Philipp Maier
The initial discovery of graphene, a single layer of carbon atoms arranged in a hexagonal lattice, marked the advent of Dirac materials. Following graphene, researchers explored other fascinating two-dimensional materials, including topological insulators and a diverse class of new materials, some of which even exhibit superconductivity. These materials have opened up exciting possibilities for novel electronic properties and applications in various fields. Helium scattering is uniquely suited for studying these materials and enables the determination of surface properties that remain inaccessible to other experimental techniques.
This talk presents the results of my PhD work about the investigation of Dirac and 2D material surfaces using Helium atom scattering (HAS) and neutron scattering. Elastic helium scattering can be used to determine the lattice constant of the materials and material-specific atomic surface potential. Temperature-dependent measurements also allow conclusions to be drawn about the electron-phonon measurement or possible phase transitions. I studied the surface properties of various materials, including the transition metal dichalcogenide TaS2 and graphene on a silicon carbide substrate. A second major part of my Phd-work is the role of energy dissipation during surface diffusion upon these materials. In particular, I measured the surface dynamics of molecular water on hexagonal boron nitride at the Helium spin-echo method.
Finally, I analysed the adsorption behaviour pf Pyrazine on graphite by analysing neutron diffraction and neutron spin-echo measurements that were performed at the Institute Laue-Langevin in Grenoble.
Lisanne Demelius
The current trends in microfabrication call for deposition and patterning techniques able to meet the requirements set by the continuously decreasing feature sizes and the increasingly complex device architectures. The family of techniques called atomic layer processing enables thickness control on the scale of atomic monolayers, and the inherent chemical selectivity of atomic layer processing, i.e. deposition only occurs on surfaces reactive towards the chosen precursors, allows for area-selective growth that can be used in advanced maskless patterning strategies.
To date, research on these atomic layer processing techniques has been focused primarily on depositing inorganic films on inorganic substrates. With the rise of flexible electronics, the use of polymers as substrates becomes more and more important.
This work explores the role of substrate chemistry during different ZnO atomic layer processing techniques demonstrating how the choice and design of the polymer defines ZnO growth characteristics.
While atomic layer deposition (ALD) was employed to study the ZnO film growth on different polymer surfaces and investigate the effect of using oxygen plasma as a co-reactant as opposed to water vapor, atomic layer infiltration (ALI), also known as vapor phase infiltration (VPI), was used to infiltrate photo-patternable polyacrylate networks with ZnO, thus creating a hybrid organic-inorganic material with new properties. It could be shown that it’s not only the density of polymer reactive groups that determines ZnO growth, but also process parameters and, in the case of ALI, the flexibility and free volume of the infiltrated polymer network.
These findings contribute to the fundamental understanding of atomic layer processes on and in polymers, highlighting the importance of polymer chemistry and microstructure in determining ZnO growth.
Lukas Reicht
Disordered polymers are typically characterized by a very low thermal conductivity on the order of 0.1 W/mK. In contrast, recent experiments showed that, when polymers are highly aligned (crystalline), polyethylene (PE) can reach a thermal conductivity of ~104 W/mK, which would be interesting for applications. Newly developed machine-learned potentials (MLPs) promise to be an efficient and accurate tool for calculating these thermal conductivities. Applying a new methodology, however, requires a thorough benchmarking. We performed such a benchmarking for moment tensor potentials (MTPs), which are a flavour of machine-learned potential, by calculating various phonon related properties of polyethylene (PE), polythiophene (PT), and poly(3-hexyl-thiophene) (P3HT). Based on the calculated phonon band-structures, elastic constants, thermal expansion coefficients, and thermal conductivities, we conclude that the accuracy of MTPs can be substantially increased by a deliberate choice of training data adapted to the intended use case. Having established the accuracy of the trained MTPs, they are then used to calculate thermal conductivities via the Boltzmann transport equations (i.e., in reciprocal space), and by molecular dynamics approaches (i.e., in real space). This yields complementary atomistic insights into the factors determining heat transport in polymers.
Alexander Zesar
Trapped ions are among the most researched and advanced quantum computing (QC) hardware platforms. Currently used free-space optics for ion addressing will block upscaling due to beam pointing errors and spatial restrictions. Therefore, future QC architectures with trapped ions require integrated waveguiding and focusing for scalable and stable placement of laser beams in microfabricated ion-trap chips.
This talk gives a concise overview of photonics and optics integration schemes developed at Infineon. We will discuss some of the challenges that come with femtosecond-laser-written waveguides as well as slab waveguides in conjunction with focusing grating couplers, including waveguide loss sources, fiber-to-chip coupling and integration density. The talk concludes with an outlook on scalable ion-trap chips with integrated photonics as a necessary condition for useful trapped-ion quantum computing.
Josef Simbrunner: Correlation between 2- and 3-dimensional crystallographic lattices for epitaxial analysis
Raphael Hauer: Continuous real-time characterization of ultra-low concentrated micropaticles with single-particle accuracy using an OF2i setup
Dominik Brandstetter: Band structure formation in metal-organic nanostructures