Energy and Process Systems Engineering Laboratory

Open Opportunities

Integrating Machine Learning Process and Thermodynamic Modeling for Separation Processes ETH Zurich Energy and Process Systems Engineering Laboratory Do you want to combine your knowledge of process modeling with machine learning and thermodynamic modeling? In this project, you will evaluate the efficiency and accuracy of ML-based adsorption process modeling compared to existing first-principle models. Adsorption separation processes are, e. g., required in the chemical industry or for carbon capture applications. For that, you will integrate adsorption calculations based on classical Density Functional Theory into the ML model. This integration enables the large-scale prediction of separation performance for many materials at the process level. Chemistry, Engineering and Technology, Information, Computing and Communication Sciences Bachelor Thesis, Semester Project

Global geospatial analysis of off-grid direct air capture ETH Zurich Energy and Process Systems Engineering Laboratory 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

Where to site direct air capture? - A global geospatial cost and performance analysis ETH Zurich Energy and Process Systems Engineering Laboratory 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. Engineering and Technology ETH Zurich (ETHZ), Master Thesis