Electrical characterization and accelerated aging of amorphous silicon carbide implantable encapsulation

<i>Objective</i>. Chronically implanted microelectrode arrays (MEAs) are used for stimulating and recording neural activity in research and clinical settings. However, their reliability can be compromised by insufficient encapsulation stability. Amorphous silicon carbide (a-SiC), a chemically stable and biocompatible material, has emerged as a potential thin-film encapsulation for MEAs. We aimed to evaluate thin-film a-SiC encapsulation using electrical-accelerated aging (EAA) and to demonstrate a methodology for obtaining acceleration factors for EAA by Weibull analysis.<i>Approach</i>. Interdigitated electrodes (IDEs) encapsulated with a-SiC were subjected to voltage cycling and stepped-voltage protocols to measure leakage currents in buffered saline at 37 °C. EAA employed incrementally increasing voltage biases over time to induce degradation and reveal failure mechanisms.<i>Main results</i>. IDEs exhibited a significant change in electrical behavior on exposure to saline, with failure initiating at specific voltages and accompanied by gas evolution at defect sites. Incremental voltage biasing revealed a capacitive-to-faradaic transition in leakage current response that was used as a failure criterion.<i>Significance</i>. Acceleration factors for voltage-driven accelerated aging of a-SiC thin-film encapsulation can be obtained by Weibull analysis using a mechanistic failure criterion. Breakdown occurs at processing-related defects in the a-SiC. This study demonstrates the use of EAA for evaluating failure in a-SiC thin-film encapsulation used in implantable MEAs. EAA is broadly applicable to thin-film MEAs and provides a highly relevant method of predicting implanted lifetimes of bioelectronics.

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Publication Details

Journal
Journal of Neural Engineering
Published
2025-12-01
DOI
https://doi.org/10.1088/1741-2552/ae2956
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Electrical characterization and accelerated aging of amorphous silicon carbide implantable encapsulation

Negar Geramifard, Megha D. Bhatt, Stuart F. Cogan, Christopher K. Nguyen et al.
Journal of Neural Engineering
Neuroscience and Neural Engineering
article

Electrical characterization and accelerated aging of amorphous silicon carbide implantable encapsulation

Negar Geramifard, Megha D. Bhatt, Stuart F. Cogan, Christopher K. Nguyen, Alexandra Joshi‐Imre, Yupeng Wu, Sandeep Negi
article en

Abstract

<i>Objective</i>. Chronically implanted microelectrode arrays (MEAs) are used for stimulating and recording neural activity in research and clinical settings. However, their reliability can be compromised by insufficient encapsulation stability. Amorphous silicon carbide (a-SiC), a chemically stable and biocompatible material, has emerged as a potential thin-film encapsulation for MEAs. We aimed to evaluate thin-film a-SiC encapsulation using electrical-accelerated aging (EAA) and to demonstrate a methodology for obtaining acceleration factors for EAA by Weibull analysis.<i>Approach</i>. Interdigitated electrodes (IDEs) encapsulated with a-SiC were subjected to voltage cycling and stepped-voltage protocols to measure leakage currents in buffered saline at 37 °C. EAA employed incrementally increasing voltage biases over time to induce degradation and reveal failure mechanisms.<i>Main results</i>. IDEs exhibited a significant change in electrical behavior on exposure to saline, with failure initiating at specific voltages and accompanied by gas evolution at defect sites. Incremental voltage biasing revealed a capacitive-to-faradaic transition in leakage current response that was used as a failure criterion.<i>Significance</i>. Acceleration factors for voltage-driven accelerated aging of a-SiC thin-film encapsulation can be obtained by Weibull analysis using a mechanistic failure criterion. Breakdown occurs at processing-related defects in the a-SiC. This study demonstrates the use of EAA for evaluating failure in a-SiC thin-film encapsulation used in implantable MEAs. EAA is broadly applicable to thin-film MEAs and provides a highly relevant method of predicting implanted lifetimes of bioelectronics.

Journal of Neural EngineeringVol. 22(6)
The University of Texas at Dallas (US), Blackrock Microsystems (United States) (US)
National Institutes of Health, National Institute on Deafness and Other Communication Disorders
Openalex Percentile: Top 58%
Neuroscience and Neural Engineering
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