Mauricio Iglesias, MiguelRegueira López, AlberteHauwaert, Lucas van der2025-09-292025-09-292025https://hdl.handle.net/10347/42938Biorefineries promise to replace linear and fossil-based production by leveraging renewable resources. Yet their complexity arises from technical uncertainties, economic constraints, and a variety of process options. This thesis introduces a multi-scale methodology for early-stage biorefinery design based on superstructure optimization with the OUTDOOR framework. By integrating genome-scale metabolic models into superstructure optimization, the method identifies promising microbial and substrate combinations under data-scarce conditions. Reactor-scale optimization, tested on a co-culture for propionate production, addresses trade-offs between yield and productivity and accounts for stochastic uncertainties. At the process scale, the approach manages variable feedstock compositions, fluctuating market prices, and emerging technologies.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Early-stage biorefinery DesignKinetic modelingSuperstructure modelingMulti-objective optimizationStochastic optimization330303 Procesos químicos331005 Ingeniería de procesosdoctoral thesisembargoed access