Computational chemistry
TalTech priority area
Research classification (Frascati)
Head of the research group
Research group member
Doctoral students
Keyword
Overview
Research in the Computational Chemistry Research Group is focused on the study of reactionmechanisms and weak (host-guest) interactionsutilizing modern electronic structure methods(ab initio, DFT). We have competence in modelling of both organic and organometallic reactioncomplexes as well as weakly bound systems.We use quantum-chemistry software such asGaussian, Turbomole and Orca. Besides smallin-house computational facilities we have accessto the ETAIS research computing infrastructure,a part of which is located on TalTech campus.Research in recent years has been focused on thedevelopment of force field and machine learningbased approaches for description of inorganiccompounds. A highly accurate model utilizingmoment tensor potentials was developed formodeling interactions between water molecules.Efforts towards a polynomial-based machinelearning model for organic solvents is underway.In parallel we are studying the possibilities fordescribing conformations of metal hydroxidesand intramolecular interactions.In a side project we are searching for stableforms of novel nonmetal hydrides with potentialapplications in the development of systems withhigh energy content. In collaboration with our Turkish colleagues (EgeUniversity), we are investigating weak interactions between DNA molecules and drug-typesubstances in order to predict possible mutagenicside effects of the drugs.
Related department
Teadusgrupiga seotud publikatsioonid
- Prigorchenko, E. Kaabel, S., Narva, T., Baškir, A., Fomitšenko, M., Adamson, J., Järving, I., Rissanen, K., Tamm, T., Aav, R. Formation and trapping of the thermodynamically unfavoured inverted-hemicucurbit[6]uril // Chemical communications (2019) vol. 55, 63, p. 9307−9310 : ill.
https://doi.org/10.1039/C9CC04990H - Lomaka, A., Tamm, T. Linearization of moment tensor potentials for multicomponent systems with a preliminary assessment for short-range interaction energy in water dimer and trimer // The Journal of chemical physics (2020) vol. 152, 16, art. 164115, 8 p. : ill.
https://doi.org/10.1063/5.0007473 - Piir, G., Kahn, I., García-Sosa, A.T., Sild, S., Ahte, P., Maran, U. Best practices for QSAR model reporting: physical and chemical properties, ecotoxicity, environmental fate, human health, and toxicokinetics endpoints // Environmental Health Perspectives (2018) vol. 126, 12, art. 126001 ; 20 p.: ill.
https://doi.org/10.1289/EHP3264