Evidence map›Paper›PMID 40676080›Full record

ArticleScientific reports2025

Microfluidic lab-on-chip design for efficient relative humidity sensing using a capacitive transducer.

Mohamed Abdelghani, Osama Hussien

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

2 authors.

Mohamed AbdelghaniFaculty of EMS, German University in Cairo, Cairo, Egypt. mohamed.abdelhalim.abdelghani@ieee.org.ORCID http://orcid.org/0009-0004-7763-0323
Osama HussienFaculty of IET, German University in Cairo, Cairo, Egypt.ORCID http://orcid.org/0009-0009-0942-1112

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advancements in microelectronics have provided substantial motivation for ongoing innovation within the domain of sensor and measurement technologies. The application of humidity sensors across diverse settings has been integral to system monitoring initiatives. There exists potential for further enhancements aimed at the development of sensors that are not only more efficient and safer but also more conducive to human interaction. The sensors thus developed and presented in this article hold promise for deployment in pioneering applications, offering precision measurements surpassing those of traditional sensors. Moreover, these advanced sensors are poised to be integral components of emergent applications in biomedical research and energy harvesting technologies. In this study, a lab-on-a-chip (LOC) design that uses microfluidic principles is designed and implemented. The proposed design is concerned with measuring the relative humidity of the surrounding medium using a capacitive transducer. The proposed methodology is designed, implemented, and tested on a low-cost experimental setup; results were recorded using LabVIEW. Achieving a resolution of 33.993 mL/V with a sensitivity of 0.0596 V m/F and noise tolerance of 2.028 V, the system successfully demonstrated its capability by implementing a prototype that charges a 22 pF capacitor. While the observed capacitance change and corresponding voltage output remain too low for direct device charging, this proof-of-concept demonstrates the potential of harvesting ambient moisture-driven energy. Further work on materials and circuit design will be needed to quantify power output and advance toward sustainable mobile-device charging.

Indexed as

Biomedical applicationsCapacitive transducerHumidityHygrometerLab on chipRelative permittivity

Identifiers

PMID40676080
PMCPMC12271306

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.