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Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor

Overview of attention for article published in Biotechnology for Biofuels and Bioproducts, May 2018
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Title
Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor
Published in
Biotechnology for Biofuels and Bioproducts, May 2018
DOI 10.1186/s13068-018-1147-3
Pubmed ID
Authors

Varun Loomba, Gregor Huber, Eric von Lieres

Abstract

Flat-panel photo-bioreactors (PBRs) are customarily applied for investigating growth of microalgae. Optimal design and operation of such reactors is still a challenge due to complex non-linear combinations of various impact factors, particularly hydrodynamics, light irradiation, and cell metabolism. A detailed analysis of single-cell light reception can lead to novel insights into the complex interactions of light exposure and algae movement in the reactor. The combined impacts of hydrodynamics and light irradiation on algae cultivation in a flat-panel PBR were studied by tracing the light exposure of individual cells over time. Hydrodynamics and turbulent mixing in this air-sparged bioreactor were simulated using the Eulerian approach for the liquid phase and a slip model for the gas phase velocity profiles. The liquid velocity was then used for tracing single cells and their light exposure, using light intensity profiles obtained from solving the radiative transfer equation at different wavelengths. The residence times of algae cells in defined dark and light zones of the PBR were statistically analyzed for different algal concentrations and sparging rates. The results indicate poor mixing caused by the reactor design which can be only partially improved by increased sparging rates. The results provide important information for optimizing algal biomass productivity by improving bioreactor design and operation and can further be utilized for an in-depth analysis of algal growth by using advanced models of cell metabolism.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 17%
Student > Master 8 14%
Researcher 7 12%
Student > Doctoral Student 5 9%
Student > Bachelor 4 7%
Other 9 16%
Unknown 15 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 17%
Chemical Engineering 8 14%
Biochemistry, Genetics and Molecular Biology 6 10%
Engineering 6 10%
Energy 3 5%
Other 6 10%
Unknown 19 33%