Architected Design and Fabrication of Soft Mechanical Metamaterials

This study proposes a systematic design approach to 3D print soft mechanical metamaterials by tuning material flow behavior and using optimal toolpaths and print parameters. Planar printing tool paths, utilized in layer‐by‐layer printing such as fused deposition modeling (FDM) and prevalently used in most slicing algorithms, severely limit the realization of complex topologies required in metamaterials. Utilizing parametric design principles, the proposed approach employs discrete and continuous 3D freeform tool paths for supported and unsupported direct ink writing (DIW) of elastomeric structures. The resulting textured, soft topologies significantly enhance the performance of various mechanisms in soft robotics and impact energy‐absorbing wearable devices. Various bioinspired structures such as cilia, webs, leaf‐like structures, and lattices are explored using extrusion‐based silicone 3D printing, achieving features with high aspect ratios (L/D ≤ 12) without support. These complex structures are challenging to 3D print using conventional planar toolpaths. To demonstrate the enhanced functionalities enabled by these new topologies, cilia arrays added to suction cups increased the pull‐off forces by 18%. Additionally, 3D‐printed elastomeric lattice slabs used as energy‐absorbing structures reduced the maximum impact peak forces by 85%. Further functionalities, including magnetic, thermochromic, and signal transmission properties, are also showcased using functional soft mechanical metamaterials.

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Publication Details

Journal
Advanced Intelligent Systems
Published
2024-10-28
DOI
https://doi.org/10.1002/aisy.202400514
Citations
4
Primary Topic
Advanced Materials and Mechanics
Type
article
Field-Weighted Citation Impact
0.85

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article

Architected Design and Fabrication of Soft Mechanical Metamaterials

Arturo Castillo Ugalde, Aaron Chooi, Elgar Vikram Kanhere, Saikrishna Dontu et al.
4 citations
Advanced Intelligent Systems
Advanced Materials and Mechanics
0.85
article

Architected Design and Fabrication of Soft Mechanical Metamaterials

Arturo Castillo Ugalde, Aaron Chooi, Elgar Vikram Kanhere, Saikrishna Dontu, Naresh Kumar Thanigaivel, Pablo Valdivia y Alvarado, Thileepan Stalin, Gumawang Hiramandala, Aby Raj Plamootil Mathai
article en
4 citations

Abstract

This study proposes a systematic design approach to 3D print soft mechanical metamaterials by tuning material flow behavior and using optimal toolpaths and print parameters. Planar printing tool paths, utilized in layer‐by‐layer printing such as fused deposition modeling (FDM) and prevalently used in most slicing algorithms, severely limit the realization of complex topologies required in metamaterials. Utilizing parametric design principles, the proposed approach employs discrete and continuous 3D freeform tool paths for supported and unsupported direct ink writing (DIW) of elastomeric structures. The resulting textured, soft topologies significantly enhance the performance of various mechanisms in soft robotics and impact energy‐absorbing wearable devices. Various bioinspired structures such as cilia, webs, leaf‐like structures, and lattices are explored using extrusion‐based silicone 3D printing, achieving features with high aspect ratios (L/D ≤ 12) without support. These complex structures are challenging to 3D print using conventional planar toolpaths. To demonstrate the enhanced functionalities enabled by these new topologies, cilia arrays added to suction cups increased the pull‐off forces by 18%. Additionally, 3D‐printed elastomeric lattice slabs used as energy‐absorbing structures reduced the maximum impact peak forces by 85%. Further functionalities, including magnetic, thermochromic, and signal transmission properties, are also showcased using functional soft mechanical metamaterials.

Advanced Intelligent SystemsVol. 7(4)
Singapore University of Technology and Design (SG), Singapore-HUJ Alliance for Research and Enterprise (SG)
National Research Foundation Singapore
Openalex Percentile: Top 30%
Advanced Materials and Mechanics
0.85
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