Detection of heavy metals using one-dimensional gyroidal photonic crystals for effective water treatment

Abstract

In the past century, industrial and technological improvements lead to a significant increase in water contamination with aqueous solutions of heavy metals ions. In this regard, the detection and monitoring of these dangerous solutions received considerable attention based on some chemical and physical techniques. However, these techniques are suffering from the sophisticated instrumentation, time-consuming, high cost, and complicated chemical processes despite their relatively high sensitivity and low detection limits. Therefore, we have introduced in this study a simple and efficient sensing tool based on the one-dimension gyroidal photonic crystals for detecting various types of heavy metal ions. Here, the designed photonic crystal model is composed of a distinct number of unit cells each one contains two layers of gyroidal Ag and TiO2. The mainstay of this research is focused on the appearance of sharp resonant mode inside the reflectance spectrum due to the inclusion of a defect layer in the middle of the designed photonic crystal. Each resonant dip is substantially reveals to a specific concentration or type of the heavy metal ions. Therefore, the shift in the wavelength of this resonant dip is related to any change in the concentration or type of the heavy metal ion in the contaminated water. Based on Drude model, gyroidal configuration and transfer matrix method, the theoretical formulism of this study is calculated and discussed. The numerical results demonstrate the ability of the suggested sensor in distinguishing between two important and dangerous types of heavy metals such as Cu2+ and Mg2+. Here, the findings of such a design showed that the sensitivity for both Cu2+ and Mg2+ can reach the values of 573.5 nm/RIU and 570.7 nm/RIU, respectively. Moreover, the suggested design provides higher values of the quality factor in the range from 30833 to 137275 with a minimum value of the resolution (0.0006). Thus, these findings