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Institution

University of Münster

EducationMünster, Germany
About: University of Münster is a education organization based out in Münster, Germany. It is known for research contribution in the topics: Population & Catalysis. The organization has 35609 authors who have published 69059 publications receiving 2278534 citations. The organization is also known as: University of Munster & University of Muenster.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the key fields within structured light from the perspective of experts in those areas, providing insight into the current state and the challenges their respective fields face, as well as the exciting prospects for the future that are yet to be realized.
Abstract: Structured light refers to the generation and application of custom light fields. As the tools and technology to create and detect structured light have evolved, steadily the applications have begun to emerge. This roadmap touches on the key fields within structured light from the perspective of experts in those areas, providing insight into the current state and the challenges their respective fields face. Collectively the roadmap outlines the venerable nature of structured light research and the exciting prospects for the future that are yet to be realized.

639 citations

Journal ArticleDOI
TL;DR: An intensive literature search on the distribution and concentration of the surface-dependent runoff water has been compiled and a representative concentration matrix consisting of medians and extreme values can be applied to long-term valuations and numerical modelling of storm water treatment facilities.

639 citations

Journal ArticleDOI
TL;DR: This work demonstrates the generation of single-mode coherent auto-oscillations in a device that combines local injection of a pure spin current with enhanced spin-wave radiation losses, and suggests a new route for the implementation of nanoscale microwave sources for next-generation integrated electronics.
Abstract: The dynamical processes associated with the magnetization of a material can be drastically altered by the application of a spin current. This study now demonstrates the feasibility of selectively exciting coherent auto-oscillation modes in magnetic nanostructures.

638 citations

Journal ArticleDOI
TL;DR: This review examined the emerging science of deterministic chaos (nonlinear systems theory) and its application to selected physiological systems and to the neurosciences, demonstrating that the dynamics of neural mass activity reflect psychopathological states.
Abstract: In this review we examined the emerging science of deterministic chaos (nonlinear systems theory) and its application to selected physiological systems. Although many of the popular images of fractals represent fascination and beauty that by analogy corresponds to nature as we see it, the question remains as to its ultimate meaning for physiological processes. It was our intent to help clarify this somewhat popular, somewhat obscure area of nonlinear dynamics in the context of an ever-changing procedural base. We examined not only the basic concepts of chaos, but also its applications ranging from observations in single cells to the complexity of the EEG. We have not suggested that nonlinear dynamics will answer all of our questions; however, we did attempt to illustrate ways in which this approach may help us to answer new questions and to rearticulate old ones. Chaos is revolutionary in that the overall approach requires us to adopt a different frame of reference which, at times, may move us away from previous concerns and methods of data analysis. In sections I-IV, we summarized the nonlinear dynamics approach and described its application to physiology and neural systems. First, we presented a general overview of the application of nonlinear dynamical techniques to neural systems. We discussed the manner in which even apparently simple deterministic systems can behave in an unpredictable manner. Second, we described the principles of nonlinear dynamical systems including the derived analytical techniques. We now see a variety of procedures for delineating whether frenetic chaotic behavior results from a nonlinear dynamical system with a few degrees of freedom, or whether it is caused by an infinite number of variables, i.e., noise. Third, we approached the applications of nonlinear procedures to the cardiovascular systems and to the neurosciences. In terms of time series, we described initial studies which applied the now "traditional" measures of dimensionality (e.g., based on the algorithm by Grassberger and Procaccia) and information change (e.g., Lyapunov exponents). Examples include our own work and that of Pritchard et al., demonstrating that the dynamics of neural mass activity reflect psychopathological states. Today, however, the trend has expanded to include the use of surrogate data and statistical null hypotheses testing to examine whether a given time series can be considered different from that of white or colored noise (cf. Ref. 262). One of the most important potential applications is that of quantifying changes in nonlinear dynamics to predict future states of the system.(ABSTRACT TRUNCATED AT 400 WORDS)

637 citations

Journal ArticleDOI
TL;DR: This tutorial review covers the photophysical fundamentals and most significant advances in the field of visible-light-mediated energy transfer catalysis within the last decade.
Abstract: Harnessing visible light to access excited (triplet) states of organic compounds can enable impressive reactivity modes. This tutorial review covers the photophysical fundamentals and most significant advances in the field of visible-light-mediated energy transfer catalysis within the last decade. Methods to determine excited triplet state energies and to characterize the underlying Dexter energy transfer are discussed. Synthetic applications of this field, divided into four main categories (cyclization reactions, double bond isomerizations, bond dissociations and sensitization of metal complexes), are also examined.

632 citations


Authors

Showing all 36075 results

NameH-indexPapersCitations
Hyun-Chul Kim1764076183227
Klaus Müllen1642125140748
Giacomo Bruno1581687124368
Anders M. Dale156823133891
Holger J. Schünemann141810113169
Joachim Heinrich136130976887
Markus Merschmeyer132118884975
Klaus Ley12949557964
Robert W. Mahley12836360774
Robert J. Kurman12739760277
Bart Barlogie12677957803
Thomas Schwarz12370154560
Carlos Caldas12254773840
Klaus Weber12152460346
Andrey L. Rogach11757646820
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023253
2022831
20213,683
20203,499
20193,236
20182,918