EmpaAcronym | EMPA | Homepage | http://www.empa.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Current organization | Empa | Child organizations | | Memberships | |
Open OpportunitiesStructural color is a fascinating method employed in nature to achieve vibrant hues. Examples abound, from Iridescent opals to the delicate hues of butterfly wings, and the shimmering scales of beetles1 (Figure 1 a-c). Unlike conventional pigments, structurally colored materials boost resilience against photobleaching and can be easily designed to circumvent environmental and chemical hazards. This characteristic renders them an attractive sustainable alternative for various photonic applications.2,3 Renowned for their ultralow thermal conductivity and open pore structure, Aerogels find widespread use scenarios in thermal insulation, catalysis, environmental remediation, and optics.4 Among these applications, currently, thermal insulation stands out prominently, and an aerogel with intrinsic structural color holds the promise for sustainable and smart coloring endeavors. - Composite Materials, Control Engineering
- Master Thesis
| We are looking for a motivated Master student to join Empa St. Gallen for this master thesis project. The candidate will be part of an exciting and collaborative project between the Particles-Biology Interactions Lab, the Biointerfaces Lab as well as the Biomimetic Membranes and Textiles Lab at Empa. - Biomedical Engineering
- Master Thesis
| We are looking for a highly motivated candidate with a strong experimental background in Solid State Physics, Surface Science or Quantum Nanoscience who wants to pursue cutting-edge research. In this project, you will synthesize and characterize strongly correlated quantum many-body spin systems using methods based on scanning probe microscopy. You will study local excitations at the single spin site level in bottom-up fabricated nanographene chains using a low-temperature scanning tunneling microscope. In combination with multiconfigurational simulations, such experiments will determine the energetics and dynamics of electronic and spin excitations in these strongly correlated quantum many-body systems. Obtaining precise and flexible control over spin sites and interactions will open ways toward the operation of carbon-based quantum spin devices.
- Condensed Matter Physics-Structural Properties
- PhD Placement
| In the era of climate change and growing global energy demand, smart energy systems have become pivotal in ensuring sustainable, efficient, and reliable energy delivery. These systems, characterized by the integration of advanced metering infrastructure, renewable energy sources, and innovative demand response technologies, form the backbone of modern energy strategies aimed at reducing carbon footprints and enhancing energy security. The Swiss Confederation, cognizant of these imperatives, advocates for a robust transition towards intelligent energy networks, setting the ambitious goal of a net-zero carbon economy by 2050. As we push the boundaries of energy system innovation, the imperative of resilience cannot be overstated. Resilience in this context refers to the smart energy system's capacity to anticipate, withstand, and recover from various forms of disruption like environmental phenomena, technical failures, or human-induced events. This project acknowledges the complexity and interdependence of the smart energy ecosystem, encompassing residential buildings equipped with the latest in energy-efficient technologies, user interfaces that allow for dynamic interaction with the energy grid, and decentralized renewable energy generation units that contribute to a sustainable energy mix.
Electric vehicles (EVs), Heating, Ventilation, and Air Conditioning (HVAC) systems, and domestic appliances represent significant loads within the residential sector that can be managed to foster resilience. The bi-directional flow of energy in smart grids, facilitated by smart meters, allows for sophisticated energy management strategies that not only respond to system demands but also to user behaviors and preferences. The resilience of such an interconnected system hinges on its ability to maintain stability and operation despite unpredictable renewable energy generation patterns, potential cyber-physical threats, fluctuations in the energy market due to instability in the neighboring countries, and changes in user behavior. The Swiss energy paradigm provides an exemplary context for studying and enhancing the resilience of smart energy systems. By developing a conceptual framework for resilience assessment tailored to this context, this thesis aims to contribute to the body of knowledge that will empower stakeholders to design, implement, and maintain robust energy systems. - Building, Conceptual Modelling, Systems Theory and Control
- Master Thesis, Semester Project
| Switzerland is committed to transitioning to a renewable energy system. The Swiss government has set a target of achieving net-zero carbon emissions by 2050. This will require a significant increase in the use of renewable energy sources. The Swiss power grid is also vulnerable to imbalances be-tween supply and demand. Demand flexibility can help to mitigate this risk and ensure the reliable operation of the power grid. Demand flexibility is the ability to shift or reduce energy use in response to changes in sup-ply or price. This is becoming increasingly important as the power grid transitions to renewable energy sources, such as solar and wind power, which are intermittent and less predictable. Demand flexibility can help to balance the grid and reduce the need for expensive and polluting backup power plants. Non-Intrusive Load Monitoring (NILM) and customer segmentation modeling are powerful tools that can be used to develop demand flexibility programs. NILM can be used to identify high-energy-consuming appliances and to track their energy usage over time. Customer segmentation modeling can be used to identify different groups of customers based on their energy consumption patterns. This information can then be used to develop targeted demand flexibility programs that are more likely to be effective for each group of customers. - Building not elsewhere classified, Building Science and Techniques, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Signal Processing, Simulation and Modelling
- Master Thesis
| The aim is to extend an existing linear self-learning algorithm that optimizes the heating curve depending on building physics and external parameters in terms of indoor comfort and energy efficiency. For this purpose, we are working together with one of our industrial partners in the building technology sector in order to be able to test executable prototypes under real conditions in their facilities in addition to the theoretical simulations.
