The project aims to enhance CO2 capture simulation by improving multiphase reaction algorithms and thermodynamic models, making carbon capture processes more efficient.
This PhD project, as part of the INNO-CCUS CapSim initiative, focuses on advancing the simulation technology for solvent-based CO2 capture. CO2 capture plays a critical role in mitigating climate change, and accurate simulations are essential for designing, operating, and optimizing these processes. The project aims to improve the core multiphase reactive algorithms and better integrate thermodynamics, kinetics, and transport phenomena into the simulations.
Key objectives include implementing and improving RAND-based algorithms for next-generation CO2 capture techniques and enhancing the robustness and efficiency of simulations for various solvent systems, including amine-based solvents, chilled ammonia, and non-aqueous solvents. A significant challenge lies in modeling complex reactions in non-ideal electrolyte mixtures, particularly in systems with simultaneous phase equilibrium.
The project will advance the state-of-the-art by leveraging novel RAND-based multiphase reaction algorithms developed at DTU, which are more efficient and converge faster than traditional methods. These algorithms simultaneously handle phase and chemical equilibrium, making them particularly suitable for systems with multiple phases and complex reactions. Additionally, the project will compare advanced electrolyte models, such as ex-UNIQUAC and e-NRTL, using automatic differentiation to generate thermodynamic properties, allowing for quick and accurate model evaluation.
This research will enhance the accuracy and robustness of simulation tools for standard and novel carbon capture processes. For society, this means accelerated progress toward reducing anthropogenic greenhouse gas emissions and mitigating climate change. The industry will benefit from cost-effective technologies for CO2 capture, leading to cost savings. Scientifically, the project will contribute to the development of cutting-edge minimization and root-finding multiphase reaction algorithms.
Main supervisor:
Professor Wei Yan
Co- supervisor:
Professor Erling Halfdan Stenby
Head of project:
Professor Nicolas von Solms