Light-regulated biomaterial interfaces enable flexible neural bioelectronics with stable adhesion and on-demand detachment for chronic electrophysiology
Dynamic bioelectronic interfaces are required to simultaneously ensure stable tissue integration for chronic recording and controllable debonding for device reconfiguration or retrieval. This challenge is particularly acute for implantable neural interfaces, where weak adhesion compromises signal fidelity, while permanent adhesion may cause secondary tissue damage during removal. Here, we developed a photo-programmable neural biointerface incorporating a self-healing bPDMS@Fe matrix based on a carboxyl-functionalized polydimethylsiloxane network dynamically crosslinked by Fe 3+ -carboxylate coordination. The resulting electrode exhibits robust adhesion to diverse substrates and biological tissues, as well as on-demand removal through UV-induced adhesion weakening. Moreover, it supports stable epidermal electrocardiogram recording under various conditions. Furthermore, the biointerface is translated into a 9-channel cortical electrode array that enables stable local field potential recording and spatiotemporal mapping of seizure-associated neural activity in freely moving mice. This work establishes a dynamic adhesive strategy as a new materials design paradigm for neural bioelectronic interfaces toward next-generation chronic electrophysiological monitoring devices.
Authors
- 舒幼生
- Quansheng He (ORCID: https://orcid.org/0000-0002-0235-0843)
- Zili Li (ORCID: https://orcid.org/0000-0001-9921-6394)
- Haoyi Yang
- Liting Sun
- Miao Tang (ORCID: https://orcid.org/0009-0007-2284-4510)
- Xiaoxue Zhang
- Hui Guo
- Zhongzhong Wang
- Binbin Hu
Institutions
- Qingdao University (CN)
- Fudan University (CN)
- Huadong Hospital (CN)
- Chinese Institute for Brain Research (CN)
- Frontiers Center for Brain Science of the Ministry of Education (CN)
Publication Details
- Journal
- npj Flexible Electronics
- Published
- 2026-10-26
- DOI
- https://doi.org/10.1038/s41528-026-00659-w
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Shanghai Rising-Star Program
- National Science and Technology Major Project
- Program of Shanghai Academic Research Leader