Rate My Professor Ekaterina Pas

Pas's research develops cost-effective quantum chemical methods for intermolecular interactions and chemical reactions in condensed systems such as ionic liquids, molecular crystals, and solvents. It addresses prediction of thermodynamic and transport properties including melting points, lattice energies, conductivity, viscosity, solvation mechanisms, solubility, and redox potentials. Studies cover kinetics and thermodynamics of reactions like radical polymerization and CO2 absorption in ionic media, with applications to green technologies including radical organic batteries, adhesive coatings, and electrode materials. Methods involve large-scale ab initio calculations, molecular dynamics simulations, and machine learning, coded for massively parallel computers. As Chief Investigator on ARC projects, such as the 2026 Discovery Project on digitally-guided catalytic strategies for complex molecule synthesis ($1,205,442), her work advances sustainable energy and materials. Key publications: "Accurate Prediction of Three-Body Intermolecular Interactions via Electron Deformation Density-Based Machine Learning" (Journal of Chemical Theory and Computation, 2023), "Appropriate clusterset selection for the prediction of thermodynamic properties of liquid water with QCE theory" (Physical Chemistry Chemical Physics, 2023), "Structural elucidation of polydopamine facilitated by ionic liquid solvation" (Physical Chemistry Chemical Physics, 2023). She teaches computational chemistry, supervises PhD students, and advances gender equity, increasing female professors in Monash School of Chemistry from zero to five.