Recent Advances in Transparent Microelectrode Device Architecture and Fabrication Strategies for Biomedical Applications
ABSTRACT Transparent microelectrodes represent a new class of bioelectronic interfaces that enable fast‐response electrical recording and optical mapping with high spatial resolution. This review summarizes recent advances in transparent microelectrode systems for biomedical applications, including concurrent electrical–optical mapping, simultaneous electrophysiological recording with optogenetic stimulation, non‐genetic modulation, and their integration into medical robotic platforms. We focus on device architectures and fabrication strategies categorized into inherently transparent materials, top‐down, bottom‐up, and hybrid approaches, and discuss key trade‐offs among optical transmittance, electrochemical impedance, mechanical compliance, and biostability. Current demonstrations typically achieve 60–90% optical transparency and impedance values ranging from ∼1 MΩ at 1 kHz to ∼10 kΩ at 1 kHz, depending on material choice and electrode geometry. We additionally assess integration routes that enable multifunctionality, including optical components and transistor‐based electronics. Remaining challenges, such as signal crosstalk, fabrication scalability, long‐term stability, and reliability, are discussed in the context of emerging solutions. The review concludes by outlining future opportunities in closed‐loop therapeutics and multimodal implantable systems.
Authors
- Thanh Nho Do (ORCID: https://orcid.org/0000-0002-4980-5251)
- Hoang‐Phuong Phan (ORCID: https://orcid.org/0000-0002-1724-5667)
- Chi Cong Nguyen (ORCID: https://orcid.org/0000-0002-8113-5163)
- Michael Abraham Listyawan (ORCID: https://orcid.org/0009-0009-0413-2696)
- Tran Bach Dang
- Tianruo Guo (ORCID: https://orcid.org/0000-0001-6348-6771)
- Yee Lap Pong (ORCID: https://orcid.org/0009-0001-8331-2098)
Institutions
- UNSW Sydney (AU)
- New South Wales Institute of Psychiatry (AU)
Publication Details
- Journal
- Advanced Materials Technologies
- Published
- 2026-09-21
- DOI
- https://doi.org/10.1002/admt.71333
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00