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This MMD TechHub project uses machine learning to predict anharmonic corrections of highly excited interstellar hydrocarbons

This is a proof-of-concept study focusing on improving the spectral characterization of Polycyclic Aromatic Hydrocarbons (PAHs). PAHs are key ingredients of interstellar chemistry, contributing to strong infrared emission features observed in galaxies across time.

Currently, the vibrational spectra of PAHs in space can only be partially identified, limiting our understanding of their chemical composition. Beyond astronomy, this project has implications for Health applications, as PAHs are carcinogenic and a source of pollution and there is thus a great demand for sensitive means to detect and identify them in the environment.

The Orion Bar seen by the James Webb Space Telescope. Credits: PDRs4ALL team, NASA, ESA, CSA.

Researchers

Dr. A. (Alessandra) Candian

PI

Prof. dr. W.J. (Wybren Jan) Buma

Co-PI

Dr. D. (Daniela) Huppenkothen MSc

Co-PI