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dc.contributor.author
Wang, Qianqian
dc.contributor.author
Chan, Kai F.
dc.contributor.author
Schweizer, Kathrin
dc.contributor.author
Du, Xingzhou
dc.contributor.author
Jin, Dongdong
dc.contributor.author
Yu, Simon C.H.
dc.contributor.author
Nelson, Bradley J.
dc.contributor.author
Zhang, Li
dc.date.accessioned
2021-03-15T10:57:22Z
dc.date.available
2021-03-13T04:31:48Z
dc.date.available
2021-03-15T10:57:22Z
dc.date.issued
2021-02-24
dc.identifier.issn
2375-2548
dc.identifier.other
10.1126/sciadv.abe5914
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/474223
dc.identifier.doi
10.3929/ethz-b-000474223
dc.description.abstract
Swarming micro/nanorobots offer great promise in performing targeted delivery inside diverse hard-to-reach environments. However, swarm navigation in dynamic environments challenges delivery capability and real-time swarm localization. Here, we report a strategy to navigate a nanoparticle microswarm in real time under ultrasound Doppler imaging guidance for active endovascular delivery. A magnetic microswarm was formed and navigated near the boundary of vessels, where the reduced drag of blood flow and strong interactions between nanoparticles enable upstream and downstream navigation in flowing blood (mean velocity up to 40.8 mm/s). The microswarm-induced three-dimensional blood flow enables Doppler imaging from multiple viewing configurations and real-time tracking in different environments (i.e., stagnant, flowing blood, and pulsatile flow). We also demonstrate the ultrasound Doppler–guided swarm formation and navigation in the porcine coronary artery ex vivo. Our strategy presents a promising connection between swarm control and real-time imaging of microrobotic swarms for localized delivery in dynamic environments.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
AAAS
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc/4.0/
dc.title
Ultrasound Doppler-guided real-time navigation of a magnetic microswarm for active endovascular delivery
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial 4.0 International
dc.date.published
2021-02-26
ethz.journal.title
Science Advances
ethz.journal.volume
7
en_US
ethz.journal.issue
9
en_US
ethz.journal.abbreviated
Sci Adv
ethz.pages.start
eabe5914
en_US
ethz.size
13 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Washington, DC
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::03627 - Nelson, Bradley J. / Nelson, Bradley J.
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::03627 - Nelson, Bradley J. / Nelson, Bradley J.
ethz.date.deposited
2021-03-13T04:32:09Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-03-15T10:57:32Z
ethz.rosetta.lastUpdated
2022-03-29T05:46:20Z
ethz.rosetta.versionExported
true
ethz.COinS
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