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Review and perspectives of the force-displacement measurement system with electromagnetic and electrostatic force compensation principles

  • Valeriya Cherkasova ORCID logo EMAIL logo
Published/Copyright: April 8, 2025

Abstract

The article reviews existing traceable small force-displacement measurement methods and presents a modified version of the force-displacement measurement device used to calibrate the stiffnesses of MEMS and cantilevers, as well as the forces they generate in the range from 10 nN to 2 mN. Separately, improved results for force constants and soft cantilever stiffness calibration (force up to 300 nN) with an expanded relative uncertainty of 0.46 % are shown. In conclusion, the prospects for the development of the force-displacement measurement system are discussed.

Zusammenfassung

Der Artikel gibt einen Überblick über vorhandene rückführbare Kleinkraft-Weg-Messverfahren und präsentiert eine modifizierte Version des Kraft-Weg-Messgeräts, das zur Kalibrierung der Steifigkeiten von MEMS und Cantilevern sowie der von ihnen erzeugten Kräfte im Bereich von 10 nN bis 2 mN verwendet wird. Weiterhin werden verbesserte Ergebnisse für die Kalibrierung von Kraftkonstanten und der Steifigkeit weicher Cantilever (Kraft bis 300 nN) mit einer erweiterten relativen Unsicherheit von 0,46 % gezeigt. Abschließend werden die Perspektiven für die Entwicklung des Kraft-Weg-Messsystems diskutiert.


Corresponding author: Valeriya Cherkasova, Institute of Process Measurement and Sensor Technology, Technische Universität Ilmenau, 98684 Ilmenau, Germany, E-mail: 

Acknowledgments

The author gratefully acknowledges the support by the Deutsche Forschungsgemeinschaft (DFG) in the scope of the Research Training Group “Tip- and Laser-based 3D-Nanofabrication in extended macroscopic working areas” (GRK 2182) at Technische Universität Ilmenau, Germany.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The author states no conflict of interest.

  6. Research funding: Deutsche Forschungsgemeinschaft (DFG) – Project number 274711337.

  7. Data availability: Not applicable.

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Received: 2025-01-29
Accepted: 2025-03-26
Published Online: 2025-04-08
Published in Print: 2025-05-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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