Supplementary material for the article "Machine Learning Model to Predict Saturation Vapor Pressures of Atmospheric Aerosol Constituents"

Beskrivning

This is supplementary dataset for article "Machine Learning Model to Predict Saturation Vapor Pressures of Atmospheric Aerosol Constituents". It contains following elements: - Machine learning models (in Python) for predicting saturation vapor pressures using cosmo-files (COSMO-ML-psat.zip/cosmo-ml) - cosmo-files of the training data (COSMO-ML-psat.zip/cosmo-files) - cosmo-files of all conformers of the training compounds (cosmo-files-all-conformers.zip) All cosmo-files were calculated at the BP-TZVPD-FINE level of theory using TURBOMOLE version 7.7.
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Publiceringsår

2024

Typ av data

Upphovspersoner

Kemian laitos

Hyttinen, Noora Orcid -palvelun logo - Rättighetsinnehavare

Unknown

Hyttinen, Noora Orcid -palvelun logo - Upphovsperson

Projekt

Övriga uppgifter

Vetenskapsområden

Kemi

Språk

engelska

Öppen tillgång

Öppet

Licens

Creative Commons Attribution 4.0 International (CC BY 4.0)

Nyckelord

Atmospheric sciences, machine learning, COSMO, saturation vapor pressure, atmospheric scienes, höyrynpaine, ilmakehätieteet, koneoppiminen

Ämnesord

Temporal täckning

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