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Evaluating and forecasting movement patterns of magnetically driven microbeads in complex geometries.

ABSTRACT: The manipulation of superparamagnetic microbeads for lab-on-a-chip applications relies on the steering of microbeads across an altering stray field landscape on top of soft magnetic parent structures. Using ab initio principles, we show three-dimensional simulations forecasting the controlled movement of microbeads. Simulated aspects of microbead behaviour include the looping and lifting of microbeads around a magnetic circular structure, the flexible bead movement along symmetrically distributed triangular structures, and the dragging of magnetic beads across an array of exchange biased magnetic microstripes. The unidirectional motion of microbeads across a string of oval elements is predicted by simulations and validated experimentally. Each of the simulations matches the experimental results, proving the robustness and accuracy of the applied numerical method. The computer experiments provide details on the particle motion not accessible by experiments. The simulation capabilities prove to be an essential part for the estimation of future lab-on-chip designs.

SUBMITTER: Klingbeil F

PROVIDER: S-EPMC7260204 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Evaluating and forecasting movement patterns of magnetically driven microbeads in complex geometries.

Klingbeil Finn F Block Findan F Sajjad Umer U Holländer Rasmus B RB Deshpande Sughosh S McCord Jeffrey J

Scientific reports 20200529 1

The manipulation of superparamagnetic microbeads for lab-on-a-chip applications relies on the steering of microbeads across an altering stray field landscape on top of soft magnetic parent structures. Using ab initio principles, we show three-dimensional simulations forecasting the controlled movement of microbeads. Simulated aspects of microbead behaviour include the looping and lifting of microbeads around a magnetic circular structure, the flexible bead movement along symmetrically distribute ...[more]

PMID: 32472020

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Project description:Human movements show several prominent features; movement duration is nearly independent of movement size (the isochrony principle), instantaneous speed depends on movement curvature (captured by the 2/3 power law), and complex movements are composed of simpler elements (movement compositionality). No existing theory can successfully account for all of these features, and the nature of the underlying motion primitives is still unknown. Also unknown is how the brain selects movement duration. Here we present a new theory of movement timing based on geometrical invariance. We propose that movement duration and compositionality arise from cooperation among Euclidian, equi-affine and full affine geometries. Each geometry posses a canonical measure of distance along curves, an invariant arc-length parameter. We suggest that for continuous movements, the actual movement duration reflects a particular tensorial mixture of these canonical parameters. Near geometrical singularities, specific combinations are selected to compensate for time expansion or compression in individual parameters. The theory was mathematically formulated using Cartan's moving frame method. Its predictions were tested on three data sets: drawings of elliptical curves, locomotion and drawing trajectories of complex figural forms (cloverleaves, lemniscates and limaçons, with varying ratios between the sizes of the large versus the small loops). Our theory accounted well for the kinematic and temporal features of these movements, in most cases better than the constrained Minimum Jerk model, even when taking into account the number of estimated free parameters. During both drawing and locomotion equi-affine geometry was the most dominant geometry, with affine geometry second most important during drawing; Euclidian geometry was second most important during locomotion. We further discuss the implications of this theory: the origin of the dominance of equi-affine geometry, the possibility that the brain uses different mixtures of these geometries to encode movement duration and speed, and the ontogeny of such representations.

Dataset Information

Evaluating and forecasting movement patterns of magnetically driven microbeads in complex geometries.

Publications

Evaluating and forecasting movement patterns of magnetically driven microbeads in complex geometries.

Similar Datasets

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