Phosphorus‐Containing Polymer Flame Retardants for Aliphatic Polyesters

Polyesters with 9,10‐dihydro‐9‐oxy‐10‐phosphaphenanthrene‐10‐oxide‐containing comonomers are synthesized aiming to improve the flame retardancy of aliphatic polyesters such as poly(butylene succinate) and poly(butylene sebacate). The influence of the chemical structure on the thermal decomposition and pyrolysis is examined using a combination of thermogravimetric analysis (TGA), TGA‐Fourier transform infrared (FTIR) spectroscopy, pyrolysis‐gas chromatography/mass spectrometry, and microscale combustion flow calorimetry. Thermal decomposition pathways are derived and used to select suitable candidates as flame retardants for PBS. The fire behavior of the selected polymers is evaluated by forced‐flaming combustion in a cone calorimeter. The materials show two modes of action for flame retardancy: strong flame inhibition due to the release of a variety of molecules combined with charring in the solid state.     

Mannose‐Decorated Multicomponent Supramolecular Polymers Trigger Effective Uptake into Antigen‐Presenting Cells

A modular route to prepare functional self‐assembling dendritic peptide amphiphiles decorated with mannosides, to effectively target antigen‐presenting cells, such as macrophages, is reported. The monomeric building blocks were equipped with tetra(ethylene glycol)s (TEGs) or labeled with a Cy3 fluorescent probe. Experiments on the uptake of the multifunctional supramolecular particles into murine macrophages (Mφs) were monitored by confocal microscopy and fluorescence‐activated cell sorting. Mannose‐decorated supramolecular polymers trigger a significantly higher cellular uptake and distribution, relative to TEG carrying bare polymers. No cytotoxicity or negative impact on cytokine production of the treated Mφs was observed, which emphasized their biocompatibility. The modular nature of the multicomponent supramolecular polymer coassembly protocol is a promising platform to develop fully synthetic multifunctional vaccines, for example, in cancer immunotherapy.     

Detection of Wear in One-Cathode Plasma Torch Electrodes and its Impact on Velocity and Temperature of Injected Particles

Wear at the electrode surfaces of a one-cathode plasma torch changes the characteristic fluctuation pattern of the plasma jet. This affects the trajectory of the particles injected into the plasma jet in a non-controllable way, which degrades the reproducibility of the process. Time-based voltage measurements and Fourier analysis were carried out on a one-cathode F4 torch at different wear conditions to determine the evolution of wear dependant characteristics. A significant correlation is observed between increasing torch wear and decreasing voltage roughness and high frequency noise. Furthermore, by means of particle diagnostic systems, the change in the particle velocity and temperature has been measured. The variations of the particle characteristics are significant and thus an influence on the sprayed coating microstructure is to be expected. This article is an invited paper selected from presentations at the 2007 International Thermal Spray Conference and has been expanded from the original presentation. It is simultaneously published in Global Coating Solutions, Proceedings of the 2007 International Thermal Spray Conference, Beijing, China, May 14-16, 2007, Basil R. Marple, Margaret M. Hyland, Yuk-Chiu Lau, Chang-Jiu Li, Rogerio S. Lima, and Ghislain Montavon, Ed., ASM International, Materials Park, OH, 2007.     

Correlation between spraying conditions and microcrack density and their influence on thermal cycling life of thermal barrier coatings

It is generally known that the porosity of thermal barrier coatings is essential to guarantee a sufficiently high strain tolerance of the coating during thermal cycling. However, much less is known about the influence of the specific morphology of porosity, such as microcracks and typically larger pores, on the performance of the coatings. Both features are usually formed during plasma spraying of yttria-stabilized zirconia (YSZ) thermal barrier coatings (TBCs). In this investigation, the influence of microcracks on the thermal cycling behavior was studied. The amount of microcracks within YSZ thermal barrier coatings was changed by changing the powder-feeding rate. Only small changes of the total porosity were observed. Mercury porosimetry served as a tool to investigate both the amount of microcracks and pores in the coating. Additionally, microcrack densities were determined from metallographical investigations. A linear dependence between the amount of fine pores determined by Hg porosimetry and the crack density was obtained for one set of coatings. Thermal cycling TBC specimens with different microcrack densities were produced and tested in a gas burner test facility. At high surface temperatures (above 1300 °C), failure occurred in the ceramic close to the surface. Under these conditions, the samples with increased horizontal microcrack densities showed a significant increase of thermal cycling life.     

