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

BACKGROUND: 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...

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Autores principales: Loomba, Varun, Huber, Gregor, von Lieres, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5970501/
https://www.ncbi.nlm.nih.gov/pubmed/29849766
http://dx.doi.org/10.1186/s13068-018-1147-3
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author Loomba, Varun
Huber, Gregor
von Lieres, Eric
author_facet Loomba, Varun
Huber, Gregor
von Lieres, Eric
author_sort Loomba, Varun
collection PubMed
description BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. [Image: see text]
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spelling pubmed-59705012018-05-30 Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor Loomba, Varun Huber, Gregor von Lieres, Eric Biotechnol Biofuels Research BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. [Image: see text] BioMed Central 2018-05-26 /pmc/articles/PMC5970501/ /pubmed/29849766 http://dx.doi.org/10.1186/s13068-018-1147-3 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Loomba, Varun
Huber, Gregor
von Lieres, Eric
Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor
title Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor
title_full Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor
title_fullStr Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor
title_full_unstemmed Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor
title_short Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor
title_sort single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5970501/
https://www.ncbi.nlm.nih.gov/pubmed/29849766
http://dx.doi.org/10.1186/s13068-018-1147-3
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