Evidence map›Paper›PMID 32453573›Full record

ArticleLangmuir : the ACS journal of surfaces and colloids2020

One-Dimensional Nanostructured Oxide Chemoresistive Sensors.

Navpreet Kaur, Mandeep Singh, Elisabetta Comini

Abstract read
In one paragraph

Article in Langmuir : the ACS journal of surfaces and colloids, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Resistive nanostructured WRSC advances · 2025
    Review
  6. Article
  7. n-n type InMikrochimica acta · 2024
    Article
  8. Review
  9. A Review of Gas Sensors for COSensors (Basel, Switzerland) · 2024
    Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. WSSensors (Basel, Switzerland) · 2022
    Article
  17. Review
  18. Article
  19. 1D Titanium Dioxide: Achievements in Chemical Sensing.Materials (Basel, Switzerland) · 2020
    Review
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

3 authors.

Navpreet KaurSensor Laboratory, University of Brescia, Via D. Valotti 9, 25133 Brescia, Italy.ORCID http://orcid.org/0000-0002-7789-5733
Mandeep SinghSensor Laboratory, University of Brescia, Via D. Valotti 9, 25133 Brescia, Italy.
Elisabetta CominiSensor Laboratory, University of Brescia, Via D. Valotti 9, 25133 Brescia, Italy.ORCID http://orcid.org/0000-0003-2559-5197

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Day by day, the demand for portable, low cost, and efficient chemical/gas-sensing devices is increasing due to worldwide industrial growth for various purposes such as environmental monitoring and health care. To fulfill this demand, nanostructured metal oxides can be used as active materials for chemical/gas sensors due to their high crystallinity, remarkable physical/chemical properties, ease of synthesis, and low cost. In particular, (1D) one-dimensional metal oxides nanostructures, such as nanowires, exhibit a fast response, selectivity, and stability due to their high surface-to-volume ratio, well-defined crystal orientations, controlled unidirectional electrical properties, and self-heating phenomenon. Moreover, with the availability of large-scale production methods for nanowire growth such as thermal oxidation and evaporation-condensation growth, the development of highly efficient, low cost, portable, and stable chemical sensing devices is possible. In the last two decades, tremendous advances have been achieved in 1D nanostructured gas sensors ever since the pioneering work by Comini on the development of a SnO

Identifiers

PMID32453573
PMCPMC8154880

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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.