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Oxygen mass transfer limitations set the performance boundaries of microbial PHA production processes – A model-based problem investigation supporting scale-up studies

Author:
Papapostolou, Apostolos, Karasavvas, Evgenios, Chatzidoukas, Christos
Source:
Biochemical engineering journal 2019 v.148 pp. 224-238
ISSN:
1369-703X
Subject:
algorithms, asphyxia, bioreactors, biosurfactants, issues and policy, mass transfer, models, oxygen, oxygen consumption, polyhydroxyalkanoates, polymerization
Abstract:
The microbial production of polyhydroxyalkanoates has been reported as a complex process with numerous parameters affecting its performance. Although a great deal of effort has been devoted to the investigation of crucial operating variables, via accurate dynamic polymerization/metabolic/macroscopic models, little work has been implemented on the development of a detailed oxygen mass transfer model. In this study a sophisticated model for PHA producing bacterial cultures is developed, accounting for oxygen mass transfer phenomena in a bioreactor. The volumetric mass transfer coefficient, kLa, is computed as the product of two individual factors, calculated separately with respect to operational conditions, geometrical parameters and culture physiochemical properties. Moreover, an enhancement/prevention factor of oxygen transfer rate (OTR) is taken into consideration. OTR is enhanced due to the oxygen consumption by the cells, and prevented because of the physical blocking effect originated by the cells and excreted biosurfactants, forming thin layers in the gas-liquid interface. Upon integration of the present oxygen mass transfer model to a pre-existed metabolic/macroscopic one, four different operating policies for the progressive improvement of selected process performance indices are tested. Model predictions prove a severe OTR reduction and consequent culture suffocation because of mass transfer limitations in high cell concentrations and biopolymer accumulations regimes. The latter reveals the respective restrictions on the biological process performance and points out the necessity for model-based optimization algorithms.
Agid:
6380888