Complete Meniscus Removal Method for Broadband Liquid Characterization in a Semi-Open Coaxial Test Cell

Michał Kalisiak , Wojciech Wiatr

Abstract

We present a new technique for broadband liquid characterization using a semi-open, vertically oriented test cell that is measured with a calibrated vector network analyzer in three states: the empty one and filled with two different volumes of the liquid under test. Using the measurements, we de-embed a transfer matrix representing a volume increment of the liquid sample and determine its column height with a novel closed-form formula. Thanks to the de-embedding, the method enables one, for the first time, to completely remove effects caused by a reproducible meniscus forming the top surface of a liquid tested in the cell and determine not only the propagation constant, but also characteristic impedance of the liquid sample, from which its permittivity and permeability are calculated. The results are highly consistent, because all the measurements are performed without disassembling the cell. We validate experimental results of the meniscus removal method by comparing them with reference data and outcomes of the Nicolson–Ross–Weir method.
Author Michał Kalisiak (FEIT / PE)
Michał Kalisiak,,
- The Institute of Electronic Systems
, Wojciech Wiatr (FEIT / PE)
Wojciech Wiatr,,
- The Institute of Electronic Systems
Journal seriesSensors [SENSORS-BASEL], ISSN 1424-8220, (A 30 pkt)
Issue year2019
Vol19
No9
Pages1-11
Publication size in sheets104.6
Keywords in English complex permittivity; permeability; microwave measurements; liquids; meniscus; vector network analyzer; network de-embedding
ASJC Classification2208 Electrical and Electronic Engineering; 1303 Biochemistry; 3107 Atomic and Molecular Physics, and Optics; 1602 Analytical Chemistry
DOIDOI:10.3390/s19092092
URL https://www.mdpi.com/1424-8220/19/9/2092
Languageen angielski
File
sensors-19-02092-v2.pdf 2.53 MB
Score (nominal)30
ScoreMinisterial score = 30.0, 19-06-2019, ArticleFromJournal
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2016 = 1.393; WoS Impact Factor: 2017 = 2.475 (2) - 2017=3.014 (5)
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