Evidence map›Paper›PMID 36616970›Full record

ArticleSensors (Basel, Switzerland)2022

High-Sensitivity Liquid Dielectric Characterization Differential Sensor by 1-Bit Coding DGS.

Bingfang Xie, Zhiqiang Gao, Cong Wang, Luqman Ali, Azeem Muhammad, Fanyi Meng, Cheng Qian, Xumin Ding, Kishor Kumar Adhikari, Qun Wu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Bingfang XieSchool of Astronautics, Harbin Institute of Technology, Harbin 150006, China.ORCID 0000-0002-4673-2886
Zhiqiang GaoSchool of Astronautics, Harbin Institute of Technology, Harbin 150006, China.
Cong WangSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150006, China.ORCID 0000-0002-2863-0309
Luqman AliSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150006, China.
Azeem MuhammadSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150006, China.
Fanyi MengSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150006, China.
Cheng QianOcean College, Zhejiang University, Hangzhou 310027, China.
Xumin DingSchool of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin 150006, China.ORCID 0000-0002-7725-790X
Kishor Kumar AdhikariSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150006, China.
Qun WuSchool of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150006, China.

Funding

National Key Research and Development Program of China No.2021YFF0603500National Natural Science Foundation of China No.61971160National Natural Science Foundation of China No.U22A2014
6 · The paper itself

Abstract

This paper presents two devices to detect the liquid dielectric characterization. The differential method was used to enhance the robustness and reduce tolerance. A basic sensor based on defected ground structure (DGS) was designed and the optimization for the squares of the DGS via adaptive genetic algorithm was applied to enhance the performance of the microwave sensor, which was shown by the difference of the two resonant frequencies. Furthermore, the electric field distribution was enhanced. Glass microcapillary tubes were used to hold samples to provide an environment of non-invasive. The optimized device exhibited the sensitivity of 0.076, which is more than 1.52 times than the basic structure. It could be considered a sensitive and robust sensor with quick response time for liquid dielectric characterization.

Indexed as

adaptive genetic algorithmdefected ground structureliquid dielectric characterizationmicrowave differential sensor

Identifiers

PMID36616970
PMCPMC9823319

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