ArticleComputational and structural biotechnology journal2024
Magnetic control of soft microrobots near step-out frequency: Characterization and analysis.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Sharp nanothorn-equipped ionogel microrobots for targeted periodontitis therapy.Science advances · 2026Article
- Liquid Crystal Polymers as Intrinsically Magnetic and Programmable Soft Materials for Microrobotics.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- MicroRoboScope: A Portable and Integrated Mechatronic Platform for Magnetic and Acoustic Microrobotic Experimentation.Advanced robotics research · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Magnetically actuated soft microrobots hold promise for biomedical applications that necessitate precise control and adaptability in complex environments. These microrobots can be accurately steered below their step-out frequencies where they exhibit synchronized motion with external magnetic fields. However, the step-out frequencies of soft microrobots have not been investigated yet, as opposed to their rigid counterparts. In this work, we develop an analytic model from the magneto-elastohydrodynamics to establish the relationship between the step-out frequency of soft sperm-like microrobots and their magnetic properties, geometry, wave patterns, and the viscosity of the surrounding medium. We fabricate soft sperm-like microrobots using electrospinning and assess their swimming abilities in mediums with varying viscosities under an oscillating magnetic field. We observe slight variations in wave patterns of the sperm-like microrobots as the actuation frequency changes. Our theoretical model, which analyzes these wave patterns observed without exceeding the step-out threshold, quantitatively agrees with the experimentally measured step-out frequencies. By accurately predicting the step-out frequency, the proposed model lays a foundation for achieving precise control over individual soft microrobots and enabling selective control within a swarm when executing biomedical tasks.
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