Topology optimization and 3D printing of multimaterial magnetic actuators and displays
Name
eaaw1160.full.pdf
Description
Published version
Size
2.72 MB
Format
Adobe PDF
Checksum (MD5)
c1451f583a997b454fb896c42ef09e9b
Author(s)
Sundaram, Subramanian
Skouras, Melina
Kim, David Saerom
van den Heuvel, Louise
Matusik, Wojciech
Date Issued
July 2019
Journal
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Citation
Sundaram, Subramanian et al. "Topology optimization and 3D printing of multimaterial magnetic actuators and displays." Science Advances 5(2019): eaaw1160 © 2019 The Author(s)
Version
Final published version
Abstract
Upcoming actuation systems will be required to perform multiple tightly coupled functions analogous to their natural counterparts; e.g., the ability to control displacements and high-resolution appearance simultaneously is necessary for mimicking the camouflage seen in cuttlefish. Creating integrated actuation systems is challenging owing to the combined complexity of generating high-dimensional designs and developing multifunctional materials and their associated fabrication processes. Here, we present a complete toolkit consisting of multiobjective topology optimization (for design synthesis) and multimaterial drop-on-demand three-dimensional printing for fabricating complex actuators (>10⁶ design dimensions). The actuators consist of soft and rigid polymers and a magnetic nanoparticle/polymer composite that responds to a magnetic field. The topology optimizer assigns materials for individual voxels (volume elements) while simultaneously optimizing for physical deflection and high-resolution appearance. Unifying a topology optimization-based design strategy with a multimaterial fabrication process enables the creation of complex actuators and provides a promising route toward automated,goal-driven fabrication.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution NonCommercial License 4.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1126/sciadv.aaw1160
