We present the magnetic Moment Tensor Potentials (mMTPs), a class of machine-learning
interatomic potentials, accurately reproducing both vibrational and magnetic degrees of …

The M4F project brings together the fusion and fission materials communities working on the
prediction of radiation damage production and evolution and their effects on the mechanical …

We propose a machine-learning interatomic potential for multi-component magnetic
materials. In this potential we consider magnetic moments as degrees of freedom (features) …

The development of classical interatomic potential for iron is a quite demanding task with a
long history background. A new interatomic potential for simulation of iron was created with …

The stress-induced reorientation of the low-symmetry defects due to substitution atom pairs
can give rise to an internal friction peak (Zener relaxation) and the first-nearest-neighbor …

In this work, a degenerate diffusion state is identified for common L12 intermetallics in well-
defined five-frequency model (FFM) and anti-site bridge model (ASB). The relative energy …

We investigate phase stability and vacancy formation in fcc Fe-Ni alloys over a broad
composition-temperature range, via a density functional theory parametrized effective …

The influence of a magnetic transition on Fe and Mn diffusion in bcc Fe–Mn alloys as a
function of Mn concentration is studied combining experimental measurements and DFT …

Predicting atomic diffusion in concentrated magnetic systems is challenging due to thermal
magnetic effects and complex magnetochemical interplay. We propose an efficient approach …

Diffusion analysis at the atomic scale in three orthogonal directions for both low-and high-
energy symmetric tilt grain boundaries (GBs) in bcc iron is presented. Using DFT, we report …