OL.20.004 – INFORM Intelligent fingerprinting of organic mixtures in prebiotic environments
In the investigation of the origins of life on Earth and beyond, understanding the reactions taking place in the prebiotic phase is one of the first major challenges to tackle. This difficulty is caused by the impact of different initial reagents and reaction conditions that can result into a variety of unresolved complex mixtures (UCMs) of organic material. However, these UCMs, though unknown, are reproducible under similar conditions. In this proposal, experiments will aim to approximate planetary environments by including the gas, liquid and solid phase, generating multiple UCMs. The aim is to exploit the reproducibility and find the fingerprints of these UCMs using advanced analytical techniques to train and develop a machine-learning model. In this interdisciplinary study, prebiotic chemistry routes will thus be explored using an innovative combination of state-of-the-art mass-spectrometry techniques and machine-learning algorithms. The resulting model will be able to identify prebiotic molecules and formation pathways using the fingerprints of the laboratory-generated UCMs under a variety of conditions.
machine learning, mass spectrometry, Origins, prebiotic chemistry
|Organisation||University of Amsterdam (UvA)|
|Name||dr. ir. A. (Annemieke) Petrignani|