Student Projects
Please find below the projects we have currently advertised on external page SiROP.
If there is no suitable project advertised or you already have a specific idea for a topic, do not hesitate to contact us, as we are happy to discuss other options. Please send a short description of what you would like to work on along with your CV and transcripts to . You might also find some inspiration for topics in the list of the most recent student projects at the bottom of this page.
Where to site direct air capture? - A global geospatial cost and performance analysis
Direct Air Carbon Capture and Storage (DACCS) of carbon dioxide (CO2) is a promising technology to combat climate change: DACCS systems remove CO2 directly from the atmosphere and store it permanently, thereby resulting in negative CO2 emissions and a decrease in the atmospheric CO2 concentration. The performance of DACCS systems depends on climate conditions, the price, availability, and greenhouse-gas-intensity of energy sources, and the proximity to CO2 storage sites. Therefore, operational costs and deployment potential of DACCS systems are highly location-specific. Current literature includes studies that examine the effect of location-specific meteorology on the techno-economic performance of DAC technologies [1], [2], [3]. Notably, Terlouw et al. [3] have determined the geospatial performance of potential grid-connected DAC plants in Europe, considering climate conditions as well as the environmental and economic costs associated with the entire DACCS supply chain. The analyzed supply chain includes the capture step and its energy requirements, CO2 transportation and storage. In this thesis, you will expand current geospatial models developed at ETH Zurich (among others the one by [3]) to a global scope, assessing additional environmental impact categories beyond climate change to identify potential environmental implications of large-scale DACCS deployment [1] M. Sendi, M. Bui, N. Mac Dowell, and P. Fennell, “Geospatial analysis of regional climate impacts to accelerate cost-efficient direct air capture deployment,” One Earth, vol. 5, no. 10, pp. 1153–1164, Oct. 2022, doi: 10.1016/j.oneear.2022.09.003. [2] J. F. Wiegner, A. Grimm, L. Weimann, and M. Gazzani, “Optimal Design and Operation of Solid Sorbent Direct Air Capture Processes at Varying Ambient Conditions,” Ind. Eng. Chem. Res., vol. 61, no. 34, pp. 12649–12667, Aug. 2022, doi: 10.1021/acs.iecr.2c00681. [3] T. Terlouw, D. Pokras, V. Becattini, and M. Mazzotti, “Assessment of Potential and Techno-Economic Performance of Solid Sorbent Direct Air Capture with CO2 Storage in Europe,” Environ. Sci. Technol., Jun. 2024, doi: 10.1021/acs.est.3c10041.
Keywords
Direct Air Capture; DAC; DACCS; geospatial model; optimization
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2024-10-28 , Earliest start: 2024-10-01
Organization Energy and Process Systems Engineering Laboratory
Hosts Bolongaro Vittoria
Topics Engineering and Technology
Prototyping electrically charged high-T thermal energy storage concepts
Thermal energy storage (TES) operating at temperatures above 500 °C has the potential to help decar-bonize processes which typically rely on fossil fuels to produce high-T heat on demand. Modelling this type of TES is challenging since heat transfer is dominated by radiation at high tempera-tures, which must be coupled with conduction and, for molten materials, convection. In a recent Master Thesis project, a voxel-based Monte Carlo model dedicated to these problems was developed and suc-cessfully validated against reference solutions [1]. The scope of this project is to exploit this software tool to investigate the design space of high-T thermal energy storage concepts, and to propose the design of a representative small-scale prototype to be tested in our labs.
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2024-10-09 , Earliest start: 2024-10-10
Organization Energy and Process Systems Engineering Laboratory
Hosts Casati Emiliano
Topics Engineering and Technology
Conquering Complex Substances like Water and CO2: Improving Molecular Modelling based on Symbolic Regression
Water and CO2 are known as troublemakers in the field of molecular modeling. At the same time, their description is crucial for developing tomorrow’s chemical and energy conversion processes, like heat pumps, carbon capture, or chemical production processes closing the carbon cycle. This thesis puts you at the forefront of improving a molecular model to describe molecular and mixture properties of Water, CO2, and other complex substances. In the thesis, you will apply symbolic regression, a machine technique, to enhance a recently proposed molecular model.
Keywords
Thermodynamics; Molecular modelling; Molecular property prediction; Process design; Machine Learning; Symbolic Regression; Water; CO2
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Semester Project , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2024-08-13
Organization Energy and Process Systems Engineering Laboratory
Hosts Hemprich Carl
Topics Engineering and Technology , Chemistry
Global geospatial analysis of off-grid direct air capture
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.
Keywords
Life cycle assessment, decarbonization, negative emission technologies, carbon dioxide removal, geospatial analysis, linear optimization
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Master Thesis , ETH Zurich (ETHZ)
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Published since: 2024-08-09 , Earliest start: 2024-10-01
Organization Energy and Process Systems Engineering Laboratory
Hosts Bolongaro Vittoria
Topics Engineering and Technology
Energy system modeling under uncertainty: mapping the solution space and measuring its coverage
Methods for addressing different types of uncertainty in energy system optimization models have been developed, aiming to explore ranges of possible solutions. However, it is not clear how well the solutions generated by these methods cover the entire space of possible feasible solutions, potentially leaving important solutions unexplored or deriving the same solutions multiple times leading to computational inefficiencies. A coverage metric is needed to effectively measure the energy system solution space, and to compare the solution space coverage across uncertainty methods.
Keywords
energy system, optimization, renewable, uncertainty, sustainable
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Semester Project , Master Thesis
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Published since: 2024-07-27 , Earliest start: 2024-09-02
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Organization Energy and Process Systems Engineering Laboratory
Hosts Mayer Patricia
Topics Mathematical Sciences , Engineering and Technology