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Adaptive 3D printing of moldable conductive polymer composite for highly sensitive soft sensors with a broad working range
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  • Published: 08 January 2026

Adaptive 3D printing of moldable conductive polymer composite for highly sensitive soft sensors with a broad working range

  • Yuanhang Yang1,
  • Yuxuan Tang1,
  • Kai Xue2,3,
  • Junwei Li1,
  • Shun Duan4 &
  • …
  • Changjin Huang1 

npj Flexible Electronics , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

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  • Engineering
  • Materials for devices

Abstract

Conductive putty-like polymer composites have recently received considerable attention in wearable electronics, soft robotics, and energy storage due to their unique electrical and mechanical properties. Their viscoelasticity enables direct 3D printing of intricate, customizable conductive pathways, yet printing in high-viscosity polymer solutions remains challenging. Inspired by clay, we develop a moldable conductive polymer composite (MCPC) with tunable viscoelasticity, shear-thinning behavior, and high conductivity by blending liquid Ecoflex with graphite powders. By extruding MCPC onto liquid Ecoflex of various viscosities, we demonstrate a facile strategy for fabricating soft sensors with spatially controlled conductive pathways. These sensors exhibit a wide strain response (0.05%-150%), high sensitivity (gauge factor >15000), and nearly 100% electrical repeatability over 1000 cycles. They reliably monitor human movement and control robotic hands. Our approach provides a new strategy for fabricating soft sensors with enhanced mechanical and electrical properties, expanding possibilities for next-generation wearable and bio-integrated technologies.

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Data availability

The data that support the findings of this study are available from the corresponding author upon request.

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Acknowledgements

We would like to thank Haoyu Jiang for his help on the mechanical test. C.H. acknowledges financial support from Ministry of Education (MOE), Singapore, under its Academic Research Fund Tier 1 (RG74/23 and RG84/25) and Academic Research Fund Tier 2 (MOET2EP50121-0004).

Author information

Authors and Affiliations

  1. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore

    Yuanhang Yang, Yuxuan Tang, Junwei Li & Changjin Huang

  2. Centre of High Field NMR Spectroscopy and Imaging, Nanyang Technological University, Singapore, Singapore

    Kai Xue

  3. School of Physical and Mathematical Science, Nanyang Technological University, Singapore, Singapore

    Kai Xue

  4. Beijing Laboratory of Biomedical Materials, Beijing University of Chemical Technology, Beijing, China

    Shun Duan

Authors
  1. Yuanhang Yang
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Contributions

Y.Y.: Conceptualization, Methodology, Software, Data curation, Formal analysis, Writing–original draft. Y.T.: Simulation, Methodology. K.X.: Methodology, Data curation. J.L.: Methodology, Construction of test platform. S.D.: Conceptualization, Validation writing–review. C.H.: Conceptualization, Formal analysis, Supervision, Validation writing–review and editing, Funding acquisition.

Corresponding author

Correspondence to Changjin Huang.

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Competing interests

A Singapore provisional patent (application number: 10202502020W) was filed by Y.Y., Y.T. and C.H.

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Supplementary S1.

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Yang, Y., Tang, Y., Xue, K. et al. Adaptive 3D printing of moldable conductive polymer composite for highly sensitive soft sensors with a broad working range. npj Flex Electron (2026). https://doi.org/10.1038/s41528-025-00523-3

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  • Received: 07 April 2025

  • Accepted: 22 December 2025

  • Published: 08 January 2026

  • DOI: https://doi.org/10.1038/s41528-025-00523-3

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