Nanosensors for detection of volatile organic compounds

Abstract

Nearly every day, enormous amounts consequent to volatile organic compounds seem to be released into the atmosphere via either natural or manmade origins. One of the significant unknowns within the quantitative forecast of the whole earth’s atmosphere on a broad basis as well as in the knowledge regarding regional air quality is the development of gaseous or particulate byproducts induced by volatile organic compounds (VOC) oxidation. VOCs are a varied group of chemical compounds and due to their varying lipophilicity and volatility, along with their decreased molecular size plus lack of charge, their rapid absorption is allowed into the lungs, tracts, and surfaces like epidermal which may cause both short- and long-term detrimental health implications. Understanding the origins of VOCs, their distribution in the environment, and indeed the biochemical mechanisms that eliminate those chemicals from the environment are critical for modeling and controlling their impact. Techniques and devices for extraction and analyzing volatile organic compounds have been developed from classical to modern sensing in recent years to broaden the spectrum for observable VOC substances, there are associated detection limits with great precision, sensitivity, and cost-effectiveness of the device. This chapter illustrates how sensing methods have been proven to provide significant gains over traditional approaches while also meeting the demand for quality accessing equipment. Targeting the apparent or prospective risks associated with VOC emissions, contemporary nanosensors evolved to become a major priority. Various materials, such as conducting polymers, metallic nanoparticles, metal oxide nanoparticles, and other carbons with their ternary composites, are also used to create VOC sensors that use composite nanoarchitectures to provide advantages such as detection down to very low concentrations (ppm–ppb), higher reproducibility with faster reflexes, and mechanical stability. © 2023 Elsevier Inc. All rights reserved.