Data mining in resistance spot welding

Resistance spot welding is the dominant process in the present mass production of steel constructions without sealing requirements with single sheet thicknesses up to 3 mm. Two of the main applications of resistance spot welding are the automobile and the railway vehicle manufacturing industry. The majority of these connections has safety-related character and therefore they must not fall below a certain weld diameter. Since resistance spot welding has been established, this weld diameter has been usually used as the gold standard. Despite intensive efforts, there has not been found yet a reliable method to detect this connection quality non-destructively. Considerable amounts of money and steel sheets are wasted on making sure that the process does not result in faulty joints. The indication of the weld diameter by in-process monitoring in a reliable way would allow the quality documentation of joints during the welding process and additionally lead through demand-actuated milling cycles to a substantial decrease of electrode consumption. An annual, estimated reduction in the seven- to nine-figure range could be achieved. It has an important impact, because the economics of the process is essentially characterized by the electrode caps (Klages 24). We propose a simple and straightforward approach using data mining techniques to accurately predict the weld diameter from recorded data during the welding process. In this paper, we describe the methods used during data preprocessing and segmentation, feature extraction and selection, and model creation and validation. We achieve promising results during an analysis of more than 3000 classified welds using a model tree as a predictor with a success rate of 93 %. In the future, we hope to validate our model with unseen welding data and implement it in a real world application.     

Laser confocal microscopical characterization of toughened epoxy resins: Correlations between structural features and mechanical properties

Laser confocal microscopy is used to analyze the morphology of an epoxy resin (DGEBA) modified with different amounts of toughening agent carboxyl terminated butadiene acrylonitrile (CTBN). The size and phase volume of the distributed spherical toughening particles is ranging from 0.7 to 1.6 µm and 5 to 40 vol %, respectively. These morphological parameters and particles/µm² reveal a nonlinear relationship with the amount of toughening agent. With increasing particle size and number the glass transition temperature and the tensile modulus are decreasing, whereas the fracture toughness increases. Particles larger than 1.3 µm and a value of particles/µm² higher than 0.15 exhibit a more significant impact on the resin properties. Linear correlations between the rubber phase volume and the glass transition temperatures as well as the mechanical properties, i.e., tensile modulus and fracture toughness are ascertained. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46094.     

Elastic Fluctuations and Structural Heterogeneities in Metallic Glasses

Suppressing crystallization of a metallic melt results in a disordered solid, also known as a metallic glass. One may conclude that a metallic glass is free of defined structural length scales beyond some atomic‐scale value that characterizes short‐ and medium‐range order. While it is well known from atomistic modeling that a metallic glass is structurally heterogeneous, heterogeneities at such a small length scale can hardly be resolved in experiments. This review highlights experimental insights into elastic fluctuations and structural heterogeneities that emerge at scales between a few nanometers and tens to hundreds of micrometers. It distinguishes between structural and property fluctuations in as‐cast metallic glasses, and heterogeneities introduced by elastic and inhomogeneous plastic deformation. As‐cast glasses reveal elastic fluctuations across 3 orders of magnitude, suggesting a hierarchy of length scales that can be tuned by thermomechanical processing. Similarly, nanoscale strain localization into shear bands drives the formation of structural and elastic heterogeneities at both the nano‐ and the microscale. It is proposed that both types of fluctuations will allow one to quantitatively define structure–property relationships via measurable length scales—an approach that has largely contributed to the engineering success of crystalline metals.     

Clustering-based quantisation for PDE-based image compression

Optimal known pixel data for inpainting in compression codecs based on partial differential equations is real-valued and thereby expensive to store. Thus, quantisation is required for efficient encoding. In this paper, we interpret the quantisation step as a clustering problem. Due to the global impact of each known pixel and correlations between spatial and tonal data, we investigate the central question, which kind of feature vectors should be used for clustering with popular strategies such as k-means. Our findings show that the number of colours can be reduced significantly without impacting the reconstruction quality. Surprisingly, these benefits are negated by an increased coding cost in compression applications.     

A survey of skyline processing in highly distributed environments

During the last decades, data management and storage have become increasingly distributed. Advanced query operators, such as skyline queries, are necessary in order to help users to handle the huge amount of available data by identifying a set of interesting data objects. Skyline query processing in highly distributed environments poses inherent challenges and demands and requires non-traditional techniques due to the distribution of content and the lack of global knowledge. This paper surveys this interesting and still evolving research area, so that readers can easily obtain an overview of the state-of-the-art. We outline the objectives and the main principles that any distributed skyline approach has to fulfill, leading to useful guidelines for developing algorithms for distributed skyline processing. We review in detail existing approaches that are applicable for highly distributed environments, clarify the assumptions of each approach, and provide a comparative performance analysis. Moreover, we study the skyline variants each approach supports. Our analysis leads to a taxonomy of existing approaches. Finally, we present interesting research topics on distributed skyline computation that have not yet been explored.     

Roheisen – eine Handelsware zur Stahlerzeugung in den römerzeitlichen Schmieden

Five metal samples yielded by excavations in two Roman-era occupation layers in the Roman city of Teurnia in St. Peter-in-Holz, Lendorf parish, Carinthia, were handed over to us by the Landesmuseum Kärnten (Provincial Museum of Carinthia) for metallurgical analyses. All five metal samples are pig iron raw products with graphite flakes discernible in the structure and acicular cementite crystals in a ledeburitic matrix. According to the results of light-optical microscopy, the overall carbon content in the pig iron samples is greater than 4.3?% weight.