Dynamic Observation and Machine learning-assisted profiling for fast Assessment of submicroplastics and Native ecocorona In exposure media
Dynamic Observation and Machine learning-assisted profiling for fast Assessment of submicroplastics and Native ecocorona In exposure media
This project (2023-2025) is founded by PRIN2022 (Research Projects of Significant National Interest (P2022SET7C_001: https://chimica.unibo.it/it/ricerca/progetti-di-ricerca/progetti-nazionali/domani).
It is coordinated by Valentina Marassi Dipartimento di Chimica “Giacomo Ciamician” in collaboration with IMM-INRIM – Torino and CNR-ISSMC – Faenza.
The activity of our group is to integrate Analytical Pyrolysis (Py-GC-MS) with Asymmetrical Flow Field Flow Fractionation (AF4) to investigate the interaction between nanoplastics and environomental matrices and characterise the Bio-Corona.
Eco or bio-corona are formed in the environment due to the presence of nano- and microparticles, which are akin to natural polymers or even microorganisms. This topic has gained interest in recent years due to the high impact of this external layer, which not only changes the physiochemical characteristics but also influences their fate and toxicity.
Thanks to the ability of Py-GC-MS to characterize both plastic and biobased materials its novel combination with the separation techniques AF4 integrated with advanced multidetection systems can provide new insights on this important topic.
