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Field-effect transistor array modified by a stationary phase to generate informative signal patterns for machine learning-assisted recognition of gas-phase chemicals

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Abstract

We propose an artificial intelligence-based chemical-sensing system integrating a porous gate field-effect transistor (PGFET) array modified by gas chromatography stationary phase materials and machine-learning techniques. The chemically sensitive PGFET array generates cross-reactive signals for computational analysis and shows potential for applications to compact intelligent sensing devices, including mobile electronic noses.

Graphical abstract: Field-effect transistor array modified by a stationary phase to generate informative signal patterns for machine learning-assisted recognition of gas-phase chemicals

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Publication details

The article was received on 21 Nov 2018, accepted on 16 Jan 2019 and first published on 18 Jan 2019


Article type: Communication
DOI: 10.1039/C8ME00097B
Citation: Mol. Syst. Des. Eng., 2019, Advance Article

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    Field-effect transistor array modified by a stationary phase to generate informative signal patterns for machine learning-assisted recognition of gas-phase chemicals

    T. Yoshizumi, T. Goda, R. Yatabe, A. Oki, A. Matsumoto, H. Oka, T. Washio, K. Toko and Y. Miyahara, Mol. Syst. Des. Eng., 2019, Advance Article , DOI: 10.1039/C8ME00097B

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