Literature DB >> 24838309

An improved dynamic method to measure kL a in bioreactors.

Andrew L Damiani1, Min Hea Kim, Jin Wang.   

Abstract

An accurate measurement or estimation of the volumetric mass transfer coefficient kL a is crucial for the design, operation, and scale up of bioreactors. Among different physical and chemical methods, the classical dynamic method is the most widely applied method to simultaneously estimate both kL a and cell's oxygen utilization rate. Despite several important follow-up articles to improve the original dynamic method, some limitations exist that make the classical dynamic method less effective under certain conditions. For example, for the case of high cell density with moderate agitation, the dissolved oxygen concentration barely increases during the re-gassing step of the classical dynamic method, which makes kL a estimation impossible. To address these limitations, in this work we present an improved dynamic method that consists of both an improved model and an improved procedure. The improved model takes into account the mass transfer between the headspace and the broth; in addition, nitrogen is bubbled through the broth when air is shut off. The improved method not only enables a faster and more accurate estimation of kL a, but also allows the measurement of kL a for high cell density with medium/low agitation that is impossible with the classical dynamic method. Scheffersomyces stipitis was used as the model system to demonstrate the effectiveness of the improved method; in addition, experiments were conducted to examine the effect of cell density and agitation speed on kL a.
© 2014 Wiley Periodicals, Inc.

Entities:  

Keywords:  bioreactors; dynamic method; kLa; mass transfer; oxygen transfer rate; oxygen utilization rate

Mesh:

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Year:  2014        PMID: 24838309     DOI: 10.1002/bit.25258

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  1 in total

1.  Two Experimental Protocols for Accurate Measurement of Gas Component Uptake and Production Rates in Bioconversion Processes.

Authors:  Kyle A Stone; Q Peter He; Jin Wang
Journal:  Sci Rep       Date:  2019-04-11       Impact factor: 4.379

  1 in total

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