0000000000597171
AUTHOR
Noora Hyttinen
Comparison of saturation vapor pressures of α-pinene + O3 oxidation products derived from COSMO-RS computations and thermal desorption experiments
Accurate information on gas-to-particle partitioning is needed to model secondary organic aerosol formation. However, determining reliable saturation vapor pressures of atmospherically relevant multifunctional organic compounds is extremely difficult. We estimated saturation vapor pressures of α-pinene-ozonolysis-derived secondary organic aerosol constituents using Filter Inlet for Gases and AEROsols (FIGAERO)–chemical ionization mass spectrometer (CIMS) experiments and conductor-like screening model for real solvents (COSMO-RS). We found a good agreement between experimental and computational saturation vapor pressures for molecules with molar masses around 190 g mol−1 and higher, most wit…
Saturation vapor pressure characterization of selected low-volatility organic compounds using a residence time chamber
Saturation vapor pressure (psat) is an important thermodynamic property regulating the gas-to-particle partitioning of organic compounds in the atmosphere. Low-volatility organic compounds (LVOCs), with sufficiently low psat values, primarily stay in the particle phase and contribute to aerosol formation. Obtaining accurate information on the psat of LVOCs requires volatility measurements performed at temperatures relevant to atmospheric aerosol formation. Here, we present an isothermal evaporation method using a residence time chamber to measure psat for dry single-compound nanoparticles at 295 K. Our method is able to characterize organic compounds with psat spanning from 10−8 to 10−4 Pa …
Comparison of computational and experimental saturation vapor pressures of α-pinene + O<sub>3</sub> oxidation products
Abstract. Accurate information on gas-to-particle partitioning is needed to model secondary organic aerosol formation. However, determining reliable saturation vapor pressures of atmospherically relevant multifunctional organic compounds is extremely difficult. We estimated saturation vapor pressures of α-pinene ozonolysis derived secondary organic aerosol constituents using FIGAERO-CIMS experiments and COSMO-RS theory. We found a good agreement between experimental and computational saturation vapor pressures for molecules with molar masses around 190 g mol−1 and higher, most within a factor of 3 comparing the average of the experimental vapor pressures and the COSMO-RS estimate of the iso…
Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions
We have trained the Extreme Minimum Learning Machine (EMLM) machine learning model to predict chemical potentials of individual conformers of multifunctional organic compounds containing carbon, hydrogen, and oxygen. The model is able to predict chemical potentials of molecules that are in the size range of the training data with a root-mean-square error (RMSE) of 0.5 kcal/mol. There is also a linear correlation between calculated and predicted chemical potentials of molecules that are larger than those included in the training set. Finding the lowest chemical potential conformers is useful in condensed phase thermodynamic property calculations, in order to reduce the number of computationa…
Predicting liquid–liquid phase separation in ternary organic–organic–water mixtures
Liquid–liquid phase separation (LLPS) affects the water uptake of aerosol particles in the atmosphere through Kelvin and Raoult effects. This study investigates LLPS in ternary mixtures containing water and two organic compounds, using a conductor-like screening model for real solvents (COSMO-RS). COSMO-RS found LLPS in all of the studied mixtures containing water and proxies for primary and secondary organic aerosol (POA and SOA, respectively), due to the limited solubility of the hydrophobic POA proxies in water. The computations predict additional three-phase states in some of the SOA–POA–water mixtures at relative humidity (RH) close to 100%, which was not observed in experiments, likel…
Supplementary data for the article "Predicting liquid-liquid phase separation in ternary organic-organic-water mixtures"
Artikkelin "Predicting liquid-liquid phase separation in ternary organic-organic-water mixtures" lisäaineisto. The data set contains the supplementary data of the article "Predicting liquid-liquid phase separation in ternary organic-organic-water mixtures" published in Phys. Chem. Chem. Phys. The data includes cosmo-files used in the COSMOtherm calculations of the article.
Supplementary data for the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions"
The data set contains the supplementary data of the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions" published in J. Phys. Chem. Lett., https://doi.org/10.1021/acs.jpclett.2c02612. The data includes: - A machine learning (EMLM) model for predicting chemical potentials of individual conformers of multifunctional organic compounds calculated by the COSMOtherm program - COSMO-files used for training and testing the EMLM model - Descriptors and chemical potentials used for the training and testing the model Artikkelin "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds i…