State‐Programmable Conductive and Reactivatable Bio‐Adhesive for High‐Fidelity Epidermal Biointerfaces
Owing to the inherent trade-off between conformal wetting and mechanical stability at the electrode-skin interface, achieving both microscale conformality and mechanical stability for epidermal electrophysiology remains challenging. Ionically conductive gels provide low interfacial impedance through fluidic wetting but suffer from dehydration and instability, whereas dry soft electrodes offer mechanical stability but lack the rheological adaptability needed for intimate skin contact. Here, we report a state-programmable graft interpenetrating network (g-IPN) that enables a printable and reactivatable conductive adhesive (RCA). The RCA simultaneously achieves high electrical conductivity, state-dependent adhesion, and reversible viscoelasticity. By transitioning from a mechanically robust solid film to a fluidic state via solvent activation, the RCA infiltrates complex skin surfaces and hair-occluded regions, delivering lower interfacial impedance than traditional gels. These properties enable stable electroencephalogram (EEG) and pulse recordings across both rigid and soft electrode platforms, establishing a scalable strategy for high-fidelity epidermal bioelectronic interfaces.
Authors
- Tao Zhou (ORCID: https://orcid.org/0000-0002-6507-8912)
- Xiaojun Lian (ORCID: https://orcid.org/0000-0002-9161-1004)
- Yueqi Deng
- Salahuddin Ahmed (ORCID: https://orcid.org/0000-0002-0666-8496)
- Marzia Momin
- Jiashu Ren
- Hyunjin Lee
- Jia Sun
- Jirong Lin (ORCID: https://orcid.org/0009-0008-9662-6820)
- Xinyi Wang
Institutions
- Pennsylvania State University (US)
Publication Details
- Journal
- Small
- Published
- 2026-08-26
- DOI
- https://doi.org/10.1002/smll.75442
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- National Institutes of Health
- Huck Institutes of the Life Sciences
- Division of Materials Research