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3D-Printable, Honeycomb-Inspired Tissue-Like Bioelectrodes for Patient-Specific Neural Interface

  • Marzia Momin
  • , Luyi Feng
  • , Xiaoai Chen
  • , Salahuddin Ahmed
  • , Basma AlMahmood
  • , Li Pang Huang
  • , Jiashu Ren
  • , Xinyi Wang
  • , Hyunjin Lee
  • , Samuel R. Cramer
  • , Nanyin Zhang
  • , Sulin Zhang
  • , Tao Zhou

Research output: Contribution to journalArticlepeer-review

Abstract

The unique gyral patterns of the human brain demand patient-specific neural interfaces to achieve precise neuromodulation, mitigate adverse tissue responses, and optimize therapeutic efficacy and safety. One-size-fits-all, conventional rigid electrocorticography (ECoG) electrodes, standardized for mass production through lithographic techniques, exhibit limited conformability to the brain's heterogeneous cortical topography. This mechanical mismatch results in poor electrode-tissue contact, signal loss, and foreign body responses. To address these limitations, we present an integrated novel platform, synergizing MRI-based anatomical mapping, finite element analysis (FEA)—optimized mechanical design, and direct ink writing (DIW) 3D printing to fabricate electrodes customized to individual gyral patterns. The resulting honeycomb-inspired printable gel electrode (HiPGE) employs a bioinspired honeycomb architecture with ultra-soft hydrogels, engineered to match the bending stiffness of brain tissue (0.1–10 kPa) while maintaining cost-efficiency and long-term durability. This mechanical congruence ensures exceptional cortical conformability and adaptive interfacing, circumventing the geometric and material limitations of traditional rigid electrodes. By combining patient-specific design with scalable fabrication, our platform establishes a transformative framework for neural interface engineering, enhancing precision, biocompatibility, and functional performance in neuromodulation therapies and neuroprosthetic applications.

Original languageEnglish (US)
Article numbere16291
JournalAdvanced Materials
Volume38
Issue number31
DOIs
StatePublished - Jun 2 2026

All Science Journal Classification (ASJC) codes

  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering

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