and Technology5, National Renewable Energy Laboratory6, Autonomous University of Barcelona7, University of California, Davis8, University of Groningen9, The Nature Conservancy10, Alpen-Adria-Universität Klagenfurt11, Humboldt University of Berlin12, Potsdam Institute for Climate Impact Research13, ETH Zurich14, Electric Power Research Institute15, University of Aberdeen16, University of California, Santa Barbara17, National Autonomous University of Mexico18
TL;DR: In this article, the authors bring together perspectives of various communities involved in the research and regulation of bioenergy deployment in the context of climate change mitigation: Land-use and energy experts, land use and integrated assessment modelers, human geographers, ecosystem researchers, climate scientists and two different strands of life-cycle assessment experts.
Abstract: Bioenergy deployment offers significant potential for climate change mitigation, but also carries considerable risks. In this review, we bring together perspectives of various communities involved in the research and regulation of bioenergy deployment in the context of climate change mitigation: Land-use and energy experts, land-use and integrated assessment modelers, human geographers, ecosystem researchers, climate scientists and two different strands of life-cycle assessment experts. We summarize technological options, outline the state-of-the-art knowledge on various climate effects, provide an update on estimates of technical resource potential and comprehensively identify sustainability effects. Cellulosic feedstocks, increased end-use efficiency, improved land carbon-stock management and residue use, and, when fully developed, BECCS appear as the most promising options, depending on development costs, implementation, learning, and risk management. Combined heat and power, efficient biomass cookstoves and small-scale power generation for rural areas can help to promote energy access and sustainable development, along with reduced emissions. We estimate the sustainable technical potential as up to 100EJ: high agreement; 100-300EJ: medium agreement; above 300EJ: low agreement. Stabilization scenarios indicate that bioenergy may supply from 10 to 245EJyr(-1) to global primary energy supply by 2050. Models indicate that, if technological and governance preconditions are met, large-scale deployment (>200EJ), together with BECCS, could help to keep global warming below 2 degrees degrees of preindustrial levels; but such high deployment of land-intensive bioenergy feedstocks could also lead to detrimental climate effects, negatively impact ecosystems, biodiversity and livelihoods. The integration of bioenergy systems into agriculture and forest landscapes can improve land and water use efficiency and help address concerns about environmental impacts. We conclude that the high variability in pathways, uncertainties in technological development and ambiguity in political decision render forecasts on deployment levels and climate effects very difficult. However, uncertainty about projections should not preclude pursuing beneficial bioenergy options.
550 citations
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TL;DR: Fundamental ML methodologies are outlined and their uses for understanding, modeling, optimizing, and controlling fluid flows are discussed and the strengths and limitations of these methods are addressed.
Abstract: The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machi...
549 citations
Authors
Showing all 27602 results
Name | H-index | Papers | Citations |
---|---|---|---|
Markus Antonietti | 176 | 1068 | 127235 |
Jian Li | 133 | 2863 | 87131 |
Klaus-Robert Müller | 129 | 764 | 79391 |
Michael Wagner | 124 | 351 | 54251 |
Shi Xue Dou | 122 | 2028 | 74031 |
Xinchen Wang | 120 | 349 | 65072 |
Michael S. Feld | 119 | 552 | 51968 |
Jian Liu | 117 | 2090 | 73156 |
Ary A. Hoffmann | 113 | 907 | 55354 |
Stefan Grimme | 113 | 680 | 105087 |
David M. Karl | 112 | 461 | 48702 |
Lester Packer | 112 | 751 | 63116 |
Andreas Heinz | 108 | 1078 | 45002 |
Horst Weller | 105 | 451 | 44273 |
G. Hughes | 103 | 957 | 46632 |