arXiv subjects

Silvia Richter

Publications and source records attributed to Silvia Richter.

2 recordsLinked to original sources

arXiv2026

EBSD and Subtle Crystallographic Differences - A Study of Resolving Interlayer Spacings in Nb-Ni and Nb-Co mu-phases

In ordered intermetallics, slight variations in lattice site occupancy and specific interlayer spacings have been identified as the sources of significant changes in critical resolved shear stress and therefore how a given phase may affect alloy properties. So far, atom positions and lattice site occupancies have traditionally been characterised by high-resolution transmission electron microscopy (HR-TEM) and X-ray diffraction (XRD), which are methods that offer either local detail or high statistical significance but not both. Electron backscatter diffraction (EBSD), by contrast, provides high spatial resolution across large sample areas and therefore, has the potential to enable the local investigation of interlayer spacing and site lattice occupancy with improved statistical reliability. The objectives of the study are to benchmark EBSDs capability for resolving these subtle features and to correlate them with compositional and mechanical properties. In this case study, we therefore show that EBSD can resolve key crystallographic features of mu-phase intermetallics, specifically interlayer spacings. We combine pattern matching with large-scale dynamical simulations of template libraries guided by XRD based information on lattice parameters. For this, we generate structures that vary in the spacing between triple-layer and Kagome layer and in the site lattice occupancy of the 3a site. This approach successfully predicts the change of interlayer spacing between Kagome and triple layers in Nb-Co and Nb-Ni mu-phases, in good agreement with XRD and HR-TEM.

cond-mat.mtrl-sci↗

arXiv2014

The LAMA Planner: Guiding Cost-Based Anytime Planning with Landmarks

LAMA is a classical planning system based on heuristic forward search. Its core feature is the use of a pseudo-heuristic derived from landmarks, propositional formulas that must be true in every solution of a planning task. LAMA builds on the Fast Downward planning system, using finite-domain rather than binary state variables and multi-heuristic search. The latter is employed to combine the landmark heuristic with a variant of the well-known FF heuristic. Both heuristics are cost-sensitive, focusing on high-quality solutions in the case where actions have non-uniform cost. A weighted A* search is used with iteratively decreasing weights, so that the planner continues to search for plans of better quality until the search is terminated. LAMA showed best performance among all planners in the sequential satisficing track of the International Planning Competition 2008. In this paper we present the system in detail and investigate which features of LAMA are crucial for its performance. We present individual results for some of the domains used at the competition, demonstrating good and bad cases for the techniques implemented in LAMA. Overall, we find that using landmarks improves performance, whereas the incorporation of action costs into the heuristic estimators proves not to be beneficial. We show that in some domains a search that ignores cost solves far more problems, raising the question of how to deal with action costs more effectively in the future. The iterated weighted A* search greatly improves results, and shows synergy effects with the use of landmarks.

cs.AI↗