Research Data Leeds Repository
Data associated with ‘Multi-modal millimeter-wave sensors for plastic polymer material characterization’
Citation
Chudpooti, Nonchanutt and Doychinov, Viktor and Hong, Binbin and Akkaraekthalin, Prayoot and Robertson, Ian and Somjit, Nutapong (2018) Data associated with ‘Multi-modal millimeter-wave sensors for plastic polymer material characterization’. University of Leeds. [Dataset] https://doi.org/10.5518/396
Dataset description
This paper presents, for the first time, a multimodal sensor for characterizing relative permittivity of plastic polymers by integrating in a single sensor (1) frequency-reconfigurable resonance technique at 98 and 100 GHz, and (2) 80-100-GHz broadband modified transmission-line technique. The sensor is designed based on a custom-made WR-10 waveguide featuring dual rectangular Complementary Split-Ring Resonators (CSRRs). By loading the CSRRs with a Material-Under-Test (MUT), the reflected and transmitted electromagnetic waves propagating inside the waveguide are changed depending on the dielectric properties of the material. Various plastic polymer materials, e.g. Polytetrafluoroethylene (PTFE), Polymethylmethacrylate (PMMA) and High-Density Polyethylene (HDPE), are characterized. The sensor in this paper offers various key advantages over any state-of-the-art material characterization techniques at millimeter-wave frequencies, e.g. multiple characterization techniques integrated in a single device, miniaturization, much higher tolerance to changes in the measurement environment, ease of design and fabrication, and better cost effectiveness.
Keywords: | Complex dielectric properties, millimeter-wave, CSRR, modified transmission-line, microwave measurements | ||||||
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Subjects: | H000 - Engineering > H600 - Electronic & electrical engineering | ||||||
Divisions: | Faculty of Engineering and Physical Sciences > School of Electronic and Electrical Engineering | ||||||
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License: | Creative Commons Attribution 4.0 International (CC BY 4.0) | ||||||
Date deposited: | 09 Nov 2018 16:37 | ||||||
URI: | https://archive.researchdata.leeds.ac.uk/id/eprint/448 | ||||||