Related papers: Kob-Andersen model crystal structure: genetic algo…
We have developed an efficient and reliable methodology for crystal structure prediction, merging ab initio total-energy calculations and a specifically devised evolutionary algorithm. This method allows one to predict the most stable…
Supercooled liquids are kinetically trapped materials in which the transition to a thermodynamically more stable state with long-range order is strongly suppressed. To assess the glass-forming abilities of a liquid empirical rules exist,…
The swap Monte Carlo algorithm allows the preparation of highly stable glassy configurations for a number of glass-formers, but is inefficient for some models, such as the much studied binary Kob-Andersen (KA) mixture. We have recently…
The prediction of energetically stable crystal structures formed by a given chemical composition is a central problem in solid-state physics. In principle, the crystalline state of assembled atoms can be determined by optimizing the energy…
We present new results reflecting the analogies between the Kob-Andersen model and other glassy systems. Studying the stability of the blocked configurations above and below the transition we also give arguments that supports their…
Evolutionary crystal structure prediction proved to be a powerful approach for studying a wide range of materials. Here, we present a specifically designed algorithm for the prediction of the structure of complex crystals consisting of…
Using molecular dynamics simulations, with a realistic many-body embedded-atom potential, and a novel method to characterize local order, we study the structure of pure nickel during the rapid quench of the liquid and in the resulting…
At density 1.2 the Kob-Andersen binary Lennard-Jones liquid partly crystallizes in the temperature interval [0.39, 0.44] after typically 10-100 microseconds (Argon units). The crystallization is initiated by a phase separation where the…
Molecular crystals often exist in multiple competing polymorphs, showing significantly different physico-chemical properties. Computational crystal structure prediction is key to interpret and guide the search for the most stable or useful…
Complex crystal structures are composed of multiple local environments, and how this type of order emerges spontaneously during crystal growth has yet to be fully understood. We study crystal growth across various structures and along…
Recently the supercooled Wahnstrom binary Lennard-Jones mixture was partially crystallized into ${\rm MgZn_2}$ phase crystals in lengthy Molecular Dynamics simulations. We present Molecular Dynamics simulations of a modified Kob-Andersen…
Crucial to gaining control over crystallisation in multicomponent materials or accurately modelling rheological behaviour of magma flows is to understand the mechanisms by which crystal nuclei form. The microscopic nature of such nuclei,…
Time-dependent dynamical properties of a fluid can not be estimated from a single configuration without performing a simulation. Here we show, however, that the scaling properties of both structure and dynamics can be predicted from a…
Autonomous materials discovery with desired properties is one of the ultimate goals for materials science, and the current studies have been focusing mostly on high-throughput screening based on density functional theory calculations and…
Reliable and robust methods of predicting the crystal structure of a compound, based only on its chemical composition, is crucial to the study of materials and their applications. Despite considerable ongoing research efforts, crystal…
The physical behavior of glass-forming liquids presents complex features of both dynamic and thermodynamic nature. Some studies indicate the presence of thermodynamic anomalies and of crossovers in the dynamic properties, but their origin…
Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structure-property relationships. Nearly all available models rely…
The local organisation of a simulated glass-forming mixture due to Kob and Andersen is analysed. Evidence is presented for a structural transition from triangulated coordination polyhedra to cubic as the number fraction of the smaller…
The classic Kob-Andersen (KA) binary Lennard-Jones mixtures which are designed to prevent crystallization has been extensively studied in simulation of slow dynamics. Although crystallization can occur if a liquid system is cooled slowly,…
Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has emerged as a powerful tool for advancing this understanding and…