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Electronics with switchable flexibility for 3D conforming neural interfaces
Xingdao He1, Matthew Chamberlin1, Zhaoqi Chen2
1Department of Biomedical Engineering, College of Biomedicine, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China.
Science Advances
|June 19, 2026
Summary
Researchers developed sFlex-Fold, a novel bioelectronic system for brain-computer interfaces. This system offers nonpenetrative, 3D access to neural information within complex cortical folds, overcoming previous limitations.
Area of Science:
- Bioelectronic systems
- Neuroscience
- Materials science
Background:
- Cortical folds in large primates limit neural information access by current interface devices.
- Existing neural interfaces struggle with nonpenetrative, deep tissue coverage of complex brain structures.
Purpose of the Study:
- To develop a novel bioelectronic system, sFlex-Fold, for nonpenetrative, 3D neural interfacing.
- To enable large-area coverage of both gyri and sulci within the brain's intricate folds.
- To achieve tissue-matching mechanical compliance for high-quality neural signal acquisition.
Main Methods:
- Designed a switchable flexibility bioelectronic system using an AI-designed liquid metal alloy (LM-alloy).
- Leveraged the phase change of the LM-alloy around 36.2°C for tunable mechanical response.
- Patterned the LM-alloy with ~10-micrometer resolution for intricate circuit layouts.
- Demonstrated nondestructive implantation and large-area coverage (>80 cm²) in rodent and porcine models.
Main Results:
- sFlex-Fold exhibits switchable flexibility, transitioning from rigid to highly compliant upon in vivo contact.
- Achieved a three-order-of-magnitude reduction in the device's effective modulus.
- Enabled nonpenetrative, 3D access to deep cortical sulci and gyri.
- Demonstrated high-quality electrical interfacing with large-area, tissue-compliant coverage.
Conclusions:
- sFlex-Fold provides a unique solution for accessing neural information in complex brain structures.
- The system's adaptable mechanical properties and 3D morphing capabilities overcome limitations of traditional neural interfaces.
- This technology facilitates high-fidelity neural interfacing for advanced neuroscience research and potential clinical applications.

