Nanna Bach Moeller
Previous studies have found that high-energy radiation like cosmic rays and stellar energetic particles, can induce the initial nucleation of cloud particles from molecular clusters in the atmosphere, but the effect on larger existing particles is still poorly understood.
This study explores the question “How is the aggregation of mineral cloud particles affected by high-energy radiation and humidity?”. I will present experiments conducted in an atmosphere chamber on the charging and aggregation of 50nm SiO2 particles under varying degrees of gamma radiation and relative humidity.
We observe an aggregation of the SiO2 particles to form larger clusters, and that this aggregation is inhibited by irradiation with gamma radiation. We find that gamma radiation shifts the charging of the particles to become more negative, by increasing the charging state of negatively charged particles. The effect of gamma radiation on the aggregation and charge of the particles is present both at lower (~20%) and higher (~60%) relative humidity. We suggest that the overall effect of gamma radiation could favor the formation of a high number of small particles over a lower number of larger particles.
In recent years exoplanet research has focused on how we can interpret atmosphere observations through models, and here cloud formation has proven to be a challenge. Clouds are known to play a role in both the energy balance and chemistry of atmospheres, as well as directly affecting the spectrum observed from a planet. Exoplanet clouds are believed to be very chemically heterogeneous and SiO2 is one of the species that easily condense, making SiO2 relevant both as a nucleation seed on Earth-like planets and as a cloud species on Exoplanets. Since cloud formation has been found to be affected not only by the atmospheric properties, but also by high-energy radiation from outside the atmosphere it indicates that the host star and interstellar environment of an exoplanet might affect its clouds.
Helena Lecoq Molinos
Observations of numerous gaseous exoplanets have revealed the presence of clouds in their atmospheres, but how exactly these clouds form is not fully understood. In this work, we study the first steps of cloud formation in gaseous atmospheres using quantum chemistry calculations of vanadium oxide clusters (VxOy)n (with x=1-2, y=1-5, n=1-10).
The formation of clouds is initiated by different nucleation processes. Nucleation takes place when gas phase molecules cluster together to form nanometer-sized particles (i. e. nanoclusters), which can further coagulate into macroscopic dust grains that provide a surface for the cloud materials to condense on. The process is highly dependent on the characteristics of the clusters such as their potential energies, geometries and spectral properties, all of which are not well known. We apply a bottom-up approach to obtain the geometries and thermochemical energies of global minima candidate structures for the different oxidation states. Each structure has been calculated applying Density Functional Theory at the B3LYP/cc-pVTZ level of theory.
We present thermochemical results for VO and V2O5 that are in accordance with the experimental energies listed in the JANAF-NIST tables. Further, we provide updated values for VO2 as well as results for larger structures that are not currently available in the literature. We use a chemical equilibrium code to explore the astrophysical environments for which vanadium oxide nucleation will be important, with a focus on exoplanet atmospheres. For temperatures less than 1500 K, we find that vanadium oxide clusters are the most stable vanadium bearing species at a large range of atmospheric pressures.
Thorsten Balduin
Lightning can have a profound impact on the chemistry of planetary atmospheres. In a similar manner, as protoplanetary disks are the foundation of planet formation, the emergence of lightning in protoplanetary disks can substantially alter their chemistry.
We aim to study under which conditions lightning could emerge within protoplanetary disks.
We employed the ProDiMo code to make 2D thermo-chemical models of protoplanetary disks. We included a new way of how the code handles dust grains, which allows the consideration of dust grains of different sizes. We investigated the chemical composition, dust charging behavior, and charge balance of these models to determine which regions could be most sufficient for lightning.
We identify six regions within the disks where the charge balance is dominated by different radiation processes and find that the emergence of lightning is most probable in the lower and warmer regions of the midplane. This is due to the low electron abundance in these regions and dust grains being the most abundant negative charge carriers. We find that NH4+ is the most abundant positive charge carrier in those regions at the same abundances as the dust grains. We developed a method of inducing electric fields via turbulence within this mix of dust grains and NH4+. The electric fields generated with this mechanism are however several orders of magnitude weaker than required to overcome the critical electric field.
