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Reference type: Journal
Authors: Lu W, Dong X, Qiu LL, Yan ZQ, Meng ZH, Xue M, He X, Liu XY
Article Title: Colorimetric sensor arrays based on pattern recognition for the detection of nitroaromatic molecules.
Publication date: 2017
Journal: Journal of Hazardous Materials
Volume: 326
Page numbers: 130-137.
DOI: 10.1016/j.jhazmat.2016.12.024
Alternative URL: http://www.sciencedirect.com/science/article/pii/S0304389416311657

Abstract: This research demonstrated that, in a colorimetric sensor array, 2,4,6-trinitrotoluene (TNT), 2,6-dinitrotoluene (2,6-DNT), 2,4-dinitrotoluene (2,4-DNT) and 4-nitrotoluene (4-MNT) were identifiable through a unique pattern in a qualitative and semi-quantitative manner. The adsorption capacity of the molecularly imprinted colloidal particles (MICs) for their corresponding templates was 0.27 mmol TNT/g, 0.22 mmol 2,6-DNT/g, 0.31 mmol 2,4-DNT/g and 0.16 mmol 4-MNT/g, respectively. Every optical sensor utilized in the arrays contained three-dimensional molecularly imprinted photonic crystal (MIPC) sensor with different imprinted templates. The intelligent materials can display different colors from green to red to 20 mM corresponding nitroaromatics with varying diffraction red shifts of 84 nm (TNT), 46 nm (2,6-DNT), 54 nm (2,4-DNT) and 35 nm (4-MNT), respectively. With the assistance of principal component analysis (PCA) and rational design, the sensor array can illustrate the influence of the nitryl quantity and generate a separate response region of nitroaromatics for pattern recognition with 95.25% of variance explained in the measurements by the first three principal components (PCs). The statistical analysis endowed the cross-reactive array with better classification and identification ability and this novel detection platform provided a wider applied range among other harmful chemicals in a simple sensor array with customized functionality
Template and target information: 2,4,6-trinitrotoluene, TNT, 2,6-dinitrotoluene, 2,6-DNT, 2,4-dinitrotoluene, 2,4-DNT, 4-nitrotoluene, 4-MNT
Author keywords: pattern recognition, Principal component analysis (PCA), Photonic crystal (PhC), molecular imprinting, nitroaromatics


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