2012
DOI: 10.1016/j.proeng.2012.09.411
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Detection of Explosives based on the Work Function Read-out of Molecularly Imprinted Polymers

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Cited by 4 publications
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“…Molecularly imprinted polymers (MIPs) principally have this advantage, offering specific molecular recognition sites, and can be used as selective recognition elements in sensors [19,20]. Selective detection of TNT without pre-separation by means of MIPs was already demonstrated using a mass sensitive readout [21] and other techniques [22,23], including electrochemical [24] and optical readouts via fiber or interferometer structures [25,26,27]. Nevertheless, with most of the described techniques, TNT concentrations in the lower ppb range are still hardly measurable.…”
Section: Introductionmentioning
confidence: 99%
“…Molecularly imprinted polymers (MIPs) principally have this advantage, offering specific molecular recognition sites, and can be used as selective recognition elements in sensors [19,20]. Selective detection of TNT without pre-separation by means of MIPs was already demonstrated using a mass sensitive readout [21] and other techniques [22,23], including electrochemical [24] and optical readouts via fiber or interferometer structures [25,26,27]. Nevertheless, with most of the described techniques, TNT concentrations in the lower ppb range are still hardly measurable.…”
Section: Introductionmentioning
confidence: 99%
“…Due to the high mechanical strength and flexibility, molecularly imprinted polymers (MIPs) were recently utilized to fabricate highly sensitive, selective and cost-effective molecular recognition materials [14][15][16][17]. Referred to as antibody mimics, the artificial materials contain thousands to millions of target-shaped cavities, which could bind specific molecules [18][19][20][21] and reduce the cross-absorptivity of the targets' analogues. And the state of MIPs have been used to enable TNT detection through the use of fluorescence [22,23], quartz crystal microbalance (QCM) [24,25], and surface plasma resonance measurements [26].…”
Section: Introductionmentioning
confidence: 99%