Three-dimensional close-to-substrate trajectories of magnetic microparticles in dynamically changing magnetic field landscapes.

Magnetic Fields Physical Phenomena Cell-Derived Microparticles Motion Lab-On-A-Chip Devices

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
03 12 2022
Historique:
received: 08 09 2022
accepted: 29 11 2022
entrez: 3 12 2022
pubmed: 4 12 2022
medline: 7 12 2022
Statut: epublish

Résumé

The transport of magnetic particles (MPs) by dynamic magnetic field landscapes (MFLs) using magnetically patterned substrates is promising for the development of Lab-on-a-chip (LOC) systems. The inherent close-to-substrate MP motion is sensitive to changing particle-substrate interactions. Thus, the detection of a modified particle-substrate separation distance caused by surface binding of an analyte is expected to be a promising probe in analytics and diagnostics. Here, we present an essential prerequisite for such an application, namely the label-free quantitative experimental determination of the three-dimensional trajectories of superparamagnetic particles (SPPs) transported by a dynamically changing MFL. The evaluation of defocused SPP images from optical bright-field microscopy revealed a "hopping"-like motion of the magnetic particles, previously predicted by theory, additionally allowing a quantification of maximum jump heights. As our findings pave the way towards precise determination of particle-substrate separations, they bear deep implications for future LOC detection schemes using only optical microscopy.

Identifiants

DOI: 10.1038/s41598-022-25391-z PMID: 36463293 PMC: PMC9719552
pubmed: 36463293
doi: 10.1038/s41598-022-25391-z
pii: 10.1038/s41598-022-25391-z
pmc: PMC9719552
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

20890

Informations de copyright

© 2022. The Author(s).

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Auteurs

Rico Huhnstock (R)

Institute of Physics and Center for Interdisciplinary Nanostructure Science and Technology (CINSaT), University of Kassel, Heinrich-Plett-Strasse 40, 34132, Kassel, Germany. rico.huhnstock@physik.uni-kassel.de.
Artificial Intelligence Methods for Experiment Design (AIM-ED), Joint Lab of Helmholtzzentrum für Materialien und Energie, Berlin (HZB) and University of Kassel, Hahn-Meitner-Platz 1, 14109, Berlin, Germany. rico.huhnstock@physik.uni-kassel.de.

Meike Reginka (M)

Institute of Physics and Center for Interdisciplinary Nanostructure Science and Technology (CINSaT), University of Kassel, Heinrich-Plett-Strasse 40, 34132, Kassel, Germany.

Claudius Sonntag (C)

Intelligent Embedded Systems, University of Kassel, Wilhelmshöher Allee 71-73, 34121, Kassel, Germany.

Maximilian Merkel (M)

Institute of Physics and Center for Interdisciplinary Nanostructure Science and Technology (CINSaT), University of Kassel, Heinrich-Plett-Strasse 40, 34132, Kassel, Germany.
Artificial Intelligence Methods for Experiment Design (AIM-ED), Joint Lab of Helmholtzzentrum für Materialien und Energie, Berlin (HZB) and University of Kassel, Hahn-Meitner-Platz 1, 14109, Berlin, Germany.

Kristina Dingel (K)

Artificial Intelligence Methods for Experiment Design (AIM-ED), Joint Lab of Helmholtzzentrum für Materialien und Energie, Berlin (HZB) and University of Kassel, Hahn-Meitner-Platz 1, 14109, Berlin, Germany.
Intelligent Embedded Systems, University of Kassel, Wilhelmshöher Allee 71-73, 34121, Kassel, Germany.

Bernhard Sick (B)

Artificial Intelligence Methods for Experiment Design (AIM-ED), Joint Lab of Helmholtzzentrum für Materialien und Energie, Berlin (HZB) and University of Kassel, Hahn-Meitner-Platz 1, 14109, Berlin, Germany.
Intelligent Embedded Systems, University of Kassel, Wilhelmshöher Allee 71-73, 34121, Kassel, Germany.

Michael Vogel (M)

Institute of Physics and Center for Interdisciplinary Nanostructure Science and Technology (CINSaT), University of Kassel, Heinrich-Plett-Strasse 40, 34132, Kassel, Germany.
Artificial Intelligence Methods for Experiment Design (AIM-ED), Joint Lab of Helmholtzzentrum für Materialien und Energie, Berlin (HZB) and University of Kassel, Hahn-Meitner-Platz 1, 14109, Berlin, Germany.
Institute for Materials Science, Kiel University, Kaiserstraße 2, 24143, Kiel, Germany.

Arno Ehresmann (A)

Institute of Physics and Center for Interdisciplinary Nanostructure Science and Technology (CINSaT), University of Kassel, Heinrich-Plett-Strasse 40, 34132, Kassel, Germany. ehresmann@physik.uni-kassel.de.
Artificial Intelligence Methods for Experiment Design (AIM-ED), Joint Lab of Helmholtzzentrum für Materialien und Energie, Berlin (HZB) and University of Kassel, Hahn-Meitner-Platz 1, 14109, Berlin, Germany. ehresmann@physik.uni-kassel.de.

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Classifications MeSH

questionsmedicales.fr › Phénomènes physiques › Phénomènes magnétiques › Champs magnétiques › Three-dimensional close-to-substrate...
questionsmedicales.fr › Phénomènes physiques › Three-dimensional close-to-substrate...
questionsmedicales.fr › Cellules › Structures cellulaires › Espace extracellulaire › Vésicules extracellulaires › Microparticules membranaires › Three-dimensional close-to-substrate...
questionsmedicales.fr › Phénomènes physiques › Déplacement › Three-dimensional close-to-substrate...
questionsmedicales.fr › Équipement et fournitures › Équipement et fournitures électriques › Laboratoires sur puces › Three-dimensional close-to-substrate...