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Contactless precision steering of particles in a fluid inside a cube with rotating walls

Published online by Cambridge University Press:  30 June 2025

Lucas Amoudruz Open the ORCID record for Lucas Amoudruz [Opens in a new window] ,
Petr Karnakov Open the ORCID record for Petr Karnakov [Opens in a new window]  and
Petros Koumoutsakos Open the ORCID record for Petros Koumoutsakos [Opens in a new window]
Lucas Amoudruz
Affiliation:
Computational Science and Engineering Laboratory, Harvard University, Cambridge, MA 02138, USA
Petr Karnakov
Affiliation:
Computational Science and Engineering Laboratory, Harvard University, Cambridge, MA 02138, USA
Petros Koumoutsakos*
Affiliation:
Computational Science and Engineering Laboratory, Harvard University, Cambridge, MA 02138, USA
*
Corresponding author: Petros Koumoutsakos, petros@seas.harvard.edu
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Abstract

Contactless manipulation of small objects is essential for biomedical and chemical applications, such as cell analysis, assisted fertilisation and precision chemistry. Established methods, including optical, acoustic and magnetic tweezers, are now complemented by flow control techniques that use flow-induced motion to enable precise and versatile manipulation. However, trapping multiple particles in fluid remains a challenge. This study introduces a novel control algorithm capable of steering multiple particles in flow. The system uses rotating disks to generate flow fields that transport particles to precise locations. Disk rotations are governed by a feedback control policy based on the optimising a discrete loss framework, which combines fluid dynamics equations with path objectives into a single loss function. Our experiments, conducted in both simulations and with the physical device, demonstrate the capability of the approach to transport two beads simultaneously to predefined locations, advancing robust contactless particle manipulation for biomedical applications.

JFM classification

Flow Control: Flow Control Low-Reynolds-number flows: Low-Reynolds-number flows Mathematical Foundations: Machine learning

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Type
JFM Papers
Information
Journal of Fluid Mechanics , Volume 1014 , 10 July 2025 , A15
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Copyright
© Harvard University, 2025. Published by Cambridge University Press

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Footnotes

†

Petr Karnakov and Lucas Amoudruz contributed equally.

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Supplementary material: File

Amoudruz et al. supplementary material movie 1

Two sinking beads in the robotic device. The control policy initially aims to keep the beads at their targets. The control policy is switched off and the beads sink due to gravity. Left, middle: view from the cameras, with tracking of individual beads. Right: three-dimensional reconstruction of the beads positions.
Download Amoudruz et al. supplementary material movie 1(File)
File 819.1 KB
Supplementary material: File

Amoudruz et al. supplementary material movie 2

Two beads swapping target positions in the robotic device. Left, middle: view from the cameras, with tracking of individual beads. Right: three-dimensional reconstruction of the beads positions.
Download Amoudruz et al. supplementary material movie 2(File)
File 2.2 MB
Supplementary material: File

Amoudruz et al. supplementary material movie 3

Two beads with rotating target positions in the robotic device. Left, middle: view from the cameras, with tracking of individual beads. Right: three-dimensional reconstruction of the beads positions.
Download Amoudruz et al. supplementary material movie 3(File)
File 4.3 MB