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Heavy metals biosensor based on defective one-dimensional phononic crystals. | LitMetric

AI Article Synopsis

Article Abstract

In recent years, the detection of water pollution with low levels of heavy metals has attracted the great attention of many researchers as a result of the imminent danger of this type of pollution to all mankind. Meanwhile, we introduce a theoretical approach based on the one-dimensional phononic crystals (1D-PnCs) with a central defect layer as a novel platform for the highly sensitive detection of heavy metal pollution in freshwater. Therefore, the creation of a resonant peak in the transmittance spectrum related to this defect layer is highly conceivable. In this regard, the detection of cadmium chloride (CdCl) as a dangerous, toxic, and extremely hazardous heavy metal could be investigated based on the small displacement in the position of this resonant peak with the changes in the CdCl concentration. Notably, any change in CdCl concentration has a direct impact on its acoustic properties. The theoretical framework of our research study is essentially based on the 2 × 2 transfer matrix method and the acoustic properties of the constituent materials as well. The optimization of all sensor parameters represents the mainstay of this study to get the best sensor performance. In this regard, the proposed sensor has a remarkably high sensitivity (S = 1904.25 Hz/ppm) over a concentration range of 0 - 10000 ppm. In addition, the sensor has a high quality factor (QF), and figure of merit of 1771.318, and 73529410 (ppm), respectively. Finally, we believe this sensor could be a key component of a feasible platform for detecting low concentrations of different heavy metal ions in freshwater.

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Source
http://dx.doi.org/10.1016/j.ultras.2023.106928DOI Listing

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