Saturday, July 20, 2024

E-nose That Sniffs Organic Compounds

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Researchers have developed an electric nose (“e-nose”) with porous metal-organic framework (MOF) films that can accurately differentiate xylene isomer combinations, according to his paper published in ACS Sensors.

An “e-nose” MOF-based sensor accurately distinguishes o-xylene, m-xylene and p-xylene from mixtures. (Credit: Peng Qin)

When paint thinner, ink, and adhesives dry, volatile organic compounds (VOCs) are released, which can be harmful to one’s health. One of the most common VOCs is xylene, which comes in three distinct isomers with the same components but slightly different configurations. Because the isomers are so similar, it’s difficult to keep track of them separately.

If large amounts of xylene, also known as xylol, are inhaled or absorbed through the skin, it can be harmful. Because each isomer, o-xylene, m-xylene, and p-xylene, interacts differently in humans and other mammals, it’s critical to keep an eye on the environment for each one, rather than just the total amount. The three types of xylene were previously identified via gas chromatography analysis. However, this process necessitates the use of huge, expensive apparatus, and the analyses are time consuming. In order to detect and analyse the presence of each isomer independently in the air, Lars Heinke and colleagues wanted to test if MOF films could be included into simple, quicker sensors.

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Six distinct porous MOF films known to adsorb xylene isomers were produced and attached on gravimetric sensors in an array termed a “e-nose” by the researchers. Initial tests revealed that the MOF films were sensitive to o-xylene, m-xylene, and p-xylene in distinct ways. The e-ability nose’s to detect xylene isomers within mixtures was next evaluated at concentrations of 10 ppm and 100 ppm, which is the exposure limit set by the US National Institute for Occupational Safety and Health.

The team was able to estimate the composition of the mixtures with 86 percent accuracy for the 10-ppm combination and 96 percent accuracy for the 100-ppm mixture using sensor array data and a machine learning technique. The MOF-based e-nose, according to the researchers, is a simple device for distinguishing between the three types of xylene in environmental monitoring and diagnostic health testing.


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