3 citations · 7 across the 6 of their papers we have counts for
5 papers · 1 filter
Gate-tunable magnetic damping in van der Waals Heterostructures
Lukas Cvitkovich, Klaus Zollner, Jaroslav Fabian
Active control of magnetic damping is a crucial capability for the development of low-power, tunable spintronic devices. In this work, we demonstrate that the intrinsic magnetic da…
Valley Splittings in Si/SiGe Heterostructures from First Principles
Lukas Cvitkovich, Tancredi Salamone, Christoph Wilhelmer +3
We compute valley splittings in Si/SiGe superlattices using ab initio density functional theory (DFT). This first-principle approach is expected to provide an excellent description…
Machine Learning Prediction of Magnetic Proximity Effect in van der Waals Heterostructures: From Atoms to Moiré
Lukas Cvitkovich, Klaus Zollner, Jaroslav Fabian
We introduce a machine learning framework that efficiently predicts large-scale proximity-induced magnetism in van der Waals heterostructures, overcoming the high computational cos…
Machine Learning Force Field for Thermal Oxidation of Silicon
Lukas Cvitkovich, Franz Fehringer, Christoph Wilhelmer +3
Looking back at seven decades of highly extensive application in the semiconductor industry, silicon and its native oxide SiO are still at the heart of several technological de…
Modeling the Initial Stages of Si(100) Thermal Oxidation: An Ab-initio Approach
Lukas Cvitkovich, Dominic Waldhör, Al-Moatassem El-Sayed +3
Silicon together with its native oxide SiO was recognized as an outstanding material system for the semiconductor industry in the 1950s. In state-of-the-art device technology,…