Preferential Nucleation of Dislocation Loops under Stress Explained by A15 Frank-Kasper Nanophases in Aluminum.

The asymmetric distribution of geometrically equivalent defects is a long-standing problem in materials science. In this study, we investigate the preferential nucleation of interstitial dislocation loops in specific planes in stressed aluminum, commonly observed experimentally, and seek to clarify the underlying mechanism. For this purpose, we consider a structural change in the geometry of defects, specifically the transformation of 3D compact A15 clusters into 2D Frank loops.

Compact A15 Frank-Kasper nano-phases at the origin of dislocation loops in face-centred cubic metals.

It is generally considered that the elementary building blocks of defects in face-centred cubic (fcc) metals, e.g., interstitial dumbbells, coalesce directly into ever larger 2D dislocation loops, implying a continuous coarsening process.

Capabilities and limits of autoencoders for extracting collective variables in atomistic materials science.

Free energy calculations in materials science are routinely hindered by the need to provide reaction coordinates that can meaningfully partition atomic configuration space, a prerequisite for most enhanced sampling approaches. Recent studies on molecular systems have highlighted the possibility of constructing appropriate collective variables directly from atomic motions through deep learning techniques. Here we extend this class of approaches to condensed matter problems, for which we encode the finite temperature collective variable by an iterative procedure starting from 0 K features of the energy landscape activation events or migration mechanisms given by a minimum - saddle point - minimum sequence.

On Sampling Minimum Energy Path.

Sampling the minimum energy path (MEP) between two minima of a system is often hindered by the presence of an energy barrier separating the two metastable states. As a consequence, direct sampling based on molecular dynamics or Markov Chain Monte Carlo methods becomes inefficient, the crossing of the energy barrier being associated to a rare event. Augmented sampling methods based on the definition of collective variables or reaction coordinates allow us to circumvent this limitation at the price of an arbitrary choice of the dimensionality reduction algorithm.