Evaluation of the Biocompatibility of Poly(benzimidazobenzophenanthroline)(BBL) Polymer Films with Living Cells
The integration of organic electronic materials with biological systems to monitor, interface with, and regulate physiological processes is a key area in the field of bioelectronics. Central to this advancement is the development of cell-chip coupling, where materials engineering plays a critical role in enhancing biointerfacing capabilities. Conductive polymers have proven particularly useful in cell interfacing applications due to their favorable biophysical and chemical properties. However, n-type conductive polymers remain underexplored, primarily due to their limited long-term stability. In this study, it is demonstrated that the conductive polymer poly(benzimidazobenzophenanthroline) (BBL), commonly used in organic electronic devices, can effectively support neuronal cell viability and spreading, both as a bare cell culture material and when coated with exracellular matrix proteins. This work provides a preliminary validation of BBL's potential for future integration into bioelectronic devices and in biointerfacing.
Authors
- Qifan Li (ORCID: https://orcid.org/0000-0002-9081-8564)
- Claudia Latte Bovio (ORCID: https://orcid.org/0000-0002-2064-4570)
- Grazia M. L. Messina (ORCID: https://orcid.org/0000-0001-6144-4914)
- Ana De La Fuente Durán
- Francesca Santoro (ORCID: https://orcid.org/0000-0001-7323-9504)
- Simone Fabiano (ORCID: https://orcid.org/0000-0001-7016-6514)
- Alberto Salleo (ORCID: https://orcid.org/0000-0002-7448-9123)
- Paola Campione (ORCID: https://orcid.org/0009-0004-1756-028X)
- Hanyan Wu
Institutions
- Linköping University (SE)
- Forschungszentrum Jülich (DE)
- Italian Institute of Technology (IT)
- University of Catania (IT)
- University of Naples Federico II (IT)
- RWTH Aachen University (DE)
- Stanford University (US)
Publication Details
- Journal
- Small
- Published
- 2024-12-23
- DOI
- https://doi.org/10.1002/smll.202404451
- Citations
- 4
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 1.07