Leuven | More than two weeks ago
Towards the future generation of high speed optical modulator devices
Introduction: Thin epitaxial films of Barium Titanate (BaTiO3 or BTO) on Silicon (Si) substrates have garnered significant interest for their potential application as active layers in high-speed light modulators exploiting the Pockels effect. Despite the considerable attention from the optical photonic industry, large-scale device fabrication remains challenging due to a lack of comprehensive understanding regarding the influence of BTO crystalline structure on its electro-optical properties.
Objective: The primary objective of this proposed PhD research is to bridge this knowledge gap by systematically investigating the impact of BTO crystalline structure on its electro-optical characteristics through optimization of BTO epitaxy on Si substrates.
Methodology: The focus of the research will primarily be on employing molecular beam epitaxy as the main technique for growing BTO layers with the requisite quality. Alternative growth techniques will also be explored. The produced BTO layers will undergo thorough characterization, including assessment of stoichiometry, microstructure, crystallinity, strain state, and defectivity, utilizing techniques such as X-ray diffraction, atomic force microscopy, Rutherford backscattering spectroscopy, X-ray photoluminescence spectroscopy, and transmission electron microscopy.
Following characterization, the BTO samples will be processed in the lab, and their electro-optical properties will be meticulously investigated using an existing Pockels setup. The ultimate aim is to establish a comprehensive understanding of the relationship between growth parameters, BTO structural properties, and electro-optical characteristics.
Expectations from the Candidate: The PhD candidate is expected to:
Required background: materials science, physics, optical characterization
Type of work: 30% experimental, 30% characterization, 15% modeling/simulation, 15% literature, 10% reporting
Supervisor: Clement Merckling
Daily advisor: Marina Baryshnikova
The reference code for this position is 2024-163. Mention this reference code on your application form.