(546f) Understanding Risk of Dissolved Gas Gradients in Sparged Systems

Bioreactors, fermenters, and hydrogenation reactors involve mass transfer of a gaseous species to or from the liquid phase using sparged bubbles, and the dissolved gas is consumed or produced in a (bio)chemical reaction. The aqueous concentration of these species can determine the quality and yield of the final product and can be monitored by in-process or offline process analytical technology (PAT) or probes. An example is dissolved oxygen (DO) in a bioreactor or fermenter, where changes in DO can drive metabolic changes in the cellular metabolism. However, during scale-up it is possible to observe heterogeneity in aqueous concentrations due to mixing challenges. There is little exploration in the literature of how to estimate when such systems are operating in regimes of heterogeneity without direct measurement. This situation is common in industrial systems where often only a single probe is used to provide information about the dissolved gas concentration level for feedback control. Complex Computational Fluid Dynamics (CFD) models that incorporate bubble-liquid drag coupling, bubble breakage/coalescence, and mass transfer between the gaseous and liquid phases could provide such a prediction. CFD-based approaches are numerically expensive, but more importantly often require tuning multiple sub-model choices and/or parameters such as the initial bubble size from the sparger and the drag model form, diminishing their practical utility.

Here, the Dissolved Gas Gradient, DGG, number is developed to describe the degree of heterogeneity of dissolved gas species. The DGG number is derived from a dimensionless analysis of the various time scales, which results in a modification to the well-known Damköhler number by incorporating a description of the heterogeneity of the mass transfer of the gas species. The unknowns in the complex behavior of the gas bubbles can be lumped into a single parameter, which can be tuned if multiple measurements are available, and if measurements are unavailable, literature evidence can be used to give estimates. A greatly simplified CFD model employing the one lumped parameter is developed. This analysis shows that the DGG number alone sufficiently describes the degree of heterogeneity of the concentration of the gaseous species in the liquid phase. The importance of this analysis will be demonstrated by determining the DGG number for various cell culture operating conditions including bioreactor scale, P/V, and cell culture type.