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      Molecular recognition using receptor-free nanomechanical infrared spectroscopy based on a quantum cascade laser

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          Abstract

          Speciation of complex mixtures of trace explosives presents a formidable challenge for sensors that rely on chemoselective interfaces due to the unspecific nature of weak intermolecular interactions. Nanomechanical infrared (IR) spectroscopy provides higher selectivity in molecular detection without using chemoselective interfaces by measuring the photothermal effect of adsorbed molecules on a thermally sensitive microcantilever. In addition, unlike conventional IR spectroscopy, the detection sensitivity is drastically enhanced by increasing the IR laser power, since the photothermal signal comes from the absorption of IR photons and nonradiative decay processes. By using a broadly tunable quantum cascade laser for the resonant excitation of molecules, we increased the detection sensitivity by one order of magnitude compared to the use of a conventional IR monochromator. Here, we demonstrate the successful speciation and quantification of picogram levels of ternary mixtures of similar explosives (trinitrotoluene (TNT), cyclotrimethylene trinitramine (RDX), and pentaerythritol tetranitrate (PETN)) using nanomechanical IR spectroscopy.

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          Desorption characteristics of uncoated silicon microcantilever surfaces for explosive and common nonexplosive vapors.

          We measured the desorption of explosive trinitrotoluene (TNT), pentaerythritol tetranitrate (PETN), and hexahydro-1,3,5-triazine (RDX) vapors from piezoresistive silicon microcantilevers under ambient air. Depending on the amount of vapor loaded on the cantilever, TNT desorption took a few minutes to tens of minutes (for nanogram quantities). On the other hand, no significant loss of PETN or RDX was observed after many hours. We also measured desorption of common "nonexplosive" compounds (water, acetone, and ethyl alcohol) and observed that desorption was too fast to be measured. There is a good correlation between the desorption time and the melting point (or the vapor pressure) of a particular substance. In principle, this method can be used to measure desorption rates of various substances from cantilever surfaces.
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            Prion protein detection using nanomechanical resonator arrays and secondary mass labeling.

            Nanomechanical resonators have shown potential application for mass sensing and have been used to detect a variety of biomolecules. In this study, a dynamic resonance-based technique was used to detect prion proteins (PrP), which in conformationally altered forms are known to cause neurodegenerative diseases in animals as well as humans. Antibodies and nanoparticles were used as mass labels to increase the mass shift and thus amplify the frequency shift signal used in PrP detection. A sandwich assay was used to immobilize PrP between two monoclonal antibodies, one of which was conjugated to the resonator's surface while the other was either used alone or linked to the nanoparticles as a mass label. Without additional mass labeling, PrP was not detected at concentrations below 20 microg/mL. In the presence of secondary antibodies the analytical sensitivity was improved to 2 microg/mL. With the use of functionalized nanoparticles, the sensitivity improved an additional 3 orders of magnitude to 2 ng/mL.
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              Evaluation of multitransducer arrays for the determination of organic vapor mixtures.

              A study of vapor recognition and quantification by polymer-coated multitransducer (MT) arrays is described. The primary data set consists of experimentally derived sensitivities for 11 organic vapors obtained from 15 microsensors comprising five cantilever, capacitor, and calorimeter devices coated with five different sorptive-polymer films. These are used in Monte Carlo simulations coupled with principal component regression models to assess expected performance. Recognition rates for individual vapors and for vapor mixtures of up to four components are estimated for single-transducer (ST) arrays of up to five sensors and MT arrays of up to 15 sensors. Recognition rates are not significantly improved by including more than five sensors in an MT array for any specific analysis, regardless of difficulty. Optimal MT arrays consistently outperform optimal ST arrays of similar size, and with judiciously selected 5-sensor MT arrays, one-third of all possible ternary vapor mixtures are reliably discriminated from their individual components and binary component mixtures, whereas none are reliably determined with any of the ST arrays. Quaternary mixtures could not be analyzed effectively with any of the arrays. A "universal" MT array consisting of eight sensors is defined, which provides the best possible performance for all analytical scenarios. Accurate quantification is predicted for correctly identified vapors.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                23 January 2013
                2013
                : 3
                : 1111
                Affiliations
                [1 ]Department of Chemical and Materials Engineering, University of Alberta , Edmonton, AB T6G 2V4, Canada
                [2 ]Department of Chemical Engineering, Pohang University of Science and Technology , Pohang, South Korea
                [3 ]These authors contributed equally to this work.
                Author notes
                Article
                srep01111
                10.1038/srep01111
                3552270
                23346368
                da0fa72a-4207-4893-9df6-757ff1250634
                Copyright © 2013, Macmillan Publishers Limited. All rights reserved

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/

                History
                : 22 October 2012
                : 11 December 2012
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