- Control Engineering, Optimisation, Simulation and Modelling, Systems Theory and Control
- Bachelor Thesis, Master Thesis, Semester Project
| Wound infections present a significant challenge in healthcare, and traditional treatments involving antibiotics can lead to the emergence of antibiotic-resistant bacteria. Probiotics (i.e. the "good bacteria") have been studied widely for their potential antimicrobial effects and use in wound treatment as an alternative to antibi-otics. They have been reported to enhance wound healing, produce antimicrobial substances, disrupt biofilm, and restore the microbial balance in wounds. In this project, we aim to combine the benefits of probiotics and hydrogels to form a so-called "living hydrogel": i.e. a hydrogel with organisms inside. The living hydrogel can not only fulfill the function of a normal wound patch but also deliver the therapeutic factors secreted by the encapsulated probiotics to fight against pathogen infection and also promote wound healing. - Biomedical Engineering, Complementary/alternative Medicine, Interdisciplinary Engineering, Macromolecular Chemistry, Materials Engineering
- Internship, Master Thesis
| Underwater gliders rely on their wings to convert vertical motion, induced by variable buoyancy, into forward motion. No active propulsion, such as propellers, is required. Wing efficiency, or lift-to-drag ratio, is a key parameter in enhancing the vehicle’s performance. In order to reduce the mechanical complexity, underwater gliders have no control surfaces, but at the cost of diminished maneuverability. Wings capable of changing shape would be able to adapt to encountered gliding conditions. Therefore, their efficiency would be optimized, and the operational range of the underwater vehicle extended [4]. Over the last years, actuators based on soft elastomers have contributed to the field of robotics, providing greater adaptability, improving collision resilience, and enabling shape-morphing. The Laboratory of Sustainability Robotics and its research partners designed a soft wing for integration into an underwater glider. The morphing ability and the efficiency of this wing have been characterized though experiments in the water channel testing facility at Empa and are discussed in a recent journal publication [1]. Currently, the soft wing awaits completion of a Fluid Structure Interaction (FSI) simulation to provide better insights on its deformation and efficiency. - Aerospace Engineering, Mechanical and Industrial Engineering
- Master Thesis
| Buildings appear as significant energy consumers, especially due to the management of heating, ventilation, and air-conditioning (HVAC). Each building has unique characteristics such as varied geometries, floor layouts, construction properties, age, climatic regions, orientation, and service systems. Better control of indoor temperature in buildings seems to be a means of energy savings. Traditional approaches rely on building modeling for this purpose.
While physics-based models may be precise and aligned with expected physical behaviors, their complex design can limit their application and scalability.
An alternative modeling approach based solely on sensor data (temperature, solar irradiance, etc.) aims to be more flexible and is generating increasing interest. However, these approaches require diverse data in sufficient quantity to train the model parameters and might demand more computing power than what buildings can accommodate.
The complexity of models, their instability, or the lack of data poses obstacles when attempting to model a new building.
The primary goal of this project is to leverage the flexibility of data-driven methods to model the thermal behavior of buildings, emphasizing the development of a transferable model.
This approach aims to streamline the modeling process by enabling the initial learning of a model for one building and its subsequent adaptation to other buildings. - Artificial Intelligence and Signal and Image Processing, Engineering and Technology, Systems Theory and Control
- Master Thesis, Semester Project
| 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. - Electrical Engineering, Intelligent Robotics, Mechanical Engineering, Simulation and Modelling, Systems Theory and Control
- Master Thesis
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