Alexandra Serebrennikova
Transport of volatile organic compounds (VOCs) through porous media with active surfaces occurs in many important applications, such as in cellulose-based materials for packaging. In general, it is a complex process that combines diffusion with sorption at any time. Models for predicting the transport of volatile organic compound (VOC) in paper must consider complex interactions like diffusion, adsorption, desorption, and chemical reactions. Selecting a suitable theoretical model that accurately predicts transport for different polarities is challenging and requires thorough validation against experimental data. Prior to the start of the current research project, the data needed to use and validate the mathematical models proposed in literature were scarce and had not been systematically compiled. Therefore, we combined specifically chosen experiments that deliver the data suitable for validation of such mathematical models. We employed physics-informed neural networks (PINNs) to evaluate five kinetic models. Using experimentally obtained concentration profiles and the set of partial differential equations (PDEs) associated to each model, PINNs allowed to (i) predict the concentration of preselected model compounds and (ii) to determine model-specific material parameters. Our PINN-based evaluation identified two accurate models that comply with the experimental data: A pseudo first-order model and a second-order reversible sorption model, that considers polarity-driven differences in sorption times. We further extended the applicability of the suitable model(s) for the opposite case in which VOCs desorb from paper. The latter case is a real-life scenario in food packaging industry where the accumulation of potential contaminants may restrict shelf times of the products.
Thomas Jauk
The integration of spin degrees of freedom into optoelectronic circuits has become one of the central obstacles for the future of information technology. Even though the manipulation of spins using ultrafast light waveforms is technologically appealing, it is limited by the feeble coupling between light and the solid’s spin system. Since the discovery of ultrafast magnetization dynamics by Baurepaire et al. [1] a wealth of studies has been carried out to shed light on the microscopic origin. While a variety of experiments focused on quenching the magnetic order at ultrafast speeds, few investigations dedicated themselves to the exploration how to photo-generate or enhance ferromagnetism. Impeded by rapid carrier thermalization and spin-flip scattering, most ferromagnetic systems fail to establish a long-lasting increase in magnetic moment upon light-induced population transfer. We found a formidable candidate in the ferromagnet metal-oxide interface, as it suppresses these counteracting mechanisms and allows for other subtle processes to dictate the evolution of the magnetic moment. By employing magnetic circular dichroism in a photoemission experiment, we synchronously track the evolution of the energy-dependent magnetic moment and occupation upon photoexcitation with a near-infrared light burst. Strikingly, the charge redistribution creates a long-term stable enhanced magnetic state that even survives the de-excitation of the carriers. This observation could lay the foundation for the investigation of novel magnetic systems with methods capable of capturing transient phenomena on a multidimensional scale.
[1] Beaurepaire et al. Ultrafast Spin Dynamics in Ferromagnetic Nickel. Phys. Rev. Lett. 76, 4250–4253 (1996).
Kazma Komatsu
For the realization of ultrafast nanophotonic circuits, the complete control of surface plasmon polaritons (SPPs) in space and time is crucial. Here we show that short grating couplers in gold plasmonic waveguides support few-cycle SPPs, while maintaining a good light-to-plasmon coupling efficiency. Using photoelectron microscopy with subwavelength spatial and temporal resolution, we characterize the temporal evolution of co- and counter-propagating SPPs launched from the grating couplers into rhombic gold structures. By comparing their propagation, we track the evolution of the laser-plasmon phase, which is controllable via the coupling conditions. Based on these findings, we propose a scheme for plasmonic waveform synthesis that will allow obtaining electromagnetic field confinement in the smallest possible space-time volumes.
Markus Markl
Controlled thermonuclear fusion can potentially provide clean and sustainable energy that may serve as the backbone of our future energy mix. The furthest developed magnetic confinement fusion concept, the tokamak, is haunted by edge localized mode instabilities when operated in the so-called high confinement mode. A promising method of suppressing these instabilities is to apply magnetic perturbations to the plasma. However, despite being experimentally verified, this method is not fully understood yet, thus its reliable extrapolation to future devices like ITER is uncertain. In this talk, a kinetic model and its advancement are presented that are used to study the plasma response to magnetic perturbations. Within the model, a criterion was developed that indicates the occurrence of a bifurcation of the magnetic topology which is commonly assumed to be responsible for the suppression of the edge localized modes. By applying it to experimental data, the model is used to study the process behind bifurcation and edge localized mode suppression.
