Hybrid Attachment Systems as an End-effector for Aerial Drones
While aerial drones provide humans with a powerful tool to get access to hard-to-reach environments, end-effectors, or robotic grippers, allow the drones to have a dynamic interaction with their surrounding environments by touching, sensing, and grasping an object. In this project, we aim at developing a hybrid soft robotic gripper that can adhere onto a wide range of real-world surfaces and geometries, while simultaneously achieving high adhesion strength with minimal necessary peripherals. We also aim at a system-level integration of the hybrid soft gripper with a UAV to demonstrate grasping of various objects and real-world surfaces.
3D culturing of human skin T cells for an in vitro Lichen disease model
At Empa (St. Gallen), we have been working on different ECM-mimetic hydrogels for 3D cell culturing and in vitro skin models. In collaboration with the Department of Dermatology at the University Hospital of Zürich (Barbara Meier-Schiesser, Dr. med. Dr. sc. nat.), this project aims at 3D culturing of patient T cells (isolated from human skins) with ECM-mimetic hydrogels, and ultimately for the development of patient-specific treatments with reduced side effects.
Intern: Modelling and parameterization of waste incineration plant including carbon capture and storage (paid position)
We are looking for an intern to strengthen our energy hub modelling team on modelling and parameteriza-tion of waste incineration plants including carbon capture and storage.
Software Engineer for urban energy system modelling (20% or more, paid position)
We are looking for a software engineer to develop and maintain an MILP based energy system optimization library in an interdisciplinary team.
Thermomechanical Simulation for Distortion and Residual Stress Prediction in SLM Parts: Sensitivity Analysis
Excessive distortion and the existence of high levels of residual stress are of the major concern for AM products. The sensitivity of predicted residual stress to the type of material constitutive model will be evaluated.
Application of machine learning in multiscale thermal modelling of laser powder-bed fusion processes
Finite element (FE) thermal simulation of additive manufacturing processes is computationally very expensive due to the need for employment of fine time and space discretization levels. This student project aims to employ neural networks as a general function approximator to develop a metamodel that would generate the outcome of FE simulations based on given inputs parameters.
Exploration of novel brazing procedures for high-performance steels
Brazing is a typical method for fabrication of high-strength joints between metallic and/or ceramic components. Examples are the joining of turbine parts made from Ni-base alloys, or of tools made from various steels. To reduce the melting temperature of the brazing alloy, elements like B, Si, or P, are often added as melting-point depressants. However, these additives can have severe effects on the performance of the components to be joined. One example is the decrease of the corrosion resistance of a steel joint due to reaction of Cr from the base material with the melting-point depressant (cf. Figure). One way to improve the corrosion resistance is to prolong the brazing step or increase the brazing temperature to achieve a more homogeneous distribution of the melting point depressant. However, this approach is limited, because the joining procedure must also be compatible with the heat treatment recommended for the joining components to avoid deterioration of the base-material properties (hardness, fracture toughness, …). Scope of the thesis In this project, a novel approach for vacuum brazing of a hot-working steel with a modified brazing alloy will be explored. The project will involve (i) preparation of the brazing components, and execution of the brazing process, (ii) microstructural analysis of the brazed joints by OM, SEM, and XRD, and (iii) mechanical testing as well as corrosion testing. We are looking for motivated students in the field of Materials Science or Mechanical Engineering with a keen interest in carrying out systematic experiments and materials analysis. Duration: 6 months (master thesis).
