computational materials 1octahedral tilting 1perovskite oxides 1structural modeling 1symmetry breaking 1
From the 1 of 3 linked papers with an AI index.
3 papers
cond-mat.mtrl-sci2026
Ordered-to-disordered transfer learning with graph neural networks for formation-energy and HOMO-LUMO gap prediction in high-entropy perovskite oxides
Panupol Untarabut, Narjes Jomaa, Sylvian Cadars +4
High-entropy perovskite oxides (HEPOs) represent a chemically complex class of materials with promising functional properties, yet their vast compositional space and, chemical/stru…
cond-mat.mtrl-sci2026
Mapping the influence of symmetry breaking in structure-property relationships of ABO perovskites
Panupol Untarabut, Sylvian Cadars, Fabien Pascale +5
The paper introduces an efficient computational framework to generate and explore composition‑dependent structural models of ABO₃ perovskites across low‑ and high‑symmetry phases,…
cond-mat.mtrl-sci2026
Modeling phase separation in polymer-derived silicon carbonitride ceramics through extended machine learning molecular dynamics
Fabien Mortier, Sylvian Cadars, Olivier Masson +5
Polymer-derived ceramics combine the thermal stability of ceramics with the versatile properties of carbon domains, but modeling their atomic-scale evolution during processing rema…