 ETH Zurich| Acronym | ETHZ | | Homepage | http://www.ethz.ch/ | | Country | Switzerland | | ZIP, City | | | Address | | | Phone | | | Type | Academy | | Current organization | ETH Zurich | | Child organizations | | | Members | | | Memberships | | | Partners | |
Open OpportunitiesEnergy storage systems become increasingly important to tackle the intermittent nature of renewable energy sources such as photovoltaics and wind turbines. This thesis focuses on a novel energy storage solution where excess electrical energy is converted into heat and back into electricity, using a novel piston-based engine concept that achieves over 70% round-trip efficiency. The aim is to design, optimize, and control this thermal energy storage system and to assess its economic potential in various scenarios. - Environmental Technologies, Interdisciplinary Engineering, Mechanical Engineering
- Master Thesis
| The Swiss Energy Strategy 2050 aims to achieve zero net emissions target as of 2050. The four leading Swiss research institutes — Paul Scherrer Institute (PSI), Swiss Federal Laboratories for Materials Science and Technology (EMPA), Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), and Swiss Federal Institute of Aquatic Science and Technology (EAWAG)—are at the forefront of this en-deavour. In the context of the SCENE project, these institutes are collaboratively developing science-based roadmaps that outline the anticipated pathways to attain net-zero emissions before 2040. The tran-sition to net zero requires a multifaceted approach, encompassing technological advancements, con-sumption reductions, and market-based mechanisms for emission compensation and reduction. An es-sential component of this transition is a comprehensive CO2 emission-related cost analysis. This analysis will evaluate the financial implications of shifting energy technologies, reducing consumption, and imple-menting market-based emission compensation and reduction strategies. - Earth Sciences, Economics, Engineering and Technology, Policy and Political Science
- ETH Zurich (ETHZ), Master Thesis
| Direct air capture (DAC) is an indispensable technology for meeting the challenges of achieving net-zero emissions [1]. Despite its promise, DAC with CO2 storage (DACCS) faces significant hurdles, primarily due to its (current) high energy intensity and capital expenditures, which are sensitive to design- and location-specific factors. Optimal carbon dioxide removal (CDR) efficiency is reached when powered by low-carbon energy sources [2–4]. This indicates the potential of so-called `off-grid' DACCS designs – i.e., DACCS systems without a connection to the power grid network – since they allow a system fully powered by renewable energy sources, thereby avoiding emissions from currently carbon-intensive power grids. However, off-grid systems rely on intermittent renewable energy sources, such as solar photovoltaic (PV) and wind turbines. The intermittency of these sources, the power requirements of DACCS, and the need for heat limit the feasibility of widespread deployment, especially in land-constrained areas. Here, the main goal is to assess the performance of off-grid DACCS with a global scope by extending an earlier geospatial model developed at ETH Zurich.
Prerequisites
Basic knowledge of energy technologies and energy systems analysis, techno-economic analysis, and life cycle assessment. Familiarity with negative emissions technologies/carbon dioxide removal is an asset. Familiarity and knowledge of Python, geospatial analysis, and linear optimization is a plus. - Engineering and Technology
- ETH Zurich (ETHZ), Master Thesis
| Recent advances in model-free Reinforcement Learning have shown superior performance in different complex tasks, such as the game of chess, quadrupedal locomotion, or even drone racing. Given a reward function, Reinforcement Learning is able to find the optimal policy through trial-and-error in simulation, that can directly be deployed in the real-world. In our lab, we have been able to outrace professional human pilots using model-free Reinforcement Learning trained solely in simulation.
- Flight Control Systems, Intelligent Robotics, Knowledge Representation and Machine Learning
- Master Thesis, Semester Project
| As Europe moves towards a renewable energy future, heat pumps are becoming essential in reducing fossil fuel dependency in building heating. Although heat pumps are generally more efficient than traditional combustion-based systems, the high cost of electricity in Europe makes it essential to optimize their operation for affordability.
Heat pump efficiency is closely linked to the amount of energy and power required to maintain comfortable indoor temperatures, which vary significantly by user preferences and building specifics. Strategies such as temperature setbacks—reducing heating when the building is unoccupied or at night—can greatly enhance efficiency. However, applying these strategies effectively requires a nuanced understanding of user-specific comfort ranges and sensitivity to temperature changes.
- Behavioural and Cognitive Sciences, Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences
- Collaboration, Master Thesis
| Electric mobility is key for decarbonising road transport. Its uptake in Switzerland and other countries has slowed down recently, threatening important progress in climate mitigation. This project will empirically explore some of the reasons why this is happening, using a range of statistical, bottom-up models. - Applied Statistics, Economics, Public Policy, Stochastic Analysis and Modelling
- Master Thesis
| The main objective of this project is to analyse tiller densities of perennial ryegrass depending on the management type, the ploidy, and the cultivar. - Environmental Impact Assessment, Plant Improvement (Selection, Breeding and Genetic Engineering), Plant Protection (Pests, Diseases and Weeds)
- Bachelor Thesis
| This research aims to advance biohybrid robotics by integrating living biological components with artificial materials. The focus is on developing computational models for artificial muscle cells, a critical element in creating biohybrid robots. Challenges include modeling the complex and nonlinear nature of biological muscles, considering factors like elasticity and muscle fatigue, as well as accounting for fluid-structure interaction in the artificial muscle's environment. The research combines first principle soft body simulation methods and machine learning to improve understanding and control of biohybrid systems. - Biology, Engineering and Technology, Information, Computing and Communication Sciences, Physics
- Bachelor Thesis, Master Thesis, Semester Project
| In our project, the objective is to detect nitrogen dioxide gas (NO2) through Carbon Nanotube (CNT) gas sensor array by repeatedly measuring the transfer characteristics of the CNT-FETs (Field Effect Transistors) in the array. However, achieving sensor recovery poses a challenge, necessitating the application of high voltage pulses at regular intervals to heat the channel and desorb gas molecules (self-heating). Our current measurement mode face challenges in independently controlling and tuning the voltages for each device. This project aims to develop a new PCB design that addresses these challenges.
- Electrical and Electronic Engineering
- Master Thesis, Semester Project
| This project aims to develop an online learning framework for achieving precise position control of a soft robotic arm while adapting to time-varying system dynamics. - Engineering and Technology
- Master Thesis
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