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: Computer science & Context (language use). 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.

Amorphous Si(Al)OC ceramic from polysiloxanes: bulk ceramic processing, crystallization behavior and applications

Abstract: Here we report on bulk Si–Al–O–C ceramics produced by pyrolysis of commercial poly(methylsilsesquioxane) precursors. Prior to the pyrolysis the precursors were cross-linked with a catalyst, or modified by the sol-gel-technique with an Al-containing alkoxide compound, namely alumatrane. This particular procedure yields amorphous ceramics with various compositions (Si1.00O1.60C0.80, Si1.00Al0.04O1.70C0.48, Si1.00Al0.07O1.80C0.49, and Si1.00Al0.11O1.90C0.49) after thermal decomposition at 1100 °C in Ar depending on the amount of Al-alkoxide used in the polymer reaction synthesis. The as-produced ceramics are amorphous and remain so up to 1300 °C. Phase separation accompanied by densification (1300–1500 °C) and formation of mullite at T > 1600 °C are the stages during heat-treatment. Bulk SiAlOC ceramics are characterized in terms of microstructure and crystallization in the temperature regime ranging from 1100 to 1700 °C. Aluminum-free SiOC forms SiC along with cracking of the bulk compacts. In contrast, the presence of Al in the SiOC matrix forms SiC and mullite and prevents micro cracking at elevated temperatures due to transient viscous sintering. The nano-crystals formed are embedded in an amorphous Si(Al)OC matrix in both cases. Potential application of polysiloxane derived SiOC ceramic in the field of ceramic micro electro mechanical systems (MEMS) is reported.

Unsupervised generation of data mining features from linked open data

Abstract: The quality of the results of a data mining process strongly depends on the quality of the data it processes. A good result is more likely to obtain the more useful background knowledge there is in a dataset. In this paper, we present a fully automatic approach for enriching data with features that are derived from Linked Open Data, a very large, openly available data collection. We identify six different types of feature generators, which are implemented in our open-source tool FeGeLOD. In four case studies, we show that our approach can be applied to different problems, ranging from classical data mining to ontology learning and ontology matching on the semantic web. The results show that features generated from publicly available information may allow data mining in problems where features are not available at all, as well as help improving the results for tasks where some features are already available.

Pore structure and surface area of silica SBA-15: influence of washing and scale-up.

Abstract: The removal of the surfactant (EO(20)PO(70)EO(20)) by washing before final calcination is a critical step in the synthesis of silica SBA-15 In contrast to washing with pure water or ethanol, washing with water and ethanol may, depending on the quantity of solvent used, alter the homogeneity and order of the pores, but also lead to an increase of the surface area of SBA-15 A reduction of solvent volume and a controlled washing protocol allow the synthesis of high surface area SBA-15 materials with a narrow monomodal pore size distribution For larger batch sizes the influence of the quantity of solvent on the quality of the SBA-15 is reduced

MobilityGraphs: Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering

Abstract: Learning more about people mobility is an important task for official decision makers and urban planners. Mobility data sets characterize the variation of the presence of people in different places over time as well as movements (or flows) of people between the places. The analysis of mobility data is challenging due to the need to analyze and compare spatial situations (i.e., presence and flows of people at certain time moments) and to gain an understanding of the spatio-temporal changes (variations of situations over time). Traditional flow visualizations usually fail due to massive clutter. Modern approaches offer limited support for investigating the complex variation of the movements over longer time periods.

Interesting Physical Properties of the New Spinel Phase of Si 3 N 4 and C 3 N 4

Abstract: The physical properties of the new high-pressure spinel phase of ${\mathrm{Si}}_{3}{\mathrm{N}}_{4}$ and ${\mathrm{C}}_{3}{\mathrm{N}}_{4}$ were studied by first-principles calculations. The presence of Si at the octahedral site and the elongated Si-N bonds under pressure have a profound effect on many properties of ${\mathrm{Si}}_{3}{\mathrm{N}}_{4}$ including lowering the compressibility, decreasing the direct band gap and effective mass, increasing the static dielectric constants, and enhancing covalent bonding. The last effect is explained by calculating the bond order and number of bonds. Possible routes of synthesis at lower pressure and potential applications are suggested.