Evidence map›Paper›PMID 41830336›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2026

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 and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Marzia MominDepartment of Engineering Science and Mechanics, The Pennsylvania State University, University Park, Pennsylvania, USA.
Luyi FengDepartment of Engineering Science and Mechanics, The Pennsylvania State University, University Park, Pennsylvania, USA.
Xiaoai ChenDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA.
Salahuddin AhmedDepartment of Engineering Science and Mechanics, The Pennsylvania State University, University Park, Pennsylvania, USA.
Basma AlMahmoodDepartment of Physics, The Pennsylvania State University, University Park, Pennsylvania, USA.
Li-Pang HuangDepartment of Biology, The Pennsylvania State University, University Park, Pennsylvania, USA.
Jiashu RenDepartment of Engineering Science and Mechanics, The Pennsylvania State University, University Park, Pennsylvania, USA.
Xinyi WangDepartment of Mechanical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA.
Hyunjin LeeDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA.
Samuel R CramerDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA.
Nanyin ZhangDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA.
Sulin ZhangDepartment of Engineering Science and Mechanics, The Pennsylvania State University, University Park, Pennsylvania, USA.
Tao ZhouDepartment of Engineering Science and Mechanics, The Pennsylvania State University, University Park, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-6507-8912

Funding

3D Printed Soft and Stretchable Tissue-Like Bioadhesive Electronic Device Enabled Neuromodulation for Resistant Hypertension TherapyR01HL171633 · NHLBI · PENNSYLVANIA STATE UNIVERSITY, THE · PI Tao Zhou · 2024 to 2026
$1.1M
National Science FoundationNational Taipei University of Technology-Penn State Collaborative Seed Grant Program NTUT-PSU-113-01NHLBI NIH HHS R01 HL171633NIH HHS 1R01HL171633
6 · The paper itself

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.

Indexed as

Biomimetic MaterialsBrain-Computer InterfacesPrinting, Three-DimensionalBrainElectrocorticographyElectrodesFinite Element AnalysisHumansHydrogelsMagnetic Resonance ImagingHydrogels3D printingbioinspiredbrain‐computer interfaceECoGneural interfacepatient‐specificsoft electrodes

Identifiers

PMID41830336
PMCPMC13016203

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.