Room: Amazon
Date: Tuesday, 19 May 2026
Time: 16:15 - 17:15 CEST
Session code 4AO.5
Gasification processes for polygeneration and including biochar and classification model
Interpretable Classification Model for Identifying Potential Syngas Applications Based on Feedstock Properties And Process Parameters
Short Introductive summary
Residual biomass gasification is a promising pathway for sustainable energy and chemicals’ production. However, biomass feedstock variability and complex operational interactions limit the large-scale application of the process. This study presents a data-driven model to predict syngas composition and end-use application based on biomass’ properties and operational conditions, covering a wide range of residual biomass feedstocks, gasification conditions and reactor configurations. A CatBoost-based Decision Tree Regressor was trained on 133 experimental samples compiled from peer-reviewed studies. The dataset was augmented using the Synthetic Minority Over-sampling Technique (SMOTE) to mitigate class imbalance and enhance generalization across diverse gasification outcomes. Model performance was rigorously evaluated through nested cross-validation, yielding mean average errors of 4.2 ± 0.3 %vol for H2, 2.9 ± 0.4 %vol for CO, and 1.4 ± 0.3 %vol for CH4. Beyond composition predictions, the model accurately classified the most suitable syngas applications, achieving over 90% identification for heat/power generation, methanol and biofuel synthesis, and SNG production.
Presenter
Laura Catalina GONZÁLEZ
University EAFIT, Applied Science and Engineering Dpt., COLOMBIA
Presenter's biography
PhD candidate with four years of research experience in alternative fuels and thermochemical conversion. Research focused on bioSNG production from residual biomass, integrating data-driven and mechanistic modeling with laboratory-scale experimental and pilot system development.
Biographies and Short introductive summaries are supplied directly by presenters and are published here unedited
Co-authors:
S. García-Freites, Promigas, Barranquilla, COLOMBIA
M. Sanjuan, Promigas, Barranquilla, COLOMBIA
D. Acosta, Promigas, Barranquilla, COLOMBIA
A. Aristizabal, University EAFIT, Medellin, COLOMBIA
M.L. Botero, University EAFIT, Medellin, COLOMBIA
S. Builes, University EAFIT, Medellin, COLOMBIA
Session reference: 4AO.5.4