This work investigates solute transport due to self-interstitial defects and radiation induced
segregation tendencies in dilute ferritic alloys, by computing the transport coefficients of …

Prussian blue (PB) and its analogues (PBAs) are drawing attention as promising materials
for sodium-ion batteries and other applications, such as desalination of water. Because of …

Data-driven, or machine learning (ML), approaches have become viable alternatives to
semiempirical methods to construct interatomic potentials, due to their capacity to accurately …

Micro-alloying strongly affects the incubation period of void swelling in irradiated face-
centered cubic materials. However, the underlying mechanism, which relates to the …

Irradiation creates excess point defects in materials (vacancies and self-interstitial atoms),
which can be eliminated by mutual recombination, clustering, or annihilation of preexisting …

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

To better understand the hydrogen diffusion mechanisms in monoclinic zirconia that take
place in fuel rod cladding during reactor operation, we calculate the diffusion paths of …

Prussian blue analogs (PBAs) form crystals with large lattice voids that are suitable for the
capture, transport and storage of various interstitial ions. Recently, we introduced the …

Machine learning surrogate models employing atomic environment descriptors have found
wide applicability in materials science. In our previous work, this approach yielded accurate …

A phase-field model dedicated to dislocation climb under irradiation has been coupled to
point defects and chemical species transport equations. It allows to predict radiation induced …