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Voxelated soft matter via multimaterial multinozzle 3D printing

Author

Listed:
  • Mark A. Skylar-Scott

    (Harvard University
    Harvard University)

  • Jochen Mueller

    (Harvard University
    Harvard University)

  • Claas W. Visser

    (Harvard University
    Harvard University)

  • Jennifer A. Lewis

    (Harvard University
    Harvard University)

Abstract

There is growing interest in voxelated matter that is designed and fabricated voxel by voxel1–4. Currently, inkjet-based three-dimensional (3D) printing is the only widely adopted method that is capable of creating 3D voxelated materials with high precision1–4, but the physics of droplet formation requires the use of low-viscosity inks to ensure successful printing5. By contrast, direct ink writing, an extrusion-based 3D printing method, is capable of patterning a much broader range of materials6–13. However, it is difficult to generate multimaterial voxelated matter by extruding monolithic cylindrical filaments in a layer-by-layer manner. Here we report the design and fabrication of voxelated soft matter using multimaterial multinozzle 3D (MM3D) printing, in which the composition, function and structure of the materials are programmed at the voxel scale. Our MM3D printheads exploit the diode-like behaviour that arises when multiple viscoelastic materials converge at a junction to enable seamless, high-frequency switching between up to eight different materials to create voxels with a volume approaching that of the nozzle diameter cubed. As exemplars, we fabricate a Miura origami pattern14 and a millipede-like soft robot that locomotes by co-printing multiple epoxy and silicone elastomer inks of stiffness varying by several orders of magnitude. Our method substantially broadens the palette of voxelated materials that can be designed and manufactured in complex motifs.

Suggested Citation

  • Mark A. Skylar-Scott & Jochen Mueller & Claas W. Visser & Jennifer A. Lewis, 2019. "Voxelated soft matter via multimaterial multinozzle 3D printing," Nature, Nature, vol. 575(7782), pages 330-335, November.
  • Handle: RePEc:nat:nature:v:575:y:2019:i:7782:d:10.1038_s41586-019-1736-8
    DOI: 10.1038/s41586-019-1736-8
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    Citations

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    Cited by:

    1. Zizheng Fang & Yunpeng Shi & Hongfeng Mu & Runzhi Lu & Jingjun Wu & Tao Xie, 2023. "3D printing of dynamic covalent polymer network with on-demand geometric and mechanical reprogrammability," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    2. Jianxiang Cheng & Rong Wang & Zechu Sun & Qingjiang Liu & Xiangnan He & Honggeng Li & Haitao Ye & Xingxin Yang & Xinfeng Wei & Zhenqing Li & Bingcong Jian & Weiwei Deng & Qi Ge, 2022. "Centrifugal multimaterial 3D printing of multifunctional heterogeneous objects," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    3. Yuxuan Sun & Liu Wang & Yangyang Ni & Huajian Zhang & Xiang Cui & Jiahao Li & Yinbo Zhu & Ji Liu & Shiwu Zhang & Yong Chen & Mujun Li, 2023. "3D printing of thermosets with diverse rheological and functional applicabilities," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    4. Sang-Joon Ahn & Howon Lee & Kyu-Jin Cho, 2024. "3D printing with a 3D printed digital material filament for programming functional gradients," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    5. Yue Zhang & Kangkang Liu & Tao Liu & Chujun Ni & Di Chen & Jiamei Guo & Chang Liu & Jian Zhou & Zheng Jia & Qian Zhao & Pengju Pan & Tao Xie, 2021. "Differential diffusion driven far-from-equilibrium shape-shifting of hydrogels," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    6. Liang Yue & S. Macrae Montgomery & Xiaohao Sun & Luxia Yu & Yuyang Song & Tsuyoshi Nomura & Masato Tanaka & H. Jerry Qi, 2023. "Single-vat single-cure grayscale digital light processing 3D printing of materials with large property difference and high stretchability," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    7. Bin Wang & Einstom Engay & Peter R. Stubbe & Saeed Z. Moghaddam & Esben Thormann & Kristoffer Almdal & Aminul Islam & Yi Yang, 2022. "Stiffness control in dual color tomographic volumetric 3D printing," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    8. Tie Mei & Chang Qing Chen, 2023. "In-memory mechanical computing," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    9. Yue Liu & Na Peng & Yifeng Yao & Xuan Zhang & Xianqi Peng & Liyan Zhao & Jing Wang & Liang Peng & Zuankai Wang & Kenji Mochizuki & Min Yue & Shikuan Yang, 2022. "Breaking the nanoparticle’s dispersible limit via rotatable surface ligands," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    10. Pei Zhang & Iek Man Lei & Guangda Chen & Jingsen Lin & Xingmei Chen & Jiajun Zhang & Chengcheng Cai & Xiangyu Liang & Ji Liu, 2022. "Integrated 3D printing of flexible electroluminescent devices and soft robots," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    11. Mohsen Habibi & Shervin Foroughi & Vahid Karamzadeh & Muthukumaran Packirisamy, 2022. "Direct sound printing," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    12. Kyle C. H. Chin & Grant Ovsepyan & Andrew J. Boydston, 2024. "Multi-color dual wavelength vat photopolymerization 3D printing via spatially controlled acidity," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    13. Huawei Qu & Chongjian Gao & Kaizheng Liu & Hongya Fu & Zhiyuan Liu & Paul H. J. Kouwer & Zhenyu Han & Changshun Ruan, 2024. "Gradient matters via filament diameter-adjustable 3D printing," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

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