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.

A Monolingual Tree-based Translation Model for Sentence Simplification

Abstract: In this paper, we consider sentence simplification as a special form of translation with the complex sentence as the source and the simple sentence as the target. We propose a Tree-based Simplification Model (TSM), which, to our knowledge, is the first statistical simplification model covering splitting, dropping, reordering and substitution integrally. We also describe an efficient method to train our model with a large-scale parallel dataset obtained from the Wikipedia and Simple Wikipedia. The evaluation shows that our model achieves better readability scores than a set of baseline systems.

Universal temperature and body-mass scaling of feeding rates.

Abstract: Knowledge of feeding rates is the basis to understand interaction strength and subsequently the stability of ecosystems and biodiversity. Feeding rates, as all biological rates, depend on consumer and resource body masses and environmental temperature. Despite five decades of research on functional responses as quantitative models of feeding rates, a unifying framework of how they scale with body masses and temperature is still lacking. This is perplexing, considering that the strength of functional responses (i.e. interaction strengths) is crucially important for the stability of simple consumer–resource systems and the persistence, sustainability and biodiversity of complex communities. Here, we present the largest currently available database on functional response parameters and their scaling with body mass and temperature. Moreover, these data are integrated across ecosystems and metabolic types of species. Surprisingly, we found general temperature dependencies that differed from the Arrhenius terms predicted by metabolic models. Additionally, the body-mass-scaling relationships were more complex than expected and differed across ecosystems and metabolic types. At local scales (taxonomically narrow groups of consumer–resource pairs), we found hump-shaped deviations from the temperature and body-mass-scaling relationships. Despite the complexity of our results, these body-mass- and temperature-scaling models remain useful as a mechanistic basis for predicting the consequences of warming for interaction strengths, population dynamics and network stability across communities differing in their size structure.

Supported Gold Nanoparticles from Quantum Dot to Mesoscopic Size Scale: Effect of Electronic and Structural Properties on Catalytic Hydrogenation of Conjugated Functional Groups

Abstract: Titania- and zirconia-supported gold particles of 1−5 nm size, prepared by various routes of synthesis, were employed in the partial hydrogenation of acrolein. In-depth characterization of their structural and electronic properties by electron microscopy, electron paramagnetic resonance, and optical absorption spectroscopy aimed at disclosing the nature of the active sites controlling the hydrogenation of CO vs CC bonds. The structural characteristics of the catalysts, as mean particle size, size distribution, and dispersion, distinctly depend on the synthesis applied and the oxide support used whereby the highest gold dispersion (DAu = 0.78, Au/TiO2) results from a modified sol−gel technique. For extremely small gold particles on titania and zirconia (1.1 and 1.4 nm mean size), conduction electron spin resonance of the metal and paramagnetic F-centers (trapped electrons in oxygen vacancies) of the support were observed. Besides the influence of the surface geometry on the adsorption mode of the α,β-unsat...

Nanosensors: towards morphological control of gas sensing activity. SnO2, In2O3, ZnO and WO3 case studies

Abstract: Anisotropy is a basic property of single crystals. Dissimilar facets/surfaces have different geometric and electronic structure that results in dissimilar functional properties. Several case studies unambiguously demonstrated that the gas sensing activity of metal oxides is determined by the nature of surfaces exposed to ambient gas. Accordingly, a control over crystal morphology, i.e. over the angular relationships, size and shape of faces in a crystal, is required for the development of better sensors with increased selectivity and sensitivity in the chemical determination of gases. The first step toward this nanomorphological control of the gas sensing properties is the design and synthesis of well-defined nanocrystals which are uniform in size, shape and surface structure. These materials possess the planes of the symmetrical set {hkl} and must therefore behave identically in chemical reactions and adsorption processes. Because of these characteristics, the form-controlled nanocrystals are ideal candidates for fundamental studies of mechanisms of gas sensing which should involve (i) gas sensing measurements on specific surfaces, (ii) their atomistic/quantum chemical modelling and (ii) spectroscopic information obtained on same surfaces under operation conditions of sensors.