Tu-SFM-05 - Efficient Prediction of Damping in Acceleration Sensors by Physical Compact Modelling

Event

EUROSENSORS 2026
2026-09-06 - 2026-09-09
Zurich

Band

Poster

Chapter

Sensor Fundamentals & Modelling

Author(s)

F. Michael, G. Schrag - Technical University of Munich,Munich (Germany), K. Hiller, S. Weidlich - TU Chemnitz,Chemnitz (Germany), R. Forke - Fraunhofer Institute for Electronic Nano Systems ENAS,Chemnitz (Germany), S. Pregl - Infineon Technologies AG,Dresden (Germany)

Pages

682 - 683

DOI

10.5162/eurosensors2026/Tu-SFM-05

ISBN

978-3-910600-12-6

Price

free

Abstract

In this work, we use generalized Kirchhoffian networks (GKNs) composed of physically based compact models to efficiently and accurately predict viscous damping in highly perforated moving micromechanical structures. We introduce compact models for slit-shaped perforations, validated by dedicated test structures, and successfully applied them to an acceleration sensor. Comparison with measurements shows good agreement and prove the feasibility of the approach.