Computational Design of Flexible MOFs for the Separation of Hydrocarbons.

• Applicant: Mikhail Suyetin, Ph.D.
• Subject Area: Theoretical Chemistry: Molecules, Materials, Surfaces ; Physical Chemistry of Solids and Surfaces, Material Characterisation
• Term: from 2020 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 448235795

Separation of hydrocarbons, specifically ethylene/ethane, propylene/propane, xylene isomers, etc., is a high-ranking separation problem and highly challenging because of the similar physicochemical properties of the molecules in the hydrocarbon mixtures. Thermal processes at industrial scale consume large amounts of energy and are equipment intensive. Shape-selective structures, such as metal-organic-frameworks (MOFs) deposited on carriers forming a membrane have a high potential to drastically reduce the energy input, while technically achieving full separation. Here I aim to screen the CoRE MOF database to generate a computationally inexpensive model to prescreen databases of potential MOF structures. The computationally inexpensive models will be trained employing Multivariate Data Analysis to reveal hidden structure-property relationships, and then select MOFs in a large chemical space of more than 500,000 MOFs from different databases. The best 1000 MOFs will be then investigated with molecular dynamics and Monte Carlo simulations will be thoroughly performed to identify the best MOFs for particular hydrocarbon mixture (ethylene/ethane, propylene/propane, xylene isomers, etc.).

• DFG Programme: Research Grants