Bioprocess Modelling of Biohydrogen Production by Rhodopseudomonas palustris: Model Development and Effects of Operating Conditions on Hydrogen Yield and Glycerol Conversion Efficiency
Chemical Engineering Science
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Zhang, D., Xiao, N., Mahbubani, K., del, R. E., Slater, N., & Vassiliadis, V. (2015). Bioprocess Modelling of Biohydrogen Production by Rhodopseudomonas palustris: Model Development and Effects of Operating Conditions on Hydrogen Yield and Glycerol Conversion Efficiency. Chemical Engineering Science, 130 68-78. https://doi.org/10.1016/j.ces.2015.02.045
This research explores the photofermentation of glycerol to hydrogen by Rhodopseudomonas palus- tris, with the objective to maximise hydrogen production. Two piecewise models are designed to simulate the entire growth phase of R. palustris; a challenge that few dynamic models can accomplish. The parameters in both models were fitted by the present batch experiments through the solution of the underlying optimal control problems by means of stable and accurate discretisation techniques. It was found that an initial glutamate to glycerol ratio of 0.25 was optimal, and was independent of the initial biomass concentration. The glycerol conversion efficiency was found to depend on initial biomass concentration and its computational peak is 64.4%. By optimising a 30-day industrially relevant batch process, the hydrogen productivity was improved to be 37.7 mL·g biomass-1·hr-1 and the glycerol conversion efficiency was maintained at 58%. The models can then be applied as the connection to transfer biohydrogen production from laboratory scale into industrial scale.
purple non-sulphur bacteria, photofermentation, dynamic simulation, process optimisation, discretisation
Authors N. Xiao and Dr. K. T. Mahbubani are funded through the KACST-Cambridge Center for Advanced Material Manufacture, the author E. A. del Rio-Chanona is found by CONACyT scholarship No. 522530 from the Secretariat of Public Education and the Mexican government.
King Abdulaziz City for Science and Technology (KACST) (unknown)
External DOI: https://doi.org/10.1016/j.ces.2015.02.045
This record's URL: https://www.repository.cam.ac.uk/handle/1810/247752
Attribution-NonCommercial-NoDerivs 2.0 UK: England & Wales
Licence URL: http://creativecommons.org/licenses/by-nc-nd/2.0/uk/
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