Bernhard Ramsauer
Scanning probe microscopy gives us the ability to precisely control the position, orientation and structure of single molecules and unlocks the possibility to nanofabricate artificial structures with enhanced properties. However, the interaction processes at the nanoscale are stochastic processes, and because their effect on a manipulation is often unintuitive and hard to predict, inducing controlled movements is not trivial at all.
In this talk we present a road to autonomous nanofabrication of artificial structures with a machine learning algorithm controlling the tip of a scanning tunneling microscope. This requires the machine learning algorithm to identify the optimal manipulation parameters (i.e., the bias voltage, height, and lateral position of the STM tip relative to the molecule) for any arbitrary (unknown) moiety. However, leaving all the manipulation parameters open for investigation requires to exclude parameters that pick-up or destroy the molecules, as this would make it impossible to learn in an autonomous fashion. As a consequence, there are too many possible manipulation parameters to conduct in an experimental approach. However, probing this large parameter space can be circumvented by finding the underlying model and find a clever way to infer prior knowledge to similar manipulation parameters (e.g.: to infer knowledge at the same bias voltage to adjacent tip positions or at the same tip position but at various bias voltages).
These combined approaches find the optimal manipulation parameters in a single day. Thus, allowing us to autonomously control initially unknown moieties with high sub-nanometer precision that set the foundation to autonomously nanofabrication of artificial nanostructures one-by-one.
N. Šimić
Lithium Iron Phosphate (LiFePO4) is a technologically highly relevant and widely used cathode material for rechargeable battery systems, due to its stability, long cycle-life and high charge and discharge efficiency. Although previous work investigated crystal phases of partially delithiated battery cells with TEM based techniques, such as Selected Area Electron Diffraction (SAED) and Bright-Field TEM [1], as well as Precession Electron Diffraction [2], the underlying charging and discharging mechanisms are still not well understood at the atomic level.
Our work shows that we are able to determine the local crystal phase and degree of delithiation on electrochemically delithiated LiFePO4 samples. Identification and analysis of LixFePO4 crystals was not only performed macroscopically, but also at an atomically resolved level.
Phase transition boundaries between lithiated and delithiated phases are depicted with High-Resolution integrated Differential Phase Contrast (iDPC) imaging, a technique with high sensitivity to light elements which is particularly well suited for beam sensitive materials like LiFePO4. Partially delithiated phases have also been observed among fully delithiated and fully lithiated phases. We also present a method to determine the quantitative delithiation grade on a nanometer scale using High-Resolution STEM-FFT analysis. These evaluations are further supported by SAED as well as extensive multislice STEM simulations.
[1] G. Chen; Electrochem. Solid-State Lett., 2006, 9, 295-298.
[2] G. Brunetti; Chemistry of Materials, 2011, 23, 4515-4524.
Thomas Planko
Direct costs due to corrosion worldwide amount 3% - 5% of the GDP (gross domestic product) [1][2]. Secondary cost like production losses or efficiency loss can be much higher [3]. Apart from these enormous costs and the economic consequences, in many areas, corrosion represents a very high safety risk (e.g. aircraft and pipelines). MIC is responsible for 20% of all corrosion damage [4]. In this context, there is great interest in understanding MIC especially, since it has been shown that some microbes slow down the rate of corrosion [5], while others speed it up [6]. The fact that the composition of bacterial cultures and biofilms can vary greatly [7], makes any newly discovered composition an interesting topic to study. CIC occurs when chloride ions penetrate steel surfaces in concrete, causing rust formation and structural damage. ASR, a reaction between alkalis in cement and silicates in aggregate materials, can cause expansive cracking and damage in concrete structures.
