FPU2025 - Exploring dara-driven/machine-learning models for guest-host interactions

The project involves computer quantum modelling to characterize guest-host interactions and guest occupancy capacity of clathrate hydrates under given thermodynamic conditions, aiming to explore potential applications in the field of gas sequestration and long-term storage. Developing data-driven/machine-learning potential models by benchmarking and cross-checking modern WF and DFT (including linear-scaling) electronic structure approaches on such non-covalent and non-standard interactions we plan to identify formation processes and phase transitions of such hydrates.