Evidence map›Paper›PMID 41942701›Full record

ArticleScientific reports2026

CVE-assisted Co

Bhawani Sahu, Ramkrushna Sahu, Priyanshu Kumar Patro, Kumar Prasannajit Sahu, Anurag Das, Tusharkant Panda, Padmini Mishra, Adarsh Nigam, Pramod Martha

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2026. 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

9 authors.

Bhawani SahuE-YUVA BIRAC Fellow, GIET University, Gunupur, Odisha, India.
Ramkrushna SahuE-YUVA BIRAC Fellow, GIET University, Gunupur, Odisha, India.
Priyanshu Kumar PatroE-YUVA BIRAC Fellow, GIET University, Gunupur, Odisha, India.
Kumar Prasannajit SahuE-YUVA BIRAC Fellow, GIET University, Gunupur, Odisha, India.
Anurag DasE-YUVA BIRAC Fellow, GIET University, Gunupur, Odisha, India.
Tusharkant PandaDepartment of Electronics and Communication Engineering, GIET University, Gunupur, Odisha, India.
Padmini MishraDepartment of Electronics and Communication Engineering, GIET University, Gunupur, Odisha, India.
Adarsh NigamManipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India.
Pramod MarthaManipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India. pramod.martha@manipal.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, an acetone sensor based on a single-mode fiber (SMF) coated with cobalt oxide (Co[Formula: see text]O[Formula: see text]) nanoparticles is characterized. Different methods were explored for coating Co[Formula: see text]O[Formula: see text] nanoparticles on SMF, and a chemical vapor etching (CVE) method was optimized to yield a functionalized SMF. The Co[Formula: see text]O[Formula: see text] nanoparticles were synthesized via coprecipitation using cobalt acetate and NaOH. SEM analysis showed that CVE pretreatment created a distinct surface morphology, enabling a more uniform and homogeneous nanoparticle coating compared to the dip coating method. Extensive material characterization methods such as Fourier transform infrared (FTIR), Ultraviolet-Visible (UV-Vis) spectroscopy, dynamic Light Scattering (DLS) analysis, and scanning electron microscope (SEM), are utilized to analyze and evaluate structural stability and homogeneous distribution with optical properties of the nanoparticles and their applicability in breath analysis. A customized sensor characterization setup has been designed for acetone sensing. An optical coupler injects light into the fiber, while another directs the transmitted signal to a photodiode, which converts it into an electrical current varying with acetone concentration. This signal is processed by a microcontroller (Arduino/ESP-32). The output current increases from 0.48 μA at 0.5 ppm to 2.6 μA at 12 ppm, yielding a sensitivity of 0.18 μA/ppm with 3% non-linearity. The sensor offers a low-cost, high-performance solution for acetone detection for early diagnosis and health monitoring, supporting sustainable healthcare and innovation.

Indexed as

AcetoneBreath analysisChemical vapour etching (CVE)Cobalt oxide nanoparticleGas sensorOptical fiber sensor

Identifiers

PMID41942701
PMCPMC13212583

What OpenQuestion holds

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LicenceCC BY
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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.