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Array-to-array transfer of an artificial nose classifier.

S E Stitzel1, L J Cowen, K J Albert

  • 1Department of Chemistry, Tufts University, Medford, Massachusetts 02155, USA.

Analytical Chemistry
|November 28, 2001
PubMed
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This study introduces a simple microsphere sensor technology for creating reproducible vapor sensor arrays. These arrays, combined with a generalized Whitney-Mann-Wilcoxen classifier, accurately detect nitroaromatic compounds even in complex mixtures.

Area of Science:

  • Chemical sensing technologies
  • Materials science and engineering
  • Machine learning for chemical detection

Background:

  • Vapor sensor arrays require reproducible fabrication for reliable performance.
  • Discriminating specific compounds in complex vapor mixtures is challenging.
  • Artificial nose technologies benefit from robust and transferable classification models.

Purpose of the Study:

  • To demonstrate a simple and reproducible fabrication method for microsphere sensor arrays.
  • To evaluate the performance of a generalized Whitney-Mann-Wilcoxen classifier for nitroaromatic compound detection.
  • To assess the transferability of trained classification models across different sensor arrays over time.

Main Methods:

  • Fabrication of billions of highly reproducible microsphere sensors.

Related Experiment Videos

  • Development and application of a generalized Whitney-Mann-Wilcoxen (GWMW) classifier.
  • Training the GWMW classifier on one sensor array and testing on subsequent arrays.

    • Main Results:

    • Microsphere sensor fabrication is uncomplicated and yields reproducible results.
    • The GWMW classifier achieved high correct classification rates (98.2% and 93.7%) for nitroaromatic compounds.
    • Successful transfer of training data between sensor arrays, even after six months.

    Conclusions:

    • Microsphere sensor technology offers a viable platform for reproducible vapor sensing.
    • The GWMW classifier demonstrates robust performance and excellent transferability for chemical detection.
    • This approach advances the capabilities of fluorescence-based artificial nose systems.