All of these forms of corrosion have been studied using correlative microscopy and will be discussed in detail in the lecture. Based on the MIC examinations, I would now like to describe my work in more detail:
With a length of 32.9 km, the Koralmtunnel is the longest railway tunnel in Austria and the seventh longest in the world. During the construction work, I was allowed to examine the effects of groundwater on different types of steel about 10km in the tunnel at a depth of about 800m underground. What was special about this was that, during investigations into the sintering of the tunnel drainage, a bacterial strain was found, whose main mass consists of iron-oxidizing gallionella ferruginea, sulfur-oxidizing thiothrix and methanotrophic bacteria. These bacteria are known to be associated with MIC. This bacterial strain causes MIC and as a result, a biofilm is formed.
To study the effects of this strain, various steel samples, with different composition were placed in the experimental setup. Both a macroscopic and microscopy analysis of the samples is performed. On the macroscopic side, the average corrosion rates and the pitting corrosion are determined. On the microscopic side a novel technique that combine Raman imaging with scanning electron microscopy (SEM) and energy dispersive X-Ray spectroscopy (EDX) is applied. The correlative Raman microscopy complements the established SEM-EDX combination with information about chemical bonds and oxidation states.
What is particularly interesting about the results is that the corrosion rate slowed down as a result of MIC, but the pitting corrosion in these samples was more pronounced.
Correlative SEM, EDX, and Raman microscopy offer a powerful approach for investigating the mechanisms underlying corrosive damage in various materials, paving the way for more effective corrosion prevention and mitigation strategies.
[1] Hays, George F. "Now is the Time." World Corrosion Organization (2010).
[2] Biezma, M. V., and J. R. San Cristobal. "Methodology to study cost of corrosion." Corrosion engineering, science and technology 40.4 (2005): 344-352.
[3] Wendler-Kalsch, Elsbeth, and Hubert Gräfen. Korrosionsschadenkunde. Springer-Verlag, 2012.
[4] Javaherdashti, Reza. "A review of some characteristics of MIC caused by sulfate-reducing bacteria: past, present and future." Anti-corrosion methods and materials 46.3 (1999): 173-180.
[5] Dubiel, M., et al. "Microbial iron respiration can protect steel from corrosion." Appl. Environ. Microbiol. 68.3 (2002): 1440-1445.
[6] Javed, M. A., et al. "Effect of sulphate-reducing bacteria on the microbiologically influenced corrosion of ten different metals using constant test conditions." International Biodeterioration & Biodegradation 125 (2017): 73-85.
[7] Beech, Iwona B., and Jan Sunner. "Biocorrosion: towards understanding interactions between biofilms and metals." Current opinion in Biotechnology 15.3 (2004): 181-186.
Sunny Laddha: Optical Vector Magnetometer Based on the Hanle Effect
Gabriel Hernandez: Anti-icing polymeric coatings
Jonathan Schatzlmayr: Simulating Colissions with GORILLA
Beatrix Campos Estrada: On the likely magnesium-iron silicate dusty tails of catastrophically evaporating exoplanets"
Anton Nrecaj: Materials Characterization of Liquid, Soft and Solid Materials Over Large Travel Ranges: Development of Different Measurement Concepts
Christoph Wachter: In search of organic improvements to ab initio thermodynamics
Robbin Stentjes: True minimum energy configurations of 2D stacked MOFs and COFs
Fabian Gasser: Intensity Corrections in Grazing Incidence X-ray Diffraction
Sanjay John: Isolation of Enantiopure Phase in Binaphthyl Thin Films
Tommaso Mazzocchi: Correlated Mott insulators in a strong electric field: The effects of phonon renormalization
Alexander Zesar: Integrated Waveguides in Trapped Ion Quantum Computing Chip
Alexander Sagar Grossek: Attosecond Light Microscopy
Henrik Siboni: Mechanical characterization of pharmaceutical nanoparticles
Leah Holzer: STREAM: STorylines of Danube stREAMflow. Assessing future streamflow for different atmospheric circulation responses to greenhouse gas forcing
Narges Taghizadeh Rahaghi: Crustal structure solution of Cu2(BDC)2 thin film