Titled “AI Meets Biodegradation: Digital Tools for Smarter Bio-based Materials,” the event explored how artificial intelligence is reshaping the way bio-based materials are designed, tested, and understood.

Moderated by Cristina Blaya (CETEC), the session gathered researchers and innovators from across the scientific community. Throughout the webinar, speakers highlighted how AI and data-driven approaches are accelerating progress toward circular, bio-based solutions, bridging the gap between molecular design and real-world biodegradation.

Jessica N. Lalonde (Los Alamos National Laboratory) opened the session by presenting a machine learning–guided framework for designing polyhydroxyalkanoate (PHA) copolymers and blends. Her work demonstrated how advanced computational tools can streamline material development and uncover new design possibilities.

Building on this, Marharyta Domnich (Digiotouch) introduced the AI-driven approach developed within the MAGICBIOMAT project. Her presentation focused on the design of bio-based and biodegradable materials, including PLA, PBAT, PBS, and TPS blends, showcasing how digital tools can support more efficient and targeted innovation.

Closing the presentations, Marianna Kotzabasaki (AUA) shared a novel framework for predicting multiple properties in PHA-based biopolymers. By combining machine learning models with experimental data, her approach offers new insights into the relationship between material structure and performance.

The session concluded with a lively discussion, as participants exchanged questions and reflections on both the opportunities and the challenges of integrating AI into sustainable polymer systems.

The ANIPH–MAGICBIOMAT webinar series continues to build a dynamic platform for knowledge exchange. The next session, titled “3D Printing and Biofabrication: Designing sustainable materials” is scheduled for the end of June. Stay tune to discover more!

Did you miss our second webinar? Watch it here.

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Cover photo by Sören Funk on Unsplash