(752f) Incorporating Hydrodynamics into Spatiotemporal Metabolic Models of Bubble Column Gas Fermentation
AIChE Annual Meeting
2016
2016 AIChE Annual Meeting
Innovations of Green Process Engineering for Sustainable Energy and Environment
Sustainable Microbial Process for Food, Feeds, Energy, and Environment
Thursday, November 17, 2016 - 4:55pm to 5:15pm
A promising route to renewable liquid fuels and chemicals is the fermentation of carbon monoxide containing gas streams to synthesize desired products such as ethanol and 2,3-butanediol. We recently developed a spatiotemporal metabolic model for bubble column reactors with the CO fermenting bacterium Clostridium ljungdahlii as the microbial catalyst [1]. This ï¬rst generation model was based on the simplifying assumptions of ideal plug ï¬?ow for the vapor phase and plug ï¬?ow plus axial dispersion for the liquid phase. However, industrial bubble column reactors are complex multiphase processes in which spatial variations in the gas superï¬cial velocity, volumetric holdup and interfacial area can have profound eï¬?ects on fermentation performance.
We discuss the development of a second-generation bubble column model that accounts for the eï¬?ects of gas phase hydrodynamics on cellular growth, nutrient update and byproduct synthesis rates in a temporarily and spatially resolved manner. The modeling approach involves the coupling of a genome-scale metabolic reconstruction with mass and momentum balances that allow the calculation of local gas metabolite concentrations, superï¬cial velocity, volumetric holdup and interfacial area as well as local concentrations of biomass and liquid phase metabolites. The resulting set of partial diï¬?erential equations with embedded linear programs is spatially discretized and numerically integrated using the MATLAB based code DFBAlab. Simulations results are shown for two CO fermentating organisms: the research model C. ljungdahlii and the industrially relevant Clostridium autoethanogenum. Model predictions are compared to those generated without gas phase hydrodynamics and to experimental data collected from a laboratory scale bubble column reactor with respect to CO conversion, biomass production, ethanol titer and ethanol-to-acetate ratio.
We discuss the development of a second-generation bubble column model that accounts for the eï¬?ects of gas phase hydrodynamics on cellular growth, nutrient update and byproduct synthesis rates in a temporarily and spatially resolved manner. The modeling approach involves the coupling of a genome-scale metabolic reconstruction with mass and momentum balances that allow the calculation of local gas metabolite concentrations, superï¬cial velocity, volumetric holdup and interfacial area as well as local concentrations of biomass and liquid phase metabolites. The resulting set of partial diï¬?erential equations with embedded linear programs is spatially discretized and numerically integrated using the MATLAB based code DFBAlab. Simulations results are shown for two CO fermentating organisms: the research model C. ljungdahlii and the industrially relevant Clostridium autoethanogenum. Model predictions are compared to those generated without gas phase hydrodynamics and to experimental data collected from a laboratory scale bubble column reactor with respect to CO conversion, biomass production, ethanol titer and ethanol-to-acetate ratio.
1. Chen, J., J. A. Gomez, K. Hoï¬?ner, P. I. Barton and M. A. Henson, â??Metabolic Modeling of Synthesis Gas Fermentation in Bubble Column Reactors,â? Biotechnology for Biofuels, 8, 89, doi:10.1186/s13068-015-0272-5 (2015).