Evidence map›Paper›PMID 37884608›Full record

ArticleScientific reports2023

Design of high-sensitivity La-doped ZnO sensors for CO

Khaled Abdelkarem, Rana Saad, Adel M El Sayed, M I Fathy, Mohamed Shaban, Hany Hamdy

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Synthesis of Cu-doped VRSC advances · 2025
    Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Facile synthesis of NiFeRSC advances · 2024
    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

6 authors.

Khaled AbdelkaremNanophotonics and Applications (NPA) Lab, Department of Physics, Faculty of Science, Beni-Suef University, Beni-Suef, 62514, Egypt. oldfighter.khaled123@gmail.com.
Rana SaadNanophotonics and Applications (NPA) Lab, Department of Physics, Faculty of Science, Beni-Suef University, Beni-Suef, 62514, Egypt.
Adel M El SayedPhysics Department, Faculty of Science, Fayoum University, El Fayoum, 63514, Egypt.
M I FathyNanophotonics and Applications (NPA) Lab, Department of Physics, Faculty of Science, Beni-Suef University, Beni-Suef, 62514, Egypt.
Mohamed ShabanDepartment of Physics, Faculty of Science, Islamic University of Madinah, 42351, Madinah, Saudi Arabia. mssfadel@aucegypt.edu.
Hany HamdyNanophotonics and Applications (NPA) Lab, Department of Physics, Faculty of Science, Beni-Suef University, Beni-Suef, 62514, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For the sake of people's health and the safety of the environment, more efforts should be directed towards the fabrication of gas sensors that can operate effectively at room temperature (RT). In this context, increased attention has been paid to developing gas sensors based on rare-earth (RE)-doped transparent conducting oxides (TCO). In this report, lanthanum-doped zinc oxide (La-doped ZnO) films were fabricated by sol-gel and spin-coating techniques. XRD analysis revealed the hexagonal structure of the ZnO films, with preferred growth along the (002) direction. The crystallite size was decreased from 33.21 to 26.41 nm with increasing La content to 4.0 at.%. The UV-vis-NIR indicating that the films are highly transparent (˃ 80%), La-doping increased the UV blocking ability of the films and narrowed the optical band gap (Eg) from 3.275 to 3.125 eV. Additionally, La-doping has influenced the refractive index of the samples. Gas sensing measurements were performed at ambient temperature (30 °C) and a relative humidity (RH) of 30%, employing different flow rates of carbon dioxide (CO

Identifiers

PMID37884608
PMCPMC10603051

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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.