Related papers: AFLOW for alloys
Phase-field models have proven indispensable for deciphering the microstructure complexities inherent in multicomponent systems. The confluence of varying phase molar volumes presents unique challenges. Understanding the impact of molar…
Amorphous solids are ubiquitous among natural and man-made materials. Often used as structural materials for their attractive mechanical properties, their utility depends critically on their response to applied stresses. Processes…
Crystal structure prediction is a long-standing challenge in materials science, with most data-driven methods developed for inorganic systems. This leaves an important gap for organic crystals, which are central to pharmaceuticals,…
The paper deals with a full annealing process, for example for a metal alloy perturbed by some fractional noise caused by conditions in furnace such as initial temperature, initial structure of material itsel. The energy of the heating…
We revisit the reliability of metallicity estimates of high velocity clouds with the help of hydrodynamical simulations. We quantify the effect of accretion and viewing angle on metallicity estimates derived from absorption lines. Model…
Designing multi-functional alloys requires exploring high-dimensional composition-structure-property spaces, yet current tools are limited to low-dimensional projections and offer limited support for sensitivity or multi-objective tradeoff…
Tailoring material properties often requires understanding the solidification process. Herein, we introduce the geometric descriptor Soliquidy, which numerically captures the Euclidean transport cost between the translationally disordered…
A key property of glass forming alloys, the anomalously small volume difference with respect to the crystal, is shown to arise as a direct consequence of the soft repulsive potentials between metals. This feature of the inter-atomic…
Crystallization is a process of great practical relevance in which rare but crucial fluctuations lead to the formation of a solid phase starting from the liquid. Like in all first order first transitions there is an interplay between…
The prediction of glass forming ability (GFA) and various properties in bulk metallic glasses (BMGs) pose a challenge due to the unique disordered atomic structure in this type of materials. Machine learning shows the potential ability to…
We present recent Monte Carlo results on surfaces of bcc-structured binary alloys which undergo an order-disorder phase transformation in the bulk. In particular, we discuss surface order and surface induced disorder at the bulk transition…
The most critical limitation to the wide-scale use of classical molecular dynamics for alloy design is the availability of suitable interatomic potentials. In this work, we demonstrate a simple procedure to generate a library of accurate…
This paper reviews recent advances in the field of metallic glasses, focusing on the development of novel experimental techniques and in silico models. We discuss progress in experimental characterization, additive manufacturing, multiscale…
Rapid solidification leads to unique microstructural features, where a less studied topic is the formation of various crystalline defects, including high dislocation densities, as well as gradients and splitting of the crystalline…
The LOFAR radio telescope creates Petabytes of data per year. This data is important for many scientific projects. The data needs to be efficiently processed within the timespan of these projects in order to maximize the scientific impact.…
Micrometre sized colloidal particles can be viewed as large atoms with tailorable size, shape and interactions. These building blocks can assemble into extremely rich structures and phases, in which the thermal motions of particles can be…
In order to better model complex real-world data such as multiphase flow, one approach is to develop pattern recognition techniques and robust features that capture the relevant information. In this paper, we use deep learning methods, and…
Glasses offer a broad range of tunable thermophysical properties that are linked to their compositions. However, it is challenging to establish a universal composition-property relation of glasses due to their enormous composition and…
Materials design has traditionally evolved through trial-error approaches, mainly due to the non-local relationship between microstructures and properties such as strength and toughness. We propose 'alloy informatics' as a machine learning…
The development of high-entropy alloys (HEAs) has marked a paradigm shift in alloy design, moving away from traditional methods that prioritize a dominant base metal enhanced by minor elements. HEAs instead incorporate multiple alloying…