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Hybrid 3D printing of bio-inspired artificial slowly adapting type II afferents

Author

Listed:
  • Mina Lee

    (Purdue University)

  • Michael Sotzing

    (Purdue University)

  • Jue Wang

    (Purdue University)

  • Alex Chortos

    (Purdue University)

Abstract

Neuromorphic sensory systems could provide low power consumption and direct electrical integration with biological systems. However, the complex fabrication of these multicomponent systems limits fabrication throughput and prototyping flexibility. To fabricate a slowly adapting type II artificial afferent nerve, this work introduces a hybrid direct write 3D printing approach that uses the pick and place of a surface mount ring oscillator to generate voltage pulses and an engineered quantum tunneling composite as a strain sensor. Our quantum tunneling sensor composition includes oil to increase the strain range and reduce the hysteresis compared to traditional quantum tunneling composites. The sensing composite provides a resistance change of over 6 orders of magnitude with a strain range of over 50%. Our approach enables rapid prototyping of 3D artificial sensory systems with potential applications in prosthetics and robotics.

Suggested Citation

  • Mina Lee & Michael Sotzing & Jue Wang & Alex Chortos, 2025. "Hybrid 3D printing of bio-inspired artificial slowly adapting type II afferents," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63470-7
    DOI: 10.1038/s41467-025-63470-7
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    References listed on IDEAS

    as
    1. Rui Yuan & Pek Jun Tiw & Lei Cai & Zhiyu Yang & Chang Liu & Teng Zhang & Chen Ge & Ru Huang & Yuchao Yang, 2023. "A neuromorphic physiological signal processing system based on VO2 memristor for next-generation human-machine interface," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Hongwei Tan & Quanzheng Tao & Ishan Pande & Sayani Majumdar & Fu Liu & Yifan Zhou & Per O. Å. Persson & Johanna Rosen & Sebastiaan van Dijken, 2020. "Tactile sensory coding and learning with bio-inspired optoelectronic spiking afferent nerves," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
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