Facile and Scalable Nanoneedle Array Fabrication for Enhanced Neural Signal Sensing on Microelectrode Arrays

Microelectrode arrays (MEAs) have emerged as a pivotal tool in electrophysiological research, enabling long-term in vitro culture of neuronal networks and real-time monitoring of their electrophysiological activities with high spatial resolution. Nevertheless, the pursuit of higher spatial resolution necessitates miniaturizing electrode dimensions, which inevitably leads to a pronounced reduction in the signal-to-noise ratio (SNR). In this context, surface modification of microelectrodes is deemed an essential strategy to optimize their electrochemical performance. Conventional surface modification approaches, such as the electrodeposition of platinum black, suffer from inadequate coating-substrate adhesion due to intrinsic material heterogeneity between the deposited layer and the electrode substrate, thereby reducing their durability. To address this critical challenge, we herein propose a facile and scalable nanofabrication strategy for preparing nanoneedle structures that directly in situ fabricates the substrate into a nanoneedle array architecture, thereby markedly enhancing the structural durability of the modified microelectrodes. Subsequent experimental characterizations further validate the superior performance of the nanoneedle-structured electrodes in effectively improving the SNR of electrophysiological signal detection. Utilizing the self-fabricated nanoneedle-based MEAs, we successfully captured the synchronized spontaneous burst activities of neuronal networks that had undergone 3 weeks of in vitro culture, demonstrating the feasibility and applicability of our modified MEA chips for long-term electrophysiological studies of neuronal networks.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2026-05-29
DOI
https://doi.org/10.1021/acsami.6c05392
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Facile and Scalable Nanoneedle Array Fabrication for Enhanced Neural Signal Sensing on Microelectrode Arrays

Guoxu Yu, Yi-Xiang Wang, Yuan Ma, Qing Zhang et al.
ACS Applied Materials & Interfaces
Neuroscience and Neural Engineering
article

Facile and Scalable Nanoneedle Array Fabrication for Enhanced Neural Signal Sensing on Microelectrode Arrays

Guoxu Yu, Yi-Xiang Wang, Yuan Ma, Qing Zhang, Yujiao Wang
article en

Abstract

Microelectrode arrays (MEAs) have emerged as a pivotal tool in electrophysiological research, enabling long-term in vitro culture of neuronal networks and real-time monitoring of their electrophysiological activities with high spatial resolution. Nevertheless, the pursuit of higher spatial resolution necessitates miniaturizing electrode dimensions, which inevitably leads to a pronounced reduction in the signal-to-noise ratio (SNR). In this context, surface modification of microelectrodes is deemed an essential strategy to optimize their electrochemical performance. Conventional surface modification approaches, such as the electrodeposition of platinum black, suffer from inadequate coating-substrate adhesion due to intrinsic material heterogeneity between the deposited layer and the electrode substrate, thereby reducing their durability. To address this critical challenge, we herein propose a facile and scalable nanofabrication strategy for preparing nanoneedle structures that directly in situ fabricates the substrate into a nanoneedle array architecture, thereby markedly enhancing the structural durability of the modified microelectrodes. Subsequent experimental characterizations further validate the superior performance of the nanoneedle-structured electrodes in effectively improving the SNR of electrophysiological signal detection. Utilizing the self-fabricated nanoneedle-based MEAs, we successfully captured the synchronized spontaneous burst activities of neuronal networks that had undergone 3 weeks of in vitro culture, demonstrating the feasibility and applicability of our modified MEA chips for long-term electrophysiological studies of neuronal networks.

ACS Applied Materials & Interfaces
Yanbian University (CN), College of Medical Sciences (NP), Tsinghua University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 8%
Neuroscience and Neural Engineering
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