Control strategy development for energy exchange in a decentralized heating systems | |
The goal of this project is 1) to explore potential control strategies to manage the energy exchange for a decentralized, bidirectional district heating network and 2) to implement the most promising controller, in terms of complexity and effectiveness, in a simulation environment | |
Structurally Colored Aerogels | |
Structural 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. | |
Development of a dynamic supramolecular hydrogel from tumor dECM | |
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. | |
PhD position: Scanning Probe Spectroscopy Investigation of Molecular Quantum Spin Systems | |
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. | |
Development of a Conceptual Framework for Resilience Assessment of Smart Energy Systems | |
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. | |
Non-Intrusive Load Monitoring and Customer Segmentation assisted demand flexibility provision in Swiss Households | |
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. | |
Economic potentials of electrolysers within a multi-energy district | |
There has been a rapid acceleration in the expansion of electrolysis capacity in recent years. The previous year marked a record-breaking deployment of electrolysis technology [1]. Recovering waste heat from electrolysis and compression can improve the overall system efficiency. The integration of such waste heat into district heating systems has been investigated in literature [2], where levelized cost of heat has been used to value waste heat. However, given dynamic electricity price, time-varying hydrogen demand, potential provision of ancillary services to energy systems, time-varying thermal demand within the district heating network and the supply temperature level, the marginal cost of waste heat can vary during the day. In addition, base heat supply systems such as heat pumps are equipped to supply the heating demand. Therefore, the pricing of waste heat from a hydrogen-based system needs to be lower than the pricing of heat from heat pumps, to be accepted by consumers. | |
Optimal design of heat prosumer communities (PSL/Empa) | |
In response to the Swiss Energy Strategy 2050 and potential gas supply vulnerabilities, there is a growing interest in developing small-scale district heating systems in Switzerland. Transitioning from singular, gas/oil-reliant heating systems to multi-energy networks not only aligns with the Swiss environmental commitments but also enhance resilience against supply disruptions. Traditional individual heating units, designed to meet peak demands, are often underutilized, while also posing concerns due to their dependency on gas supply. By interconnecting buildings, we can optimize energy use at the local level. Integrating advanced control systems into these networks can further enhance energy efficiency and responsiveness. Nonetheless, design of such small-scale district heating system is different from conventional centralized district heating system, in terms of cost, ecological impacts and additional constraints such as resource availability and limited space. Therefore, the economical and ecological aspects of such energy communities need to be thoroughly investigated taking into account different scenarios of retrofitting strategies, heating demand density, long-term thermal demand forecast and technology mixes including their operational and embodied emissions | |
Data-injection attack on data-driven controllers (ETH/Empa) | |
A data-injection attack is the unauthorized insertion of data into a system to corrupt data, compromise the system, or produce false outcomes. This cyber attack can affect databases, networks, and applications. Data accuracy is critical for decision-making, and this project will concentrate on building-level decision-making. | |
How reliable is the energy flexibility-assisted smart energy system | |
Amid the large-scale integration of renewables, energy system is increasingly relying on the demand-side flexibility provision. Flexibility provision with significant deviations from the contracted amount can be considered as a failure and associated with penalties. However, reliable provision of demand-side flexibility for system support has received little attention so far. This study aims to develop a conceptual framework for evaluating the reliability of demand-side flexibility exploring multiple sources of impacts, such as heat pump failure and occupants interactions. | |
Game-theoretic design of heat prosumer communities (ETH/Empa) | |
The Swiss Energy Strategy 2050 and concerns over gas supply vulnerabilities have sparked interest in small-scale district heating systems in Switzerland. Interconnecting buildings optimizes local energy use and moves towards decentralized systems where members are both consumers and producers. Leveraging energy storage systems and technologies within energy communities can reduce cost and revenue volatility for prosumers but also brings new challenges in cost distribution, potential manipulation risks, and operational strategies. | |
Life-cycle analysis of sustainable building automation (Empa) | |
One key to cleaner energy lies in digital transformation and smart energy system, but the elephant in the room is the associated rise in resouce consumption. Our previous work [1] demonstrates the concept of reusing discarded smartphones to connect the end-of-life of e-wastes with the start-of-life of smart buildings. Diverse controlled systems, control tasks, and algorithms have been considered. In addition, the sufficiency of communication with external agents has been quantified. The proof-of-concept experiments indicate the technical feasibility and applicability to typical tasks with satisfactory performance. As the capabilities of smartphones improve over time, higher computing performance and lower communication latency can be expected, which enhances the prospect of the proposed reuse concept. This practice of reuse, integral to the circular economy, extends the lifecycle of materials, reduces environmental impact, and promotes sustainable consumption. Embracing circularity and reuse not only conserves resources but also drives innovation in creating sustainable solutions for future needs. | |
Self-learning non-linear adaptive heating curve adjustment for intuitive optimization | |
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. | |
Living materials as an alternative to antibiotics to fight against pathogen infections. | |
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. | |
Fluid structure interaction simulation of a soft robotic wing | |
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. | |
Fully vapor-deposited perovskite solar cells for tandem applications | |
Perovskite-based tandem solar cells (TSCs) is a promising to enter the market due to their higher power conversion efficiency (PCE) potential and lower cost. However, the deposition of perovskite solar cells (PSCs) on top of the rough c-Si or Cu(In,Ga)Se2 (CIGS) subcell surface has always been a challenge, especially with solution-based techniques. Vapor deposition is an solvent-free industry scalable method for upscaling well controlled ambient perovskite thin-film photovoltaics that can achieve conformal coatings with minimal edge effects. This thesis will be focusing on developing high-performance tandem solar cells and modules based on vapor deposited perovskite solar cells combined with different subcells such perovskite, c-Si and CIGS solar cells. | |
Transfer Learning for Building Thermal Modeling | |
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. | |
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. | |
Stress and thermal characterization of bent graphene using THz na-noscopy | |
You will use THz nanoimaging techniques to investigate the properties of graphene in various condi-tions in the THz regime. | |
Flexible graphene-based THz detectors | |
You will fabricate THz bolometric detector elements, and will combine them to develop a THz camera suitable for 3D THz imaging | |
Fabrication and characterization of THz metasurfaces | |
You will use state of the art cleanroom microfabrication techniques and 3D printing for the develop-ment of THz devices such as Thz filters. | |
Decoding Alzheimer’s Protein Aggregation in Body Fluids | |
The two main proteins implicated in the pathology of AD are amyloid-beta and tau isoforms whose total content can be quantified in cerebrospinal fluid (CSF), blood plasma and serum. Yet, differences in morphology of these shape-shifting proteins in body fluids, which are also key indicators of disease stage, remains largely unknown and hence unavailable to clinicians. Recently, we discovered that the physical biomarkers (size, shape, morphology, assembly patterns and prevalence) of these protein aggregates on red blood cells (RBCs) strongly correlate with neurocognitive disorder levels in patients (Nirmalraj et al, Science Advances, 7, eabj2137, 2021). Our goal and vision are to investigate these new class of biomarkers and integrate them with clinical decision making to diagnose AD before it destroys cognition and memory in individuals. In this context, the proposed master thesis project will focus on resolving and quantifying the aggregation pathway of synthetically prepared Tau proteins at solid liquid interface using nanoscale imaging and chemical spectroscopy. The complete aggregation pathway from onset of oligomers to fibrils will be captured at single particle level using atomic force microscopy, electron microscopy and also the chemical structure resolved using Infrared and Raman spectroscopy. Knowledge developed in this project will serve as guidelines for classification of protein aggregates in blood and CSF from patients at various stages of decline in memory and cognition. |
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