Automated Parameter Extraction Of ScAlN MEMS Devices Using An Extended Euler–Bernoulli Beam Theory

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 4; p. 1001
• Main Authors: Krey, Maximilian, Hähnlein, Bernd, Tonisch, Katja, Krischok, Stefan, Töpfer, Hannes
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI 13.02.2020; MDPI AG
• Subjects: algorithm; automation; magnetoelectric sensor; mems; scandium aluminium nitride; young’s modulus; Young’s modulus; magnetoelectric sensor; scandium aluminium nitride; MEMS; automation; algorithm
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20041001

Magnetoelectric sensors provide the ability to measure magnetic fields down to the pico tesla range and are currently the subject of intense research. Such sensors usually combine a piezoelectric and a magnetostrictive material, so that magnetically induced stresses can be measured electrically. Scandium aluminium nitride gained a lot of attraction in the last few years due to its enhanced piezoelectric properties. Its usage as resonantly driven microelectromechanical system (MEMS) in such sensors is accompanied by a manifold of influences from crystal growth leading to impacts on the electrical and mechanical parameters. Usual investigations via nanoindentation allow a fast determination of mechanical properties with the disadvantage of lacking the access to the anisotropy of specific properties. Such anisotropy effects are investigated in this work in terms of the Young’s modulus and the strain on basis of a MEMS structures through a newly developed fully automated procedure of eigenfrequency fitting based on a new non-Lorentzian fit function and subsequent analysis using an extended Euler–Bernoulli theory. The introduced procedure is able to increase the resolution of the derived parameters compared to the common nanoindentation technique and hence allows detailed investigations of the behavior of magnetoelectric sensors, especially of the magnetic field dependent Young‘s modulus of the magnetostrictive layer.