Surface-state analysis for Ag sinter-bonding of semiconductors
Sinter-bonding utilises the high sintering activity of metallic nano- and microparticles to create joints between two substrates at comparatively low homologous temperatures (e.g. for Ag-NPs at about 200 °C - 300 °C, i.e. well below the melting point of bulk Ag at 961.8 °C). In contrast to classical soldering or brazing with a liquid filler alloy, the resulting sinter-bonds can be utilised up to or even above the bonding temperature, and show superior thermal and electric conductivity. Therefore, Ag sinter-bonding has gained widespread application in recent years, e.g. for die attach or heat-sink bonding in electronics. To facilitate bond formation, the joining surfaces are generally coated with a thin-film metallisation, e.g. Si/TiW/Ni/Au. Recently, Ag sinter-bonding of Si-substrates and other semiconductors or ceramics without use of a metallisation layer has been reported [1,2]. It has been show that the actual bond formation is occurring between Ag and the native oxide layer of Si. However, it is an open question how this bond formation between metal and oxide is realized on an atomic level, and what local chemical conditions are required to achieve bonding. Empa Lab 202 has recently installed a unique experimental system combing lab-based HAXPES, sputter-deposition, a glovebox, and an environmental testing chamber. With this system, sample preparation, thermal treatments, and sample analysis can be performed under controlled atmospheres. Scope of the thesis In this project, an in-depth chemical state analysis of the sinter-bonding process between Ag and Si/SiO2 by XPS will be performed. The project will involve (i) preparation and characterization of bonding components (substrates, Ag-pastes), (ii) execution of heat treatments and bonding experiments in different atmospheres, (iii) HAXPES/XPS measurements and data evaluation. We are looking for motivated students in the field of Materials Science/Physics/Chemistry with a keen interest in materials analysis with advanced analysis methods. Duration: 6 months (master thesis). [1] T. Matsuda, K. Inami, K. Motoyama, T. Sano and A. Hirose, “Silver Oxide Decomposition Mediated Direct Bonding of Silicon-based Materials,” Scientific Reports, vol. 8, 2018. [2] Z. Zhang, C. Chen, A. Suetake, M.-C. Hsieh, A. Iwaki, K. Suganuma, "Pressureless and low-temperature sinter-joining on bare Si, SiC and GaN by a Ag flake paste," Scripta Materialia, vol. 198, 2021.
Use of demand-side flexibility to alleviate congestions in distribution networks
In recent years, the penetration of renewable energy resources in distribution grids has been steadily increasing, raising new issues such as voltage violations or line congestions. Due to their large inertia, individual buildings may regulate their heating system to help distribution system operators alleviating these congestions. In our previous work, we designed an energy management system that self-exports a flexibility envelope to a system operator for system-level dispatch [1]. The envelope contains the maximal and minimum energy that the household can consume over an horizon of a day. Now, we would like to employ this information to reduce congestions in distribution grids. [1] Gasser, J., et al., Predictive energy management of residential buildings while self reporting flexibility envelope. (2021), Applied Energy, 288, p.116653.
Flooding Impacts on Energy System Planning in Accra due to Climate Change
This project presents the opportunity to collaborate with climate change and power system scientists in Ghana in order to assess the outage impacts of increased flooding events due to climate change in the city of Accra. You will have the opportunity to design outage scenarios due to increased flooding events for Accra in order to model impacts on long-term energy system planning and identify resilience solutions for the city using an optimization model.
Rising Temperature Impacts on Cooling Demand and Energy System Planning in Accra due to Climate Change
This project presents the opportunity to collaborate with climate change and power system scientists in Ghana in order to assess the impacts of rising temperature and heatwave events due to climate change on cooling demand and energy planning for the city of Accra. You will have the opportunity to design cooling demand scenarios for Accra in order to model impacts on long-term energy system planning and identify resilience solutions for the city using an optimization model.
Robot-Assisted Building Energy Management
The building sector is responsible for more than one third of the energy consumption and CO2-emissions worldwide. In industrialized countries around half of this energy is used for heating, ventilation and air conditioning (HVAC). Improving the energy efficiency of buildings has therefore a significant impact on mitigation climate change. However, renovating the building envelope or HVAC system of already existing buildings is relatively expensive and causes slow diffusion. In contrast, integration or upgrading of heating or cooling control systems and optimizing its operation can be done at comparatively low costs, resulting in fast impact. While Model Predictive Control (MPC) is considered the gold standard for climate control in buildings, a crucial part of MPC is the identification of an accurate model of the building. Here, first-principle based models still outperform purely data-driven models such as the ones presented in. However, first-principle based building modelling is associated with many tedious tasks such as mapping of the floor plan and inventory, or identification of several system parameters (e.g. thermal resistance of walls). If an experienced engineer has to perform these tasks for each building individually, MPC might not be economically feasible.
Mapping near-surface NO2 concentrations in urban areas by combining in situ and remote sens-ing observations with city-scale transport simulations
NO2 is a primary air pollutant with a high spatial and temporal variability. Therefore, high-resolution maps are critical for linking NO2 exposure and health impact. In the Munich NO2 imaging campaign, NO2 was measured with airborne and ground-based in-situ and remote sensing instruments. In this project, you will analyse the MuNIC dataset and develop an algorithm to convert APEX NO2 maps to maps of near-surface NO2 concentrations.
