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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

Maria Cecilia Barrera

Damien Leech

Aleksandar Josifovic

Anita Tolouei

Gareth Alford

Martin J. Wallace

Nicholas Bennett

Derek J. Irvine

Anna Croft

Alastair J. Florence

Blair Johnston

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