The project ML-DES aims to develop a fast and accurate interatomic potential to simulate an ensemble of deep eutectic solvents (DESs) composed of choline chloride and a variety of H-bond donor molecules using a machine learning (ML) approach. Thanks to this potential, exploration of the structure and properties of different DESs will improve the range of application of these non-toxic and environmentally friendly solvents that are a promising substitute to more traditional volatile organic compounds.
The funding provides a total of 260000 GPU hours to be used on the supercomputer LUMI and involves Marco Bortoli as P. I. with the collaboration of Hylleraas alumnus Sondre Eliasson, Hylleraas PhD student Manuela Leal Nader, and Jordan Rio who will join the team in Oslo in Spring 2026. Granted: August 18th, 2025.
Funded by: https://www.eurohpc-ju.europa.eu/index_en