most citedMinimalist machine-learned interatomic potentials can predict complex structural behaviors accurately

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2026

Intrinsic switching leads to oxygen diffusion and breakdown in hafnia ferroelectrics

Xabier Diaz de Cerio, Iñigo Robredo-Magro, Jorge Íñiguez-González

Conventional ferroelectrics exhibit well-defined polarization states linked through electric switching. In fluorite-structured ferroelectrics like hafnia, though, switching and oxy…

cond-mat.mtrl-sci2026

Effective dynamic constants for nonequilibrium third-principles simulations

Mauro Pulzone, Iñigo Robredo-Magro, Jorge Íñiguez-González

Computational studies of the thermodynamic properties of materials at the mesoscopic and macroscopic scales -- involving lengths and times of at least m and s, respectively -…

cond-mat.mtrl-sci2026

A family tree for hafnia

Nicolaie Cernov, Jorge Íñiguez-González, Hugo Aramberri

Several candidate reference phases have been proposed to discuss phase transitions and ferroelectricity in hafnia in recent years. Although these proposals comply with crystallogra…

cond-mat.mtrl-sci2025★ 1 cited

Minimalist machine-learned interatomic potentials can predict complex structural behaviors accurately

Iñigo Robredo-Magro, Binayak Mukherjee, Hugo Aramberri +1

The past decade has witnessed a spectacular development of machine-learned interatomic potentials (MLIPs), to the extent that they are already the approach of choice for most atomi…

cond-mat.mtrl-sci2025

Chiral soft mode transition driven by strain in ferroelectric bubble domains

Urmimala Dey, Natalya S. Fedorova, Jorge Íñiguez-González +1

Chirality in solids is attracting growing attention as a potential ferroic order, yet virtually no paradigmatic example of a soft-mode achiral-to-chiral phase transition has been f…