Performance assessment of universal machine learning interatomic potentials: Challenges and directions for materials' surfaces

B Focassio, LP M. Freitas… - ACS Applied Materials & …, 2024 - ACS Publications
Machine learning interatomic potentials (MLIPs) are one of the main techniques in the
materials science toolbox, able to bridge ab initio accuracy with the computational efficiency …

Structural, surface and oxygen transport properties of Sm-doped Nd nickelates

VA Sadykov, EM Sadovskaya, YN Bespalko… - Solid State Ionics, 2024 - Elsevier
Ruddlesden–Popper phases are promising materials for solid oxide fuel cell/electrolyzer air
electrodes, oxygen separation membranes and other electrochemical devices due to their …