Predictive modeling of chemical separations: From high-throughput screening to first principles simulations

Description:
Monte Carlo and molecular dynamics simulations can provide molecular-level insights into the complex processes underpinning chemical separations, and high-throughput computations allow for discovery of promising separation materials and optimal separation conditions. This talk will highlight (i) the use of Monte Carlo simulations with transferable molecular models to unravel the details of the retention mechanism in reversed-phase liquid chromatography (RPLC) and to discover zeolites challenging separations, (ii) the use of first principles Monte Carlo simulations to investigate highly selective adsorption of gas molecules in metal-organic frameworks with under-coordinated metal nodes and of reaction equilibria in cation-exchanged zeolites.

Speaker: J. Ilja Siepmann - University of Minnesota