Evidence map›Paper›PMID 39532664›Full record

ArticleACS sensors2024

Insights into Target Gas-Oxygen Interactions in Highly Sensitive Gas Sensors Using Data-Driven Methods.

Kyusung Kim, Phuwadej Pornaroontham, Hojung Yun, Sungmin Kim, Pilgyu Choi, Yoshitake Masuda

Abstract read
In one paragraph

Article in ACS sensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

6 authors.

Kyusung KimInstitute of Material Innovation, Institutes of Innovation for Future Society, Nagoya University, Nagoya 464-8601, Japan.ORCID 0000-0003-0999-6759
Phuwadej PornaroonthamDepartment of Chemical Technology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
Hojung YunDepartment of Sustainable Materials and Technology for Industries, Faculty of Engineering, Nagoya University, Nagoya 464-8601, Japan.ORCID 0000-0001-7003-6074
Sungmin KimKorea Institute of Industrial Technology, Surface R&D Group, 156, Gaetbeol-ro, Yeonsu-gu, Incheon 21999, Republic of Korea.ORCID 0000-0001-7490-5126
Pilgyu ChoiNational Institute of Advanced Industrial Science and Technology (AIST), 2266-98 Anagahora, Shimoshidami, Moriyama ,Nagoya463-8560, Japan.ORCID 0000-0003-0439-8426
Yoshitake MasudaNational Institute of Advanced Industrial Science and Technology (AIST), 2266-98 Anagahora, Shimoshidami, Moriyama ,Nagoya463-8560, Japan.ORCID 0000-0002-4710-1306

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the gas-sensing mechanism of a metal-oxide-semiconductor (n-type) gas sensor, oxygen adsorption or desorption on the oxide surface leads to an increase or decrease in the resistance of the gas sensor system. Additionally, oxygen can be adsorbed again at the location where initially adsorbed oxygen reacted with the target gas. Thus, the adsorption-desorption equilibrium of the reducing gas on the oxide surface is a significant factor in determining the sensitivity and reaction rate. In particular, for ultralow-concentration gas measurements, the relative concentration of oxygen was very high. To design an ultrasensitive gas sensor, not only the reaction of the target gas but also the competing reaction between the target gas and oxygen must be considered. Although qualitative investigations of these complex relationships have been performed according to the gas concentration and flow rate, reliable quantitative results are limited. In this study, a quantitative approach was used to understand the correlation between oxygen and a target gas by applying data analysis methods. We investigated the behavior of oxygen and the target molecules depending on the gas concentration and flow rate using the parts per billion level of the acetone gas sensor. Initial response data according to various detection conditions were processed using principal component analysis and K-means clustering; as a result, four types of reaction behaviors were inferred for 15 types of reaction conditions. Furthermore, the response time, depending on the detection conditions, can be distinguished using the suggested categorization. Our investigation suggests a possibility beyond simple optimization through the data analysis of the gas-sensing results.

Indexed as

OxygenAcetoneAdsorptionGasesPrincipal Component AnalysisSemiconductorsAcetoneGasesOxygenclusteringflow rategas sensorsnanosheetsSnO2

Identifiers

PMID39532664
PMCPMC11590098

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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.