activity
20222026
most citedMachine Learning Force Field for Thermal Oxidation of Silicon

3 citations · 7 across the 6 of their papers we have counts for

collaborators

9 papers

cond-mat.mtrl-sci2026

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…

cond-mat.mes-hall2026★ 1 cited

Resonant magnetic proximity hot spots in Co/hBN/graphene

Klaus Zollner, Lukas Cvitkovich, Riccardo Silvioli +2

Magnetic proximity effects in Co/hBN/graphene heterostructures are systematically analyzed via first-principles calculations, demonstrating a pronounced localized spatial variation…

cond-mat.mtrl-sci2025

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…

cond-mat.mes-hall2025★ 2 cited

Valley physics in the two bands model for SiGe heterostructures and spin qubits

Tancredi Salamone, Biel Martinez Diaz, Jing Li +2

We discuss the choice and implementation of inter-valley potentials in the so-called two bands model for the opposite , or valleys of silicon…

cond-mat.mtrl-sci2025

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…

cond-mat.mes-hall2025

Spin injection and detection in all-van der Waals 2D devices

Jan Bärenfänger, Klaus Zollner, Lukas Cvitkovich +7

In this work we report efficient out-of-plane spin injection and detection in an all-van der Waals based heterostructure using only exfoliated 2D materials. We demonstrate spin inj…

cond-mat.mtrl-sci2024★ 3 cited

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…

cond-mat.mes-hall2024★ 1 cited

Coherence limit due to hyperfine interaction with nuclei in the barrier material of Si spin qubits

Lukas Cvitkovich, Peter Stano, Christoph Wilhelmer +4

On the quest to understand and reduce environmental noise in Si spin qubits, hyperfine interactions between electron and nuclear spins impose a major challenge. Silicon is a promis…

cond-mat.mtrl-sci2022

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,…