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      Vapor Trace Recognition Using a Single Nonspecific Chemiresistor

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          Abstract

          An application of spectral analysis to the transient response signals of ALD-fabricated conductometric sensors (chemiresistors) upon exposure to short vapor pulses is discussed. It is based on the representation of a response curve in the frequency domain, followed by the multi-dimensional Quadratic Discriminant Analysis (QDA) for analyte identification. Compared to the standard steady-state amplitude analysis, this technique does not depend on a short-term sensor drift, does not have limitations for the number of extracted features and has a strict physical validation. Effective recognition of some relatively simple combustible analytes (acetone, toluene, ethanol) was demonstrated using a single nonspecific chemiresistor.

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          Enhanced gas sensing by individual SnO2 nanowires and nanobelts functionalized with Pd catalyst particles.

          The sensing ability of individual SnO(2) nanowires and nanobelts configured as gas sensors was measured before and after functionalization with Pd catalyst particles. In situ deposition of Pd in the same reaction chamber in which the sensing measurements were carried out ensured that the observed modification in behavior was due to the Pd functionalization rather than the variation in properties from one nanowire to another. Changes in the conductance in the early stages of metal deposition (i.e., before metal percolation) indicated that the Pd nanoparticles on the nanowire surface created Schottky barrier-type junctions resulting in the formation of electron depletion regions within the nanowire, constricting the effective conduction channel and reducing the conductance. Pd-functionalized nanostructures exhibited a dramatic improvement in sensitivity toward oxygen and hydrogen due to the enhanced catalytic dissociation of the molecular adsorbate on the Pd nanoparticle surfaces and the subsequent diffusion of the resultant atomic species to the oxide surface.
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            Pattern analysis for machine olfaction: a review

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              Pattern Recognition and Machine Learning (

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                Sensors (Basel, Switzerland)
                Molecular Diversity Preservation International (MDPI)
                1424-8220
                July 2013
                12 July 2013
                : 13
                : 7
                : 9016-9028
                Affiliations
                Department of Physics and Astronomy, Western Kentucky University, Bowling Green, KY 42101, USA; E-Mails: alexander.larin375@ 123456topper.wku.edu (A.L.); dewayne.sowell363@ 123456topper.wku.edu (D.S.)
                Author notes
                [* ] Author to whom correspondence should be addressed; E-Mail: vladimir.dobrokhotov@ 123456wku.edu .
                Article
                sensors-13-09016
                10.3390/s130709016
                3758634
                23857265
                615c008e-e817-40d3-8fdb-200ef2f40e96
                © 2013 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                : 29 May 2013
                : 27 June 2013
                : 08 July 2013
                Categories
                Article

                Biomedical engineering
                sensor,electronic nose,pattern recognition,transient response,lda,qda,73.63.bd,73.63.rt
                Biomedical engineering
                sensor, electronic nose, pattern recognition, transient response, lda, qda, 73.63.bd, 73.63.rt

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