Biocompatible Neuromorphic Device Array Based on Naturally Sourced Mucin for Implantable Bioelectronics
Although the demand for intelligent implantable bioelectronics is steadily increasing, their progress is hindered by the limited availability of materials with sufficient biocompatibility for implantation. Herein, we propose a neuromorphic device with human brain-inspired biomimetic functionality utilizing naturally sourced mucin as the active layer material. The mucin-based neuromorphic memristor (MNM) array successfully mimics key synaptic behaviors uniformly, including a paired-pulse facilitation index of 122.65%, transition from short-term to long-term memory, long-term potentiation, and long-term depression. In addition to the effect of the defect-rich mucin active layer, these behaviors are enhanced by the presence of a MgO<sub><i>x</i></sub> interfacial layer formed at its interface with the Mg top electrode. The cell cytotoxicity test results demonstrate the superior biocompatibility of the MNM array, which shows a relative cell viability of 108.46% after 72 h of cell culture. Moreover, the artificial neural network simulation demonstrates a recognition rate of 89.93% after 125 training epochs, which suggests that naturally sourced materials, including mucin, can be used in implantable bioelectronics for advanced medical healthcare applications.
Authors
- Hyun Jae Kim (ORCID: https://orcid.org/0000-0002-6879-9256)
- Kyungmoon Kwak
- Byulhana Kim
- Dong Hyun Choi (ORCID: https://orcid.org/0000-0001-6036-1404)
- Sung Min Rho
- Beom Soo Kim (ORCID: https://orcid.org/0000-0002-7251-7231)
- Justin J. Chung (ORCID: https://orcid.org/0000-0001-8058-2255)
- Byung Ha Kang (ORCID: https://orcid.org/0000-0002-6506-5118)
- Kunho Moon (ORCID: https://orcid.org/0009-0001-1106-3985)
Institutions
- Seoul National University (KR)
- Yonsei University (KR)
- Seoul National University Hospital (KR)
- Massachusetts Institute of Technology (US)
Publication Details
- Journal
- ACS Nano
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1021/acsnano.4c18846
- Citations
- 12
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 10.91
Funders
- National Research Foundation of Korea