When solvent inks, inks and adhesives dry out, they can emit volatile organic compounds (VOCs) that can adversely affect health. Typically, one such VOC is xylene, which exists as three isomers with the same elements but slightly different layouts. Because isomers are very similar, they are difficult to control individually. Now researchers report in ACS sensors developed an electric nose (“electronic nose”) with a porous organometallic framework (MOF) that can accurately distinguish mixtures of xylene isomers.
Xylene, sometimes called xylene, is harmful when large amounts are inhaled or absorbed through the skin. Each isomer, Fr.-xylene, m-xylene and p-xylene, interacts differently in humans and other mammals, so it is important to monitor the environment for each isomer, not just their cumulative presence. Previously, researchers used gas chromatographic analysis to identify three forms of xylene. But this procedure requires large tools that are expensive, and the analysis is time consuming. Thus, Lars Heinke and his colleagues wanted to know whether MOF films could be included in simpler, faster sensors to detect and measure the presence of each isomer separately in air.
The researchers prepared six different porous MOF films that are known to adsorb xylene isomers, and applied them to gravimetric sensors in an array called an “electronic nose”. In initial experiments, the team showed that MOF films have different sensitivities Fr.-xylene, m-xylene and p-xylene. They then tested the ability of the electronic nose to distinguish xylene isomers in mixtures at concentrations of 10 ppm and 100 ppm, which is the exposure limit of the U.S. National Institutes of Safety and Health. After analyzing the sensor array data using a machine learning algorithm, the team was able to determine the composition of the mixtures with an accuracy of 86% for a mixture of 10 ppm and with an accuracy of 96% for a mixture of 100 ppm. Researchers say the MOF-based e-nose is a simple device for distinguishing three forms of xylene in environmental monitoring and diagnostic health tests.
The authors acknowledge funding from the Alexander von Humboldt Foundation, the China Scholarship Council (CSC) and the Deutsche Forschungsgemeinschaft.
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