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A clear understanding of the dynamic behavior of metals is critical for developing superior structural materials as well as for improving material processing techniques such as cold spray and shot peening. Using a high velocity (from 120…

The recording of planetary magnetic fields is often attributed to uniformly-magnetised nanoscopic iron oxides, called single-domain (SD). Yet, the main magnetic constituents of rocks are more complex, non-uniformly magnetised grains in…

Solid-state nanopores have received substantial attention in the past years owing to their simplicity and potential applications expected in genomics, sensing, archival information storage, and computing. The underlying sensing technique of…

The discovery of atomic monolayer magnetic materials has stimulated intense research activities in the two-dimensional (2D) van der Waals (vdW) materials community. The field is growing rapidly and there has been a large class of 2D vdW…

Adhesion-independent migration is a prominent mode of cell motility in confined environments, yet the physical principles that guide such movement remain incompletely understood. We present a phase-field model for simulating the motility of…

Core convection and dynamo activity deep within rotating A-type stars of 2 solar masses are studied with 3--D nonlinear simulations. Our modeling considers the inner 30% by radius of such stars, thus capturing within a spherical domain the…

Early-type stars have convective cores due to a steep temperature gradient produced by the CNO cycle. These cores can host dynamos, and the generated magnetic fields can be relevant to explain the magnetism observed in Ap/Bp stars. Our main…

The transport properties of diluted magnetic semiconductors (DMS) are calculated using dynamical mean field theory (DMFT) and Boltzmann transport theory. Within DMFT we study the density of states and the dc-resistivity, which are strongly…

Earth's inner core exhibits an unusually high Poisson's ratio and noticeable elastic anisotropy. The mechanisms responsible for these features are critical for understanding the evolution of the Earth but remain unclear. This study…

Machine Learning (ML) techniques are revolutionizing the way to perform efficient materials modeling. Nevertheless, not all the ML approaches allow for the understanding of microscopic mechanisms at play in different phenomena. To address…

In this paper we present an overview of recent progress made in the understanding of the spin-torque induced magnetization dynamics in nanodevices using mesoscopic micromagnetic simulations. We first specify how a spin-torque term may be…

There is increasingly strong observational evidence that slow magnetoacoustic modes arise in the solar atmosphere. Solar magneto-seismology is a novel tool to derive otherwise directly un-measurable properties of the solar atmosphere when…

Coarse-graining is central to reducing dimensionality in molecular dynamics, and is typically characterized by a mapping which projects the full state of the system to a smaller class of variables. While extensive literature has been…

Transition-metal dichalcogenides (TMDs) are layered compounds that support many electronic phases, including various charge density waves, superconducting, and Mott insulating states. Their intercalation with magnetic ions introduces…

Transferrins are proteins responsible for transporting metal ions in all vertebrates. However, the iron binding properties of transferrins remain poorly understood. Iron, as a transition metal, forms ions with partially-occupied 3d…

Using Monte Carlo Simulations (MCS), based the Metropolis algorithm, we examine in this study, the magnetic properties of the rare earth based compound GdN. In a first step, we discuss and study the ground state phase diagrams explored in…

Magnetic reconnection is an explosive process that accelerates particles to high energies in Earth's magnetosphere, offering a unique natural laboratory to study this phenomenon. This study investigates how well data-driven fully kinetic…

We investigate a simple tight-binding Hamiltonian to understand the stability of spin-polarized transport of states with an arbitrary spin content in the presence of disorder. The general spin state is made to pass through a linear chain of…

Coronal seismology is a diagnostic tool used in solar physics for measuring parameters that are otherwise hard to measure; of these parameters, magnetic field values are arguably the most important. The parameters are inferred by combining…

Machine Learning (ML) plays an increasingly important role in the discovery and design of new materials. In this paper, we demonstrate the potential of ML for materials research using hard-magnetic phases as an illustrative case. We build…