Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-10847
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dc.contributor.authorSiebler, Flora-
dc.date.accessioned2020-05-12T07:45:51Z-
dc.date.available2020-05-12T07:45:51Z-
dc.date.issued2020de
dc.identifier.other1698020449-
dc.identifier.urihttp://elib.uni-stuttgart.de/handle/11682/10864-
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-108642de
dc.identifier.urihttp://dx.doi.org/10.18419/opus-10847-
dc.description.abstractThe reduction of greenhouse gas emissions is a global endeavour supported by society, politics and industry. In recent years, circular economy, reducing the exploitation of fossil energy sources, have increased the demand for new solutions when producing commodities and fine chemicals. Caboxydotrophic fermentations with acetogenic bacteria are potential processes in order to reach these goals. They convert gaseous substrates such as CO, and CO2/H2 mixtures. However, gases as sole substrate are rather challenging, not only in small lab-scales but especially in large-scale. Transferring an efficient fermentation process from experimental to industrial scales often results in unpredictable performance losses. This study presents an in silico concept minimising possible risks in gas fermentations up-scaling. First, the economical feasibility of various fermentation methods is investigated. Then, two computational tools are presented using Clostridium ljungdahlii as model organism and synthesis gas as substrate in a 125 m3 bubble column reactor. The combination of economical investigation with modelling tools show high potential for successful scale-up of gas fermentations. With this concept feasibility, reactor design, operation mode and general risk minimisation can be analysed and specified.en
dc.language.isoende
dc.rightsinfo:eu-repo/semantics/openAccessde
dc.subject.ddc333.7de
dc.subject.ddc500de
dc.subject.ddc530de
dc.subject.ddc540de
dc.subject.ddc570de
dc.subject.ddc620de
dc.titleScale-up of gas fermentations : modelling tools for risk minimisationen
dc.typedoctoralThesisde
ubs.dateAccepted2020-03-06-
ubs.fakultaetEnergie-, Verfahrens- und Biotechnikde
ubs.institutInstitut für Bioverfahrenstechnikde
ubs.publikation.typDissertationde
ubs.thesis.grantorEnergie-, Verfahrens- und Biotechnikde
Appears in Collections:04 Fakultät Energie-, Verfahrens- und Biotechnik

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