SOURCE-LINKED INTELLIGENCE
Advanced Identification of Atmospheric Compounds
will address these challenges by creating an MS library using computational methods. I will develop a comprehensive dataset of mass spectra of pure atmospheric compounds via simulations, alongside a machine learning tool for enhanced compound identification. This tool will be used to identify unknown compounds from aerosol samples collected during field campaigns. By integrating quantum chemical MS simulations, machine learning, and atmospheric science, CLOUDMAP will advance the digitization of atmospheric chemistry, improve the understanding of aerosol formation, and contribute to both climate change mitigation and improved air quality. machine learning, compound identification, mass spectral library, fragmentation mass spectrometry, mass spectrometry simulations, semi-empirical quantum chemistry, oxidized organic compounds
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 202125.12
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T03:21:21.440Z. This is not the publication date.