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Session 2.16: Boosting LCM with AI, Machine Learning & Data Science Tools
Time:
Thursday, 11/Sept/2025:
2:30pm - 4:00pm
Session Chair: Antonino Marvuglia, Luxembourg Institute of Science and Technology, Luxembourg Session Chair: Peter Rudolf Hans Saling, BASF SE, Germany
Presentations
(15 minutes_S)
Integrating Large Language Models into the In-Silico environmental assessment of new chemicals and materials for SSbD
Gustavo Larrea-Gallegos, Antonino Marvuglia
Luxembourg Institute of Science and Technology, Luxembourg
(15 minutes)
Automated LCI Data Generation for Fine Chemicals via Retrosynthesis
Jonas Goßen, Ludwig Jolmes, Raoul Meys
Carbon Minds GmbH, Germany
(15 minutes_S)
From SMILES to Sustainability: Predicting the Full Life Cycle Inventory of Chemicals with Machine Learning
Shaohan Chen1, Johannes Schilling1, Tim Langhorst1, Martin Pillich1, Christopher Oberschelp2, André Bardow1
1Energy & Process Systems Engineering, ETH Zurich, 8092 Zurich, Switzerland; 2cological Systems Design, ETH Zurich, 8093 Zurich, Switzerland
(15 minutes)
Using Large Language Models to Predict Manufacturing Processes for Mechanically Engineered Products and Fill Data Gaps in Prospective LCA
Alexandra Belyaeva1, Torsten Hummen1, Christoph Helbig2
1Corporate Sector Research and Advance Engineering, Robert Bosch GmbH, Robert-Bosch-Campus 1, Renningen, 71272, Germany; 2Ecological Resource Technology, University of Bayreuth, Universitätsstr. 30, 95447, Bayreuth, Germany
(Short Oral + Poster)
Data lakes for CCF and PCF assessments – Automated approach for organizations
Sabrina Neugebauer, Desiree Lotz
iPoint systems gmbh, Germany
(6 minutes)
Harnessing AI for EPD Business Intelligence: Transforming Data into Actionable Insights at Holcim
