2016 AIChE Annual Meeting
(752f) Incorporating Hydrodynamics into Spatiotemporal Metabolic Models of Bubble Column Gas Fermentation
Authors
Michael A. Henson - Presenter, University of Massachusetts Amherst
Jin Chen, University of Massachusetts Amherst
Xiangan Li, University of Massachusetts Amherst
Derek Griffin, LanzaTech Inc.
Xueliang Li, LanzaTech Inc.
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).