activity
20052022
most citedOn-the-fly machine learning force field generation: Application to melting points

688 citations · 2.1k across the 15 of their papers we have counts for

collaborators

34 papers

cond-mat.mtrl-sci2022

Temperature-dependent anharmonic phonons in quantum paraelectric KTaO by first principles and machine-learned force fields

Luigi Ranalli, Carla Verdi, Lorenzo Monacelli +3

Understanding collective phenomena in quantum materials from first principles is a promising route toward engineering materials properties on demand and designing new functionaliti…

cond-mat.mtrl-sci2021

Thermal transport and phase transitions of zirconia by on-the-fly machine-learned interatomic potentials

Carla Verdi, Ferenc Karsai, Peitao Liu +2

Machine-learned interatomic potentials enable realistic finite temperature calculations of complex materials properties with first-principles accuracy. It is not yet clear, however…

cond-mat.mtrl-sci2021

Optical and excitonic properties of transition metal oxide perovskites by the Bethe-Salpeter equation

Lorenzo Varrassi, Peitao Liu, Zeynep Ergönenc Yavas +3

We present a systematic investigation of the role and importance of excitonic effects on the optical properties of transitions metal oxide perovskites. A representative set of four…

cond-mat.mtrl-sci2021

Electronic state unfolding for plane waves: energy bands, Fermi surfaces and spectral functions

David Dirnberger, Georg Kresse, Cesare Franchini +1

Modern computing facilities grant access to first-principles density-functional theory study of complex physical and chemical phenomena in materials, that require large supercell t…

physics.chem-ph202050 cited

Local embedding of Coupled Cluster theory into the Random Phase Approximation using plane-waves

Tobias Schäfer, Florian Libisch, Georg Kresse +1

We present an embedding approach to treat local electron correlation effects in periodic environments. In a single, consistent framework, our plane-wave based scheme embeds a local…

physics.chem-ph20209 cited

New insights into the 1D carbon chain through the RPA

Benjamin Ramberger, Georg Kresse

We investigated the electronic and structural properties of the infinite linear carbon chain (carbyne) using density functional theory (DFT) and the random phase approximation (RPA…