Parametric shape optimization of flagellated microswimmers using Bayesian techniques
Understanding and optimizing the design of helical microswimmers is crucial for advancing their application in various fields. This study integrates free-form deformation with Bayesian optimization to discover optimal shapes that optimize microswimmer speed and efficiency. Applied to both monoflagellated and biflagellated swimmers, the method revealed novel optimal designs, expanding the known diversity of pushers and pullers. These findings provide insights into bio-inspired locomotion and microscale propulsion
Authors
- Luca Berti (ORCID: https://orcid.org/0000-0001-9149-2271)
- Mickaël Binois (ORCID: https://orcid.org/0000-0002-7225-1680)
- Laëtitia Giraldi (ORCID: https://orcid.org/0000-0003-2684-0203)
- Lucas Palazzolo (ORCID: https://orcid.org/0009-0002-4188-014X)
Institutions
- Université Côte d'Azur (FR)
- Centre Inria d'Université Côte d'Azur (FR)
- Laboratoire Jean-Alexandre Dieudonné (FR)
- Institut de Recherche Mathématique Avancée (FR)
- Observatoire de la Côte d’Azur (FR)
- Université de Strasbourg (FR)
Publication Details
- Journal
- Physical Review Fluids
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1103/physrevfluids.10.034101
- Primary Topic
- Micro and Nano Robotics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Agence Nationale de la Recherche