The solid-liquid interface energy, r SL , is of major importance during phase transformation. It has a strong influence on solidification morphologies and the final grain structure. The ''grain boundary groove in an applied temperature gradient'' method developed by Gu¨ndu¨z et al. [6] was found to be suitable for measuring the solid-liquid interface energy in ternary alloy systems (e.g., Al-Cu-Ag). In order to measure the solid-liquid interface energy, a radial heat flow apparatus was constructed and assembled. This apparatus ensures a stable temperature gradient for hours and leads to grain boundary grooves in chemical equilibrium. After rapid quenching, the samples were metallographically prepared and the local curvature of the grooves was analyzed.To determine the interface energy, the Gibbs-Thomson equation was used, which requires the local curvature of the grain boundary grooves and the adherent local undercooling obtained from heat flux simulations on the scale of the grooves.

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Based on 2D phase-field simulations including fluid flow driven by natural convection, columnar dendritic growth of the β-solidifying Ti-48 at%Al alloy is characterised for different gravity levels ranging from 0 to ±15g. Depending on the direction of the gravity g with respect to the growth direction, different flow regimes emerge which show stable or unstable dendritic growth dynamics. When gravity and growth directions are parallel, the dendrite tips experience downward melt flow and individual dendrites grow in a stable manner with a rather small modification of the operating state. When gravity and growth directions are antiparallel, the impact on the operating state is larger. Eventually, at higher gravity levels the upward melt flow around the dendrite tips "destabilises" the dendritic morphology resulting in tip splitting, branching and local changes in the apparent dendrite growth direction which is an alternative mechanism for the adjustment of the primary dendrite arm spacing in addition to tertiary arm formation.

The property of any material is essentially determined by its microstructure. Numerical models are increasingly the focus of modern engineering as helpful tools for tailoring and optimization of custom-designed microstructures by suitable processing and alloy design. A huge variety of software tools is available to predict various microstructural aspects for different materials. In the general frame of an integrated computational materials engineering (ICME) approach, these microstructure models provide the link between models operating at the atomistic or electronic scales, and models operating on the macroscopic scale of the component and its processing. In view of an improved interoperability of all these different tools it is highly desirable to establish a standardized nomenclature and methodology for the exchange of microstructure data. The scope of this article is to provide a comprehensive system of metadata descriptors for the description of a 3D microstructure. The presented descriptors are limited to a mere geometric description of a static microstructure and have to be complemented by further descriptors, e.g. for properties, numerical representations, kinetic data, and others in the future. Further attributes to each descriptor, e.g. on data origin, data uncertainty, and data validity range are being defined in ongoing work. The proposed descriptors are intended to be independent of any specific numerical representation. The descriptors defined in this article may serve as a first basis for standardization and will simplify the data exchange between different numerical models, as well as promote the integration of experimental data into numerical models of microstructures. An HDF5 template data file for a simple, three phase Al-Cu microstructure being based on the defined descriptors complements this article.

Controlling a biped robot with a high degree of freedom to achieve stable movement patterns is still an open and complex problem, in particular within the RoboCup community. Thus, the development of control mechanisms for biped locomotion have become an important field of research. In this paper we introduce a model-free approach of biped motion generation, which specifies target angles for all driven joints and is based on a neural oscillator. It is potentially capable to control any servo motor driven biped robot, in particular those with a high degree of freedom, and requires only the identification of the robot's physical constants in order to provide an adequate simulation. The approach was implemented and successfully tested within a physical simulation of our target system -the 19-DoF Bioloid robot. The crucial task of identifying and optimizing appropriate parameter sets for this method was tackled using evolutionary algorithms. We could show, that the presented approach is applicable in generating walking patterns for the simulated biped robot. The work demonstrates, how the important parameters may be identified and optimized when applying evolutionary algorithms. Several so evolved controllers were capable of generating a robust biped walking behavior with relatively high walking speeds, even without using sensory information. In addition we present first results of laboratory experiments, where some of the evolved motions were tried to transfer to real hardware.