Taccola, S, da Veiga, T orcid.org/0000-0002-4286-4590, Chandler, JH orcid.org/0000-0001-9232-4966 et al. (3 more authors) (2022) Micro-scale aerosol jet printing of superparamagnetic Fe₃O₄ nanoparticle patterns. Scientific Reports, 12. 17931. ISSN 2045-2322
Abstract
The opportunity to create different patterns of magnetic nanoparticles on surfaces is highly desirable across many technological and biomedical applications. In this paper, this ability is demonstrated for the first time using a computer-controlled aerosol jet printing (AJP) technology. AJP is an emerging digitally driven, non-contact and mask-less printing process which has distinguishing advantages over other patterning technologies as it offers high-resolution and versatile direct-write deposition of a wide range of materials onto a variety of substrates. This research demonstrates the ability of AJP to reliably print large-area, fine-feature patterns of superparamagnetic iron oxide nanoparticles (SPIONs) onto both rigid material (glass) and soft and flexible materials (polydimethylsiloxane (PDMS) films and poly-L-lactic acid (PLLA) nanofilms). Investigation identified and controlled influential process variables which permitted feature sizes in the region of 20 μm to be realised. This method could be employed for a wide range of applications that require a flexible and responsive process that permits high yield and rapid patterning of magnetic material over large areas. As a first proof of concept, we present patterned magnetic nanofilms with enhanced manipulability under external magnetic field gradient control and which are capable of performing complex movements such as rotation and bending, with applicability to soft robotics and biomedical engineering applications.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Future Manufacturing Processes (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Physics and Astronomy (Leeds) > Condensed Matter (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/K00512X/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Jan 2023 16:04 |
Last Modified: | 27 Jan 2023 16:04 |
Status: | Published |
Publisher: | Nature Research |
Identification Number: | 10.1038/s41598-022-22312-y |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:195503 |