Maria Cecilia Barrera
Optimisation of additively manufactured coiled flow inverters for continuous viral inactivation processes
Barrera, Maria Cecilia; Leech, Damien; Josifovic, Aleksandar; Tolouei, Anita; Alford, Gareth; Wallace, Martin J.; Bennett, Nicholas; Wildman, Ricky; Irvine, Derek J.; Croft, Anna; Özcan, Ender; Florence, Alastair J.; Johnston, Blair; Robertson, John; Brown, Cameron J.
Authors
Damien Leech
Aleksandar Josifovic
Anita Tolouei
Gareth Alford
Martin J. Wallace
Nicholas Bennett
Professor RICKY WILDMAN RICKY.WILDMAN@NOTTINGHAM.AC.UK
PROFESSOR OF MULTIPHASE FLOW AND MECHANICS
Derek J. Irvine
Anna Croft
Professor Ender Ozcan ender.ozcan@nottingham.ac.uk
PROFESSOR OF COMPUTER SCIENCE AND OPERATIONAL RESEARCH
Alastair J. Florence
Blair Johnston
Professor JOHN ROBERTSON john.robertson@nottingham.ac.uk
PROFESSOR OF SURGERY
Cameron J. Brown
Abstract
This article reports the development and utilisation of an adaptive design workflow methodology for use as a platform technology for the printing, testing, and optimisation of biopharmaceutical processing reactors. This design strategy was developed by application to the complex structure of the coiled flow inverter (CFI). In this way, the many possible physical parameters of the reactor were optimised, via a combination of experimental results, computational fluid dynamics and machine learning approaches, to find the CFI setups that provide the optimal flow properties for a particular application.
Additively manufactured reactors are seeing increasing interest in the field of biopharmaceutical production. This is because the desired output volumes are typically small and there is an increasing move towards adopting continuous production, to replace traditional batch production. This approach allows for the tailoring of reactors for a specific reaction, i.e. attempting to maximise the desired aspects of the reaction through refinement of the physical parameters of the reactor, so creating a large possible parameter space to explore.
Consequently, the holistic optimisation of CFI reactors and 3D printing is established as providing better plug flow mixing relative to traditional tube coiled reactors. In addition, a trained metamodel in combination with multilayer equations is demonstrated to predict reactor performance quickly and accurately.
Citation
Barrera, M. C., Leech, D., Josifovic, A., Tolouei, A., Alford, G., Wallace, M. J., Bennett, N., Wildman, R., Irvine, D. J., Croft, A., Özcan, E., Florence, A. J., Johnston, B., Robertson, J., & Brown, C. J. (2025). Optimisation of additively manufactured coiled flow inverters for continuous viral inactivation processes. Chemical Engineering Research and Design, 213, 126-136. https://doi.org/10.1016/j.cherd.2024.11.040
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 29, 2024 |
Online Publication Date | Nov 30, 2024 |
Publication Date | Jan 1, 2025 |
Deposit Date | Dec 2, 2024 |
Publicly Available Date | Dec 1, 2025 |
Journal | Chemical Engineering Research and Design |
Print ISSN | 0263-8762 |
Electronic ISSN | 1744-3563 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 213 |
Pages | 126-136 |
DOI | https://doi.org/10.1016/j.cherd.2024.11.040 |
Keywords | additive manufacturing; coiled flow inverter; continuous viral inactivation; computational fluid dynamics; machine learning |
Public URL | https://nottingham-repository.worktribe.com/output/42787291 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S0263876224006713?via%3Dihub |
Files
This file is under embargo until Dec 1, 2025 due to copyright restrictions.
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