Cited by 236Nanowire Synthesis and ApplicationsGas Sensing Nanomaterials and SensorsAdvanced Chemical Sensor Technologies

Artificial sensing intelligence with silicon nanowires for ultraselective detection in the gas phase

Open access
Wang, Bin, Cancilla, John C., Torrecilla, Jose S., Haick, Hossam·2014·Nano Letters

Abstract

The use of molecularly modified Si nanowire field effect transistors (SiNW FETs) for selective detection in the liquid phase has been successfully demonstrated. In contrast, selective detection of chemical species in the gas phase has been rather limited. In this paper, we show that the application of artificial intelligence on deliberately controlled SiNW FET device parameters can provide high selectivity toward specific volatile organic compounds (VOCs). The obtained selectivity allows identifying VOCs in both single-component and multicomponent environments as well as estimating the constituent VOC concentrations. The effect of the structural properties (functional group and/or chain length) of the molecular modifications on the accuracy of VOC detection is presented and discussed. The reported results have the potential to serve as a launching pad for the use of SiNW FET sensors in real-world counteracting conditions and/or applications.

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Registry

Crossref · 10.1021/nl404335p

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37 of 37 references verified0 citation errors · 0 not checkable

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  • Using ANN improves the selectivity and sensitivity of sensors in mixtures containing counteracting compounds with similar chemical structures and physical properties.

    “Here, using ANN would improve the selectivity and sensitivity of sensors in mixtures containing counteracting compounds with similar chemical structures and physical properties [216].”

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Authors
Wang, B., Cancilla, J. C., Torrecilla, J. S., & Haick, H.
Affiliations
  • Technion – Israel Institute of Technology (IL)
  • Universidad Complutense de Madrid (ES)
  • Department of Chemical Engineering, Complutense University of Madrid, Madrid 28040, Spain
Corresponding author
Haick, Hossam
Venue
Nano Letters
Published
2014-01-21
Volume
14
Issue
2
Pages
933-938
ISSN
  • 1530-6984 (ISSN-L)
  • 1530-6992
OpenAlex
W2101896997
Cited by
236
References
37
Citations by year
2026: 8 · 2025: 11 · 2024: 13 · 2023: 11 · 2022: 15 · 2021: 22 · 2020: 18 · 2019: 17 · 2018: 32 · 2017: 26 · 2016: 28 · 2015: 26 · 2014: 9
FWCI
15.39
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • Nano Letters (publishedVersion)
  • PubMed (publishedVersion)
  • Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
Funders
  • Council for Higher Education
  • Yükseköğretim Kurulu
  • FP7 Health
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Nanowire Synthesis and Applications
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Gas Sensing Nanomaterials and Sensors
  • Physical Sciences › Engineering › Biomedical Engineering › Advanced Chemical Sensor Technologies
Keywords
silicon nanowire transistors, gas sensing, volatile organic compounds, artificial intelligence, sensor selectivity, molecular functionalization, concentration estimation, functional group effects, chain length effects

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