Academy of Finland  
 
 
 
 
 
Funding decision
 
Organisation University of Jyväskylä
Project title Improving thermodynamic property estimates of SOA constituents using machine learning
Applicant / Contact person Hyttinen, Noora
Decision No. 338171
Decision date 03.06.2021
Funding period 01.09.2021 - 31.08.2024
Funding 244 440
   
Project description
Low volatility organic compounds contribute to the formation and growth of atmospheric aerosol particles. Thermodynamic properties of these compounds affect the properties of the aerosol, especially their lifetimes and ability to act as cloud condensation nuclei. This project investigates the potential of using machine learning based methods in thermodynamic property calculations. Machine learning is used in combination with quantum chemistry to compute thermodynamic properties of relevant multifunctional organic compounds in various atmospherically relevant systems. The computational results are compared with corresponding experimental values.