AI BioConversion: Advancing Biomass Pyrolysis: Experimental Kinetics, Hybrid Modeling, and Sustainable Energy Applications

Date: from 01/03/2025 to 30/05/2025
Duration: 3 months
Home laboratory: LADES - Laboratório de desenvolvimento de sistemas - Universidade Federal do Rio de Janeiro, Brasil
Host laboratory: L2CM - Laboratoire lorrain de chimie moléculaire - Université de Lorraine, France

This study aims to investigate biomass pyrolysis, focusing on the integration of kinetic modeling with machine learning to improve interpretability and scalability. A framework combining experimental investigations and modeling techniques will be developed to create an efficient, robust and sustainable pyrolysis process for various biomass feedstocks. The complexity of pyrolysis pathways makes it difficult to develop reliable first-principles models. To fill this gap, the effects of key biomass components and metallic elements will be explored to create a detailed kinetic model, incorporating data-driven approaches to establish a hybrid framework.