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Multi gas sensors u...
Multi gas sensors using one nanomaterial, temperature gradient, and machine learning algorithms for discrimination of gases and their concentration
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Thai, Nguyen Xuan (author)
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- Tonezzer, Matteo (author)
- CNR, IMEM, Sede Trento FBK, Via Cascata 56-C, Povo, TN, Italy.;Univ Trento, Via Calepina 14, Trento, Italy.
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- Masera, Luca (author)
- Univ Trento, DISI, Via Sommar 9, Povo, Trento, Italy.
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- Nguyen, Hugo, 1955- (author)
- Uppsala universitet,Mikrosystemteknik
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Duy, Nguyen Van (author)
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Hoa, Nguyen Duc (author)
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CNR, IMEM, Sede Trento FBK, Via Cascata 56-C, Povo, TN, Italy;Univ Trento, Via Calepina 14, Trento, Italy. Univ Trento, DISI, Via Sommar 9, Povo, Trento, Italy. (creator_code:org_t)
- ELSEVIER, 2020
- 2020
- English.
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In: Analytica Chimica Acta. - : ELSEVIER. - 0003-2670 .- 1873-4324. ; 1124, s. 85-93
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- In this work, four identical micro sensors on the same chip with noble metal decorated tin oxide nanowires as gas sensing material were located at different distances from an integrated heater to work at different temperatures. Their responses are combined in highly informative 4D points that can qualitatively (gas recognition) and quantitatively (concentration estimate) discriminate all the tested gases. Two identical chips were fabricated with tin oxide (SnO2) nanowires decorated with different metal nanoparticles: one decorated with Ag nanoparticles and one with Pt nanoparticles. Support Vector Machine was used as the "brain" of the sensing system. The results show that the systems using these multisensor chips were capable of achieving perfect classification (100%) and good estimation of the concentration of tested gases (errors in the range 8-28%). The Ag decorated sensors did not have a preferential gas, while Pt decorated sensors showed a lower error towards acetone, hydrogen and ammonia. Combination of the two sensor chips improved the overall estimation of gas concentrations, but the individual sensor chips were better for some specific target gases. (C) 2020 Elsevier B.V. All rights reserved.
Subject headings
- NATURVETENSKAP -- Kemi -- Analytisk kemi (hsv//swe)
- NATURAL SCIENCES -- Chemical Sciences -- Analytical Chemistry (hsv//eng)
Keyword
- Gas sensor
- Nanowires
- Tin oxide
- Selectivity
- Machine learning
Publication and Content Type
- ref (subject category)
- art (subject category)
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