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Computational Modeling of Diffusion-Based Delamination for Active Implantable Medical Devices
Minh-Hai Nguyen1,2, Adrian Onken1,2,3, Anika Wulff2
1Department of Otolaryngology and Cluster of Excellence "Hearing4all", Hannover Medical School MHH, 30625 Hannover, Germany.
Bioengineering (Basel, Switzerland)
|May 27, 2023
Summary
Delamination in active implantable medical devices (AIMDs) like cochlear implants (CIs) is a key failure mode. This study presents a mathematical model to understand and predict this failure, validated by experimental data.
Area of Science:
- Bioengineering
- Materials Science
- Mechanical Engineering
Background:
- Delamination at material interfaces is a critical failure mode in active implantable medical devices (AIMDs).
- Body fluid infiltration into polymer substrates and along metal-polymer interfaces complicates modeling of AIMDs, such as cochlear implants (CIs).
- Existing digital twin models lack the complexity to address biofluid infiltration in AIMDs.
Purpose of the Study:
- To develop and validate a mathematical model for delamination and body fluid infiltration in AIMDs, specifically CIs.
- To enhance understanding of failure mechanisms in silicone rubber and metal-based AIMDs.
- To provide a framework for digital twin development in bioengineering.
Main Methods:
- Implementation of a mathematical model using COMSOL Multiphysics®.
- Incorporation of volume diffusion and interface diffusion (delamination) models.
- Validation against experimental data from a newly developed test for AIMDs/CIs.
Main Results:
- The model successfully derived diffusion coefficients from experimental data.
- A good qualitative and functional match was observed between experimental and modeling results.
- The interface diffusion model accurately approximated previous experimental findings.
Conclusions:
- The developed mathematical model provides a better understanding of AIMD failure mechanisms.
- The model's validation against real-life data supports its utility for predicting device performance.
- This work advances the development of complex digital twins for bioengineering applications.

