Calibration and deembedding for impedance measurments
A centrepiece of our work is the design of customized printed circuit board cells (see the folder Rogers' PCB cells), optimized to simplify and enhance measurement accuracy. These PCB cells are coupled with a multi-stage calibration process, which ensures that our data is both reliable and adaptable to a range of experimental conditions. This level of precision and flexibility allows for the exploration of surface impedance under external stimuli, such as magnetic field, mechanical stress, or temperature. Our approach not only simplifies the characterization process but also provides a versatile framework for tailoring ferromagnetic microwires to specific applications, from high-performance sensors to innovative metamaterials.
Three algorithms in Python are used to enable the impedance measurements in wire samples on a vector network analyzer (VNA). Follow the detailed manual-report saved in the pdf file (Multi-stage calibration for impedance measurements).
You will need the following Python libraries: numpy, matplotlib.pyplot, scipy, scipy.interpolate
To cite this article: Azim Uddin et al 2023 Meas. Sci. Technol.; https://iopscience.iop.org/article/10.1088/1361-6501/accd09
LabVIEW programs for controlling devices during the magneto-impedance measurements can be found in our other repository: https://github.com/DYK-Team/Magneto-impedance_measurements
Also see the following project at the University of Plymouth, UK: COMPOSITE MATERIALS FILLED WITH FERROMAGNETIC MICROWIRE INCLUSIONS DEMONSTRATING MICROWAVE RESPONSE TO TEMPERATURE AND TENSILE STRESS (https://pearl-prod.plymouth.ac.uk/handle/10026.1/9488)