Technische Universität Darmstadt

About: Technische Universität Darmstadt is a education organization based out in Darmstadt, Germany. It is known for research contribution in the topics: Neutron & Finite element method. The organization has 17316 authors who have published 40619 publications receiving 937916 citations. The organization is also known as: Darmstadt University of Technology & University of Darmstadt.

Drop impact onto a liquid layer of finite thickness: dynamics of the cavity evolution.

Abstract: In the present work experimental, numerical, and theoretical investigations of a normal drop impact onto a liquid film of finite thickness are presented. The dynamics of drop impact on liquid surfaces, the shape of the cavity, the formation and propagation of a capillary wave in the crater, and the residual film thickness on the rigid wall are determined and analyzed. The shape of the crater within the film and the uprising liquid sheet formed upon the impact are observed using a high-speed video system. The effects of various influencing parameters such as drop impact velocity, liquid film thickness and physical properties of the liquids, including viscosity and surface tension, on the time evolution of the crater formation are investigated. Complementary to experiments the direct numerical simulations of the phenomena are performed using an advanced free-surface capturing model based on a two-fluid formulation of the classical volume-of-fluid (VOF) model in the framework of the finite volume numerical method. In this model an additional convective term is introduced into the transport equation for phase fraction, contributing decisively to a sharper interface resolution. Furthermore, an analytical model for the penetration depth of the crater is developed accounting for the liquid inertia, viscosity, gravity, and surface tension. The model agrees well with the experiments at the early times of penetration far from the wall if the impact velocity is high. Finally, a scaling analysis of the residual film thickness on the wall is conducted demonstrating a good agreement with the numerical predictions.

Identification of polymer types and additives in marine microplastic particles using pyrolysis-GC/MS and scanning electron microscopy

Abstract: Any assessment of plastic contamination in the marine environment requires knowledge of the polymer type and the additive content of microplastics. Sequential pyrolysis-gas chromatography coupled to mass spectrometry (Pyr-GC/MS) was applied to simultaneously identify polymer types of microplastic particles and associated organic plastic additives (OPAs). In addition, a scanning electron microscope equipped with an energy-dispersive X-ray microanalyser was used to identify the inorganic plastic additives (IPAs) contained in these particles. A total of ten particles, which were optically identified as potentially being plastics, were extracted from two sediment samples collected from Norderney, a North Sea island, by density separation in sodium chloride. The weights of these blue, white and transparent fragments varied between 10 and 350 μg. Polymer types were identified by comparing the resulting pyrograms with those obtained from the pyrolysis of selected standard polymers. The particles consisted of polyethylene (PE), polypropylene, polystyrene, polyamide, chlorinated PE and chlorosulfonated PE. The polymers contained diethylhexyl phthalate, dibutyl phthalate, diethyl phthalate, diisobutyl phthalate, dimethyl phthalate, benzaldehyde and 2,4-di-tert-butylphenol. Sequential Py-GC/MS was found to be an appropriate tool for identifying marine microplastics for polymer types and OPAs. The IPAs identified were titanium dioxide nanoparticles (TiO2-NPs), barium, sulphur and zinc. When polymer–TiO2 composites are degraded in the marine environment, TiO2-NPs are probably released. Thus, marine microplastics may act as a TiO2-NP source, which has not yet been considered.

A Racing Algorithm for Configuring Metaheuristics

Abstract: This paper describes a racing procedure for finding, in a limited amount of time, a configuration of a metaheuristic that performs as good as possible on a given instance class of a combinatorial optimization problem. Taking inspiration from methods proposed in the machine learning literature for model selection through cross-validation, we propose a procedure that empirically evaluates a set of candidate configurations by discarding bad ones as soon as statistically sufficient evidence is gathered against them. We empirically evaluate our procedure using as an example the configuration of an ant colony optimization algorithm applied to the traveling salesman problem. The experimental results show that our procedure is able to quickly reduce the number of candidates, and allows to focus on the most promising ones.

Tri-s-triazine derivatives. Part I. From trichloro-tri-s-triazine to graphitic C3N4 structures

Abstract: The first detailed structural characterisation of a functionalised tri-s-triazine derivative, trichloro-tri-s-triazine, is reported, which is a promising starting material for numerous compounds including graphitic C3N4 phases. DFT calculations show that a C3N4 structure based on tri-s-triazine should exist and that it is ∼30 kJ mol−1 more stable than the previously reported C3N4 phase of lowest energy.