Ion Wakes at Strong Magnetic Fields: Experiments and Simulations

Im Fokus dieser Dissertation steht der Einfluss starker Magnetfelder auf den Ion Wake, die Veränderung der Dichte- und Potentialtopologie im Windschatten von Mikropartikeln in einer starken Ionenströmung. Die Mikropartikel werden in komplexen Laborplasmen meist in der Plasmarandschicht, in der eine starke Ionenströmung vorherrscht, eingeschlossen. Der Einfluss von Wakes ist hier allgegenwärtig und betrifft Anordnung, Aufladung und Wechselwirkung der Partikel. Ein typisches Phänomen des Wakes ist die als Ionenfokus bezeichnete Anhäufung positiver Raumladung, die Ursprung attraktiver Wechselwirkung negativ geladener Partikel und einer Ladungsreduktion von Partikeln im Wake ist. Zur Untersuchung des Wakes und seines Einflusses auf die Mikropartikel in Gegenwart starker Magnetfelder werden zwei komplementäre Ansätze gewählt: In Experimenten werden die durch den Wake beeinflusste Dynamik und Anordnung eines Partikelpaars räumlich aufgelöst untersucht. Simulationen bieten einen Zugang zu experimentell nicht zugänglichen Eigenschaften des Wakes und dienen der Interpretation der experimentellen Befunde. Erstmals werden selbstkonsistente Simulationen des magnetisierten Wakes präsentiert. Diese zeigen für starke magnetische Flussdichten ein neues, stark nichtlineares Phänomen, den dynamischen Ionenschatten, Bereiche starker Ionenverarmung im Wake. Die experimentell im Magnetfeld auftretenden Änderungen der Anordnung zweier Partikel machen die wirkenden, durch den Wake beeinflussten Kraftfelder erfassbar. Das Schattenphänomen tritt bei experimentell realisierbaren magnetischen Flussdichten in Einklang mit Simulationen noch nicht auf. Wenn auch in abgeschwächter Form, bleibt der Wake wie im unmagnetisierten Fall Ursprung attraktiver Kräfte auf die Partikel. Die vorliegende Dissertation untersucht den magnetisierten Ion Wake erstmals detailliert und gibt damit einen Einblick in die durch starke Magnetfelder beeinflusste Ionendynamik und deren Wirkung auf komplexe Plasmen.This thesis focuses on the influence of strong magnetic fields on the ion wake, which is the modified density and potential distribution in the slipstream of microparticles exposed to a strong ion flow. In complex laboratory plasmas, microparticles are mostly enclosed in the plasma sheath, where a strong ion flow prevails. Hence, the influence of wakes is omnipresent here and affects the arrangement, charge and interaction of the particles. A typical phenomenon of wakes is the accumulation of positive space charge, the so-called ion focus, that is the origin of attractive interaction of negatively charged particles and a charge reduction of particles in the wake. Two complementary approaches are chosen to investigate the wake and its influence on the microparticles in the presence of strong magnetic fields: In experiments, the dynamics and arrangement of a pair of particles, which are influenced by the wake, are investigated spatially resolved. Simulations provide access to experimentally inaccessible properties of the wake and enable the interpretation of the experimental findings. For the first time, self-consistent simulations of magnetized wakes are presented. At strong magnetic inductions, they show a new, strongly nonlinear phenomenon, the dynamic ion shadow, areas of strong ion depletion in the wake. The analysis of changes in the arrangement of two particles occurring in the experiments with magnetic fields enables the investigation of the underlying force fields, which are influenced by the wake. The shadow phenomenon does not occur at experimentally feasible inductions, which is in accordance with simulations. As in the non-magnetized case but attenuated, the wake remains the origin of attractive particle interaction forces. This thesis investigates the magnetized ion wake in detail for the first time and thus provides an insight into the ion dynamics of a complex plasma with strong magnetic fields

Practical High-Throughput, Non-Adaptive and Noise-Robust SARS-CoV-2 Testing

We propose a compressed sensing-based testing approach with a practical measurement design and a tuning-free and noise-robust algorithm for detecting infected persons. Compressed sensing results can be used to provably detect a small number of infected persons among a possibly large number of people. There are several advantages of this method compared to classical group testing. Firstly, it is non-adaptive and thus possibly faster to perform than adaptive methods which is crucial in exponentially growing pandemic phases. Secondly, due to nonnegativity of measurements and an appropriate noise model, the compressed sensing problem can be solved with the non-negative least absolute deviation regression (NNLAD) algorithm. This convex tuning-free program requires the same number of tests as current state of the art group testing methods. Empirically it performs significantly better than theoretically guaranteed, and thus the high-throughput, reducing the number of tests to a fraction compared to other methods. Further, numerical evidence suggests that our method can correct sparsely occurring errors.Comment: 8 Pages, 1 Figur

Semiautomatische Segmentierung von Lymphknoten und dessen Einsatz bei der Prognose von oralen Plattenepithelkarzinomen

