A Ferroelectric‐Liquid Metal Hybrid Artificial Photoreceptor with Biomimetic Visual Adaptation
Abstract This study develops a photo‐responsive hybrid material based on azo polymer grafted liquid metal nanoparticles embedded in a poly(vinylidene fluoride‐trifluoroethylene) ferroelectric copolymer matrix for use as an artificial retinal prosthesis. The hybrid film with an optimal azo polymer grafted liquid metal nanoparticles loading of 5 wt% exhibits a strong photoelectric response across visible and near‐infrared wavelengths, achieving a maximum photovoltage of over 200 mV. Uniquely, the material mimics both scotopic and photopic adaptation mechanisms of natural human vision without requiring external circuitry. Implanted in rodent models of retinal degeneration, the prosthesis effectively restored visual sensitivity to visible light and extended perception to infrared light, as confirmed through electrophysiological recordings and light‐dark behavioral tests. The implant also demonstrates stable integration and good biocompatibility over three months in vivo. This work offers a promising ferroelectric polymer‐based platform for advanced bioelectronic applications, particularly in the development of next‐generation retinal prostheses with broad‐spectrum light perception.
Authors
- Yaning He (ORCID: https://orcid.org/0000-0003-0860-0126)
- Qi Zhang
- Cheng Sun (ORCID: https://orcid.org/0000-0001-8411-4619)
- Heting Li (ORCID: https://orcid.org/0000-0002-2393-897X)
- Wenlong Zhang (ORCID: https://orcid.org/0000-0002-3671-844X)
- Xi Liu (ORCID: https://orcid.org/0000-0003-4927-8292)
- Jinyu Ma (ORCID: https://orcid.org/0000-0003-1509-9421)
- Wei Wang (ORCID: https://orcid.org/0000-0002-6400-3599)
- Han Liu (ORCID: https://orcid.org/0009-0009-1447-960X)
- Tian Lu
Institutions
- Nantong University (CN)
- Affiliated Hospital of Nantong University (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2025-10-27
- DOI
- https://doi.org/10.1002/adfm.202524740
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00