2011
DOI: 10.1016/j.talanta.2011.06.062
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Modifying the response of a polymer-based quartz crystal microbalance hydrocarbon sensor with functionalized carbon nanotubes

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Cited by 35 publications
(23 citation statements)
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“…At increased plasticizer levels (i.e., 25% w/w), the sensitivities of both plasticizer−PMMA composites were found to be in agreement with log P trends, suggesting that hydrophobic interactions may be the predominate sensing mechanism. Compared to the rubbery polymers studied elsewhere under similar experimental conditions, 25 the hydrocarbon sensitivity and log P correlations for the plasticizer−PMMA composites were somewhat lower (r 2 = 0.7941 for DOP−PMMA and r 2 = 0.7646 for DOS−PMMA), implying that the PMMA response mechanism is also dependent on other factors which will be discussed later. No significant differences were observed in the response times for the different plasticizers.…”
Section: ■ Results and Discussionmentioning
confidence: 61%
“…At increased plasticizer levels (i.e., 25% w/w), the sensitivities of both plasticizer−PMMA composites were found to be in agreement with log P trends, suggesting that hydrophobic interactions may be the predominate sensing mechanism. Compared to the rubbery polymers studied elsewhere under similar experimental conditions, 25 the hydrocarbon sensitivity and log P correlations for the plasticizer−PMMA composites were somewhat lower (r 2 = 0.7941 for DOP−PMMA and r 2 = 0.7646 for DOS−PMMA), implying that the PMMA response mechanism is also dependent on other factors which will be discussed later. No significant differences were observed in the response times for the different plasticizers.…”
Section: ■ Results and Discussionmentioning
confidence: 61%
“…Although organic solvents (i.e., methanol) have been used to disperse and stabilize the VOC during the preparation of stock standard solutions (Kraft and Mizaikoff, 2000;Lima et al, 2011), we avoided their use in this study in order to minimize potential issues that may arise from solvent/matrix effects during the measurement of complex samples. Previous GC-MS studies by us have shown that the loss during the preparation of the BTEX standards directly in deionized water can vary between 20% and 60%, and this depended on the type of hydrocarbon, the concentration and the method of preparation (i.e., vigorous shaking versus ultrasonication, storage time prior to analysis) (Pejcic et al, 2011b). To limit losses by volatility and degradation, all standards were prepared freshly and ATR-FTIR studies were performed within 5 h. All of the standards used in the construction of the calibration curves in the ATR-FTIR studies have been verified using GC-MS.…”
Section: Instrumentation and Sensor Calibrationmentioning
confidence: 99%
“…Over the past several decades there has been significant interest in using chemical sensors to address these and other environmental monitoring issues (Lawrence, 2006;Lieberzeit and Dickert, 2007). Although many sensors are suitable for measuring hydrocarbon concentrations at very low levels (i.e., ppb to ppm or lg/l to mg/ l), the majority of these devices struggle to separate the various signal contributions during the analysis of multi-component hydrocarbon mixtures (Ueyama et al, 2002;Pejcic et al, 2011b). Analyte selectivity remains a major challenge impeding the acceptance of most sensors for assaying complex geochemical and environmental samples.…”
Section: Introductionmentioning
confidence: 99%
“…QCMs have been proven to be reliable in the field of electrochemistry (Paulo Tde et al, 2013; Sun et al, 2013a, 2013b), in petroleum characterization (Pejcic et al, 2011; Ueyama et al, 2002), in environmental chemistry (Nicolini et al, 2012), material science (Pei et al, 2010) and more interestingly in the development of biosensors (Bouchet-Spinelli et al, 2013; Eom et al, 2013; Guntupalli et al, 2013; Wangchareansak et al, 2013) which are valuable for disease diagnosis. QCMs also found a great interest in the monitoring of the affinity constants defining a given substrate-ligand interaction (Lebed et al, 2006; Li et al, 2013; Mori et al, 2009; Tan et al, 2013).…”
Section: Introductionmentioning
confidence: 99%