Evidence map›Paper›PMID 38063737›Full record

ArticleNanomaterials (Basel, Switzerland)2023

Bismuth-Based Metal-Organic Framework as a Chemiresistive Sensor for Acetone Gas Detection.

Ashraf Ali, Yaser E Greish, Reem H Alzard, Lamia A Siddig, Ahmed Alzamly, Naser Qamhieh, Saleh T Mahmoud

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Metal-Organic Framework (MOF)-Based Micro/Nanoscale Materials.Nanomaterials (Basel, Switzerland) · 2025
    Article
  3. Article
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

7 authors.

Ashraf AliDepartment of Physics, United Arab Emirates University, Al-Ain 15551, United Arab Emirates.ORCID 0000-0001-5996-0784
Yaser E GreishDepartment of Chemistry, United Arab Emirates University, Al-Ain 15551, United Arab Emirates.ORCID 0000-0002-7147-6773
Reem H AlzardDepartment of Chemistry, United Arab Emirates University, Al-Ain 15551, United Arab Emirates.
Lamia A SiddigDepartment of Chemistry, United Arab Emirates University, Al-Ain 15551, United Arab Emirates.
Ahmed AlzamlyDepartment of Chemistry, United Arab Emirates University, Al-Ain 15551, United Arab Emirates.ORCID 0000-0002-7586-9785
Naser QamhiehDepartment of Physics, United Arab Emirates University, Al-Ain 15551, United Arab Emirates.ORCID 0000-0002-0292-0367
Saleh T MahmoudDepartment of Physics, United Arab Emirates University, Al-Ain 15551, United Arab Emirates.ORCID 0000-0002-9232-172X

Funding

United Arab Emirates University G00004169, 12R165-Research Center- ZCHS -2-2023 and Grants Codes: USRP-G00003232 with fund 351 code 31R238-M4.
6 · The paper itself

Abstract

Analyzing acetone in the exhaled breath as a biomarker has proved to be a non-invasive method to detect diabetes in humans with good accuracy. In this work, a Bi-gallate MOF doped into a chitosan (CS) matrix containing an ionic liquid (IL) was fabricated to detect acetone gas with a low detection limit of 10 ppm at an operating temperature of 60 °C and 5 V operating bias. The sensor recorded the highest response to acetone in comparison to other test gases, proving its high selectivity along with long-term stability and repeatability. The sensor also exhibited ultra-fast response and recovery times of 15 ± 0.25 s and 3 ± 0.1 s, respectively. Moreover, the sensor membrane also exhibited flexibility and ease of fabrication, making it ideal to be employed as a real-time breath analyzer.

Indexed as

acetone sensorBi-gallate MOFbreath analyzerchitosan

Identifiers

PMID38063737
PMCPMC10708270

What OpenQuestion holds

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Registered trials

None linked

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.