journal article·2025-12Open access

Polymer‐Incorporated Mechanically Compliant Carbon Nanotube Microelectrode Arrays for Multichannel Neural Signal Recording

Hyeonhee Roh, Kwangjun Kim, Chaesung Kim, Minju Kim, Minwook Kim, Sangjun Sim, Jongbaeg Kim, Jong G. Ok, Maesoon Im

Advanced Functional Materials· Volume 35· Issue 51

Abstract

Abstract Implantable microelectrode arrays are essential for neural signal acquisition, facilitating advances in both fundamental neuroscience and clinical neuroprosthetics. However, conventional metal‐based electrodes exhibit severe mechanical mismatch with soft brain tissue, often resulting in insertion‐induced micro‐damage and chronic inflammation. While polymer‐based alternatives offer improved mechanical compliance, their inherently low electrical conductivity limits performance. Here, a soft microelectrode array composed of vertically‐aligned carbon nanotube (CNT) forests that uniquely combine high electrical conductivity (≈41.24 kΩ at 1 kHz) and mechanical softness (≈54 MPa) is presented. To enhance mechanical robustness without compromising electrical conductivity, a capillary‐force‐induced densification process, followed by a novel air‐pressure‐assisted flexibilization technique, is used. By infiltrating an elastomer matrix into the CNT pillars, polymer‐incorporated, vertically aligned CNT microelectrode arrays optimized for implantation are developed. The resulting devices exhibit enhanced mechanical compliance and stable insertion behavior, as confirmed by mechanical characterization and insertion tests into agarose gels and mouse brains. Histological analysis reveals reduced inflammatory responses compared to conventional tungsten microwires. Furthermore, in vivo electrophysiological recordings demonstrate reliable acquisition of visually evoked neural signals. These results highlight the potential of CNT‐based soft microelectrode arrays to overcome the mechanical and electrical limitations of existing neural interfaces, enabling more stable, biocompatible, and high‐fidelity neural recordings.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Neuroscience and Neural Engineering · Advanced Memory and Neural Computing · EEG and Brain-Computer Interfaces

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Brain Science Institute Korea Institute of Science and Technology (KIST) Seoul 02792 South Korea

Department of Mechanical and Automotive Engineering Seoul National University of Science and Technology Seoul 01811 South Korea

Division of Electrical Engineering College of Engineering Korea University Seoul 02841 South Korea

Department of Brain and Cognitive Engineering Korea University Seoul 02841 South Korea

School of Mechanical Engineering Yonsei University Seoul 03722 South Korea

Division of Bio‐Medical Science and Technology, KIST School University of Science and Technology (UST) Seoul 02792 South Korea

KHU‐KIST Department of Converging Science and Technology Kyung Hee University Seoul 02447 South Korea

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