Review of advanced physical and data‐driven models for dynamic bioprocess simulation: Case study of algae–bacteria consortium wastewater treatment-Reference-Cited by-同舟云学术

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Review of advanced physical and data‐driven models for dynamic bioprocess simulation: Case study of algae–bacteria consortium wastewater treatment

Published:2018-12-14 Issue:2 Volume:116 Page:342-353
ISSN:0006-3592
Container-title:Biotechnology and Bioengineering
language:en
Short-container-title:Biotechnology and Bioengineering

Author:

Del Rio‐Chanona Ehecatl Antonio¹^ORCID,Cong Xiaoyan²,Bradford Eric³,Zhang Dongda¹⁴^ORCID,Jing Keju²

Affiliation:

1. Centre for Process Systems Engineering, Imperial College London, South Kensington CampusLondon United Kingdom

2. Department of Chemical and Biochemical EngineeringCollege of Chemistry and Chemical Engineering, Xiamen UniversityXiamen China

3. Engineering Cybernetics, Norwegian University of Science and TechnologyTrondheim Norway

4. Centre for Process Integration, University of Manchester, Oxford RoadManchester United Kingdom

Funder

Engineering and Physical Sciences Research Council

National Natural Science Foundation of China

Publisher

Wiley

Subject

Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/bit.26881

Reference32 articles.

1. Kinetic modelling of growth and storage molecule production in microalgae under mixotrophic and autotrophic conditions

2. Empirical predictive modelling of poly-ɛ-lysine biosynthesis in resting cells of Streptomyces noursei

3. Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes

4. Kinetic modeling and process analysis for Desmodesmus sp. lutein photo-production

5. An efficient model construction strategy to simulate microalgal lutein photo-production dynamic process

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