3 papers
cond-mat.mtrl-sci2026
Machine Learning Materials Properties by Encoding Orbital-Projected Density of States
Paulo Pires, Pierre-Paul De Breuck, Mauro Fava +2
Graph neural networks have become the dominant machine-learning architecture for predicting materials properties from crystal structures. Yet the initialization of atomic node feat…
cond-mat.mtrl-sci2025
Handedness selection and hysteresis of chiral orders in crystals
Mauro Fava, Aldo H. Romero, Eric Bousquet
A phase transition can drive the spontaneous emergence of chiral orders in crystals below a critical temperature. However, selecting either a right- or a left-handed phase with the…
cond-mat.mtrl-sci2020
How do defects limit the ultrahigh thermal conductivity of BAs? A first principles study
Mauro Fava, Nakib Haider Protik, Chunhua Li +6
The promise enabled by BAs high thermal conductivity in power electronics cannot be assessed without taking into account the reduction incurred when doping the material. Using firs…