504 publications from this institution
Machine-learned interatomic potentials enable realistic finite temperature calculations of complex materials properties with first-principles accuracy. It is not yet clear, however, how accurately they describe anharmonic properties, which are crucial for predicting the lattice thermal conductivity and phase transitions in solids and, thus, shape their technological applications. Here we employ a recently developed on-the-fly learning technique based on molecular dynamics and Bayesian inference in order to generate an interatomic potential capable to describe the thermodynamic properties of zirconia, an important transition metal oxide. This machine-learned potential accurately captures the temperature-induced phase transitions below the melting point. We further showcase the predictive power of the potential by calculating the heat transport on the basis of Green–Kubo theory, which allows to account for anharmonic effects to all orders. This study indicates that machine-learned potentials trained on the fly offer a routine solution for accurate and efficient simulations of the thermodynamic properties of a vast class of anharmonic materials.
By performing accurate ab-initio density functional theory calculations, we study the role of $4f$ electrons in stabilizing the magnetic-field-induced ferroelectric state of DyFeO$_{3}$. We confirm that the ferroelectric polarization is driven by an exchange-strictive mechanism, working between adjacent spin-polarized Fe and Dy layers, as suggested by Y. Tokunaga [Phys. Rev. Lett, \textbf{101}, 097205 (2008)]. A careful electronic structure analysis suggests that coupling between Dy and Fe spin sublattices is mediated by Dy-$d$ and O-$2p$ hybridization. Our results are robust with respect to the different computational schemes used for $d$ and $f$ localized states, such as the DFT+$U$ method, the Heyd-Scuseria-Ernzerhof (HSE) hybrid functional and the GW approach. Our findings indicate that the interaction between the $f$ and $d$ sublattice might be used to tailor ferroelectric and magnetic properties of multiferroic compounds.