Diese Arbeit soll die Zuverlässigkeit der Volumenermittlung von Lymphknoten durch verschiedene Programme sowie den Nutzen des pathologischen, cervikalen Lymphknotenvolumens in Hinblick auf die Prognose von oralen Plattenepithelkarzinomen aufzeigen. Dafür wurden erstmals drei Programme hinsichtlich ihrer Eignung für die semiautomatische Segmentierung von Lymphknoten mit Hilfe von CT Datensätzen miteinander verglichen: ITK-Snap, InVesalius und 3D Slicer. Es konnten keine signifikanten Abweichungen zwischen den Ergebnissen gefunden werden. Demnach sind die Programme dazu geeignet, das pathologische Lymphknotenvolumen zu bestimmen und für die Prognose der Patienten zu nutzen. Die Software ITK-Snap wurde eingesetzt, um das pathologische, präoperative Lymphknotenvolumen von 100 Patienten mit oralen Plattenepithelkarzinomen zu segmentieren. Das Lymphknotenvolumen wurde mit anderen klinischen Erhebungen verglichen. Dadurch konnte herausgefunden werden, dass eine pathologische N-Klassifizierung beim Staging, zentrale Nekrose betroffener Lymphknoten und das pathologische Gesamtlymphknotenvolumen signifikant die Prognose in Hinsicht auf lokoregionale Rezidive des jeweiligen Patienten beeinflussen. Ein pathologisches Lymphknotenvolumen von mehr als 6,86cm³ geht mit einem 20 fach höheren Risiko für lokoregionale Rezidive einher. Die Ergebnisse zeigen, dass der Einsatz von semiautomatischer Segmentierung beim Staging einen Vorteil bezüglich der Prognoseeinschätzung von Patienten mit oralen Plattenepithelkarzinomen haben kann

Autonomous artificial intelligence discovers mechanisms of molecular self-organization in virtual experiments

Molecular self-organization driven by concerted many-body interactions produces the ordered structures that define both inanimate and living matter. Understanding the physical mechanisms that govern the formation of molecular complexes and crystals is key to controlling the assembly of nanomachines and new materials. We present an artificial intelligence (AI) agent that uses deep reinforcement learning and transition path theory to discover the mechanism of molecular self-organization phenomena from computer simulations. The agent adaptively learns how to sample complex molecular events and, on the fly, constructs quantitative mechanistic models. By using the mechanistic understanding for AI-driven sampling, the agent closes the learning cycle and overcomes time-scale gaps of many orders of magnitude. Symbolic regression condenses the mechanism into a human-interpretable form. Applied to ion association in solution, gas-hydrate crystal formation, and membrane-protein assembly, the AI agent identifies the many-body solvent motions governing the assembly process, discovers the variables of classical nucleation theory, and reveals competing assembly pathways. The mechanistic descriptions produced by the agent are predictive and transferable to close thermodynamic states and similar systems. Autonomous AI sampling has the power to discover assembly and reaction mechanisms from materials science to biology

Factors determining airlines' costs for climate protecting market-based measures

This paper investigates the factors influencing airline’s costs for climate protecting market-based measures. It is based on selected results of the interdisciplinary research project AviClim (Including Aviation in International Protocols for Climate Protection). AviClim has investigated how to limit aviation’s full climate impact best from an environmental and economic point of view. In this research project, both long-lived CO2 and short-lived non-CO2 effects of aviation have been addressed simultaneously and climate protecting scenarios for aviation in the timeframe 2010-2030 have been developed. On this basis, the factors determining aviation’s costs for climate protecting measures have been analysed. Results indicate that the choice of the market-based measure, it’s regional scope, the metric chosen for the translation of the non-CO2 impacts into equivalent CO2 and the prices for equivalent CO2 are important factors for airline’s costs. An analysis for single flights reveals remarkable differences in specific emissions (tons CO2 equivalent/flight kilometre). An investigation for groups of airlines differentiated by business model and country of origin indicates that the world regions served by the airlines, the business model, the length and the emission characteristics of the flights are further important factors for the costs of the regulating measure

How to best address aviation’s full climate impact from an economic policy point of view? – Main results from AviClim research project

AbstractThe interdisciplinary research project AviClim (Including Aviation in International Protocols for Climate Protection) has explored the feasibility for including aviation’s full climate impact, i.e., both long-lived CO2 and short-lived non-CO2 effects, in international protocols for climate protection and has investigated the economic impacts. Short-lived non-CO2 effects of aviation are NOx emissions, H2O emissions or contrail cirrus, for instance.Four geopolitical scenarios have been designed which differ concerning the level of international support for climate protecting measures. These scenarios have been combined alternatively with an emissions trading scheme on CO2 and non-CO2 species, a climate tax and a NOx emission charge combined with CO2 trading and operational measures (such as lower flight altitudes). Modelling results indicate that a global emissions trading scheme for both CO2 and non-CO2 emissions would be the best solution from an economic and environmental point of view. Costs and impacts on competition could be kept at a relatively moderate level and effects on employment are moderate, too. At the same time, environmental benefits are noticeable

Absolute Triple Differential Cross Section for Ionization of Helium Near Threshold

Absolute measurements with an accuracy of 22% and theoretical results in a distorted-wave Born approximation (DWBA) are reported for the triple-differential cross section for 26.6-eV electron-impact ionization of helium. An apparatus is used that allows all scattering angles to be independently varied for both coplanar and noncoplanar geometries. The measurements are compared with a DWBA calculation that includes exchange distortion in the calculation of the distorted waves, as well as with earlier calculations by Crothers [J. Phys. B 19, 463 (1986)] and Pan and Starace [Phys. Rev. Lett. 67, 185 (1991)]. Emphasis is placed on understanding the mechanisms for near-threshold ionization