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Photocatalytic production of bisabolene from green microalgae mutant: process analysis and kinetic modeling

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journal contribution
posted on 05.12.2018 by Irina Harun, Ehecatl Antonio del Rio-Chanona, Jonathan Wagner, Kyle J. Lauersen, Dongda Zhang, Klaus Hellgardt
Currently, algal fuel research has commenced to shift toward genetically engineered mutants able to express and excrete desired products directly into the culture. In this study, a mutant strain of Chlamydomonas reinhardtii, engineered for bisabolene (alternative biodiesel) excretion, was cultivated at different illumination and temperatures to investigate their effects on cell growth and bisabolene production. Moreover, a kinetic model was constructed to identify the desirable conditions for biofuel synthesis. Three original contributions were concluded. First, this work confirmed that bisabolene was partially synthesized independently of biomass growth, indicating its feasibility for continuous production. Second, it was found that while bisabolene synthesis was independent of light intensity, it was strongly affected by temperature, resulting in conflicting desirable conditions for cell growth and product synthesis. Finally, through model prediction, optimal operating conditions were identified for mutant growth and bisabolene synthesis. This study therefore paves the way toward chemostat production and process scale-up.

Funding

This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 640720. This project also received funding from the EPSRC project (EP/P016650/1, P65332). I.H. acknowledges funding from the Ministry of Higher Education, Malaysia and University Putra Malaysia.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Chemical Engineering

Published in

Industrial & Engineering Chemistry Research

Citation

HARUN, I. ... et al, 2018. Photocatalytic production of bisabolene from green microalgae mutant: process analysis and kinetic modeling. Industrial & Engineering Chemistry Research, 57 (31), pp.10336–10344.

Publisher

© American Chemical Society

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

03/07/2018

Publication date

2018-07-05

Notes

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Industrial & Engineering Chemistry Research, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://pubs.acs.org/doi/10.1021/acs.iecr.8b02509.

ISSN

0888-5885

Language

en

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