Thermoset Shape Memory Polymer Variable Stiffness 4D Robotic Catheters.

catheters composite materials shape memory polymers thermoset polymers variable stiffness

Journal

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
ISSN: 2198-3844
Titre abrégé: Adv Sci (Weinh)
Pays: Germany
ID NLM: 101664569

Informations de publication

Date de publication:
01 2022
Historique:
received: 02 08 2021
pubmed: 2 11 2021
medline: 15 3 2022
entrez: 1 11 2021
Statut: ppublish

Résumé

Variable stiffness catheters are typically composed of an encapsulated core. The core is usually composed of a low melting point alloy (LMPA) or a thermoplastic polymer (TP). In both cases, there is a need to encapsulate the core with an elastic material. This imposes a limit to the volume of variable stiffness (VS) material and limits miniaturization. This paper proposes a new approach that relies on the use of thermosetting materials. The variable stiffness catheter (VSC) proposed in this work eliminates the necessity for an encapsulation layer and is made of a unique biocompatible thermoset polymer with an embedded heating system. This significantly reduces the final diameter, improves manufacturability, and increases safety in the event of complications. The device can be scaled to sub-millimeter dimensions, while maintaining a high stiffness change. In addition, integration into a magnetic actuation system allows for precise actuation of one or multiple tools.

Identifiants

pubmed: 34723442
doi: 10.1002/advs.202103277
pmc: PMC8728812
doi:

Substances chimiques

Smart Materials 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2103277

Subventions

Organisme : European Research Council
ID : 743217
Pays : International
Organisme : European Research Council
ID : 771565
Pays : International

Informations de copyright

© 2021 The Authors. Advanced Science published by Wiley-VCH GmbH.

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Auteurs

Michael Mattmann (M)

Institute of Robotics and Intelligent Systems, ETH Zürich, Tannenstrasse 3, Zurich, CH-8092, Switzerland.

Carmela De Marco (C)

Institute of Robotics and Intelligent Systems, ETH Zürich, Tannenstrasse 3, Zurich, CH-8092, Switzerland.

Francesco Briatico (F)

Department of Chemistry, Materials and Chemical Engineering, Politecnico di Milano, Milan, 20131, Italy.

Stefano Tagliabue (S)

Department of Chemistry, Materials and Chemical Engineering, Politecnico di Milano, Milan, 20131, Italy.

Aron Colusso (A)

Institute of Robotics and Intelligent Systems, ETH Zürich, Tannenstrasse 3, Zurich, CH-8092, Switzerland.

Xiang-Zhong Chen (XZ)

Institute of Robotics and Intelligent Systems, ETH Zürich, Tannenstrasse 3, Zurich, CH-8092, Switzerland.

Jonas Lussi (J)

Institute of Robotics and Intelligent Systems, ETH Zürich, Tannenstrasse 3, Zurich, CH-8092, Switzerland.

Christophe Chautems (C)

Institute of Robotics and Intelligent Systems, ETH Zürich, Tannenstrasse 3, Zurich, CH-8092, Switzerland.

Salvador Pané (S)

Institute of Robotics and Intelligent Systems, ETH Zürich, Tannenstrasse 3, Zurich, CH-8092, Switzerland.

Bradley Nelson (B)

Institute of Robotics and Intelligent Systems, ETH Zürich, Tannenstrasse 3, Zurich, CH-8092, Switzerland.

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Classifications MeSH