A model study on monitoring CO2 emissions of cities from high-altitude pseudo satellites
High altitude pseudo satellites are self-sustaining, unmanned air vehicles that fly in the stratosphere (~20 km above the ground) and can be kept in a stationary position (e.g., above a city) for several weeks to months. In this project, you will perform an observing system simulation experiment (OSSE) to answer the question how accurately a HAPS-based imaging spectrometer would need to measure CO2 to be able quantify the CO2 emissions of a city.
Impact of uncertainties on the flexibility quantification of HVAC systems in buildings
In recent years, the penetration of renewable energy resources in distribution grids has been steadily increasing, raising new issues such as voltage violations or line congestions. Due to their large inertia, individual buildings may regulate their heating system to help distribution system operators alleviating these congestion. In our previous work, we designed an energy management system that self-exports a flexibility envelope to a system operator for system-level dispatch [1]. The envelope contains the maximal and minimal energy that the household can consume over a day. However, the impact of uncertainties on flexibility envelopes has not yet been investigated. As many uncertain parameters come into play, this project aims at assessing the accuracy of our previous quantification method. [1] Gasser, J., Cai, H., Karagiannopoulos, S., Heer, P. and Hug, G., 2021. Predictive energy management of residential buildings while self-reporting flexibility envelope. Applied Energy, 288, p.116653.
Impact of uncertain information on the detection of future congestions in distribution networks
In recent years, the penetration of renewable energy resources in distribution grids has been steadily increasing, raising new issues such as voltage violations or line congestion. Due to their large inertia, individual buildings may regulate their heating system to help distribution system operators alleviating these congestion. Previous works have proposed methods to anticipate future congestions, given forecasts and uncertainties [1,2]. In this project, we aim at assessing the impact of the spatial-temporal uncertainties on the congestion detection. In other words, how the grid placement of an uncertain consumer/producer or the knowledge on its future consumption/production may impact the congestion detection.
Gate-defined quantum confinement in graphene superlattice
This project aims to fabricate gate-defined quantum dots on graphene superlattice and study quantum confinement physics in strongly correlated two-dimensional electron system.
Biodegradable Antennas for environmental Sensing
Development of biodegradable antennas for an RFID/NFC interface for environmental monitoring applications
M.Sc. thesis: Exploring the impact of hexagonal boron nitride (nanomedicines) on bacterial communication (quorum sensing) and its consequences on pathogenesis
In quorum sensing, bacteria assess their population density by detecting the concentration of chemical signal molecules called autoinducers (AI), which are produced by the bacteria as a function of cell density. The inter-species communication within and between many bacteria species is driven by AI-2, a furanosylborate diester. Supplementing boron can trigger AI-2 biosynthesis in bacteria thus enhancing AI-2 mediated quorum sensing processes. Streptococcus pneumoniae (Spn) uses the luxS mediated AI-2 quorum sensing circuit for host-cell colonization and pathogenesis. Two-dimensional (2D) hexagonal boron nitride (hBN, a/k white graphene) is a close ally of graphene and has numerous potential applications in biomedical sectors such as drug and gene delivery, hydrogel composites, and anticancer therapy based on Boron-Neutron Capture Therapy (BNCT). BNCT is the next generation of particle therapy focused on boron elements and used for the treatment of different cancer types. We hypothesize that 2D-hBN exposure can upregulate the synthesis and release of AI-2, which could enhance quorum communication among bacteria, and eventually lead to increased virulence and pathogenesis of Spn in the host.
Architectured Desing of Nanomaterials for Robust Photonic Devices: Fundamentals and Nanofabrication
This MSc thesis project, will utilise advance nanofabrication and a dedicated reconfigurable optical microscope integrated with lasers and spectrometers to detect optical signal from nanoscale objects. With E-beam pattering and direct laser writing the student will fabricate 2D and 3D nanostructures on top of flexible membranes to explore their advanced mechanical and optical properties. Further, the student will be equipped with skills in optical elements automation and data acquisition.
Flexible graphene-based THz detectors
We will combine materials such as graphene with THz transparent polymers to develop, fabricate and characterize THz detectors based on flexible polymer and graphene with state-of-the-art equipment.
Simulations, fabrication, and characterization of THz low pass filters
We will develop low-pass filters for the THz regime using cleanroom fabrication methods. The devices will be characterized in the THz regime using a THz time-domain spectrometer.
THz nanoscopy twisted graphene on flexible polymers
We will use THz nanoimaging techniques and THz spectroscopy to investigate the properties of novel materials, such as twisted graphene, in the THz regime.
Digital twins of building energy systems
The Urban Energy System Laboratory at Empa has openings for semester projects in real-time simulation of building energy systems using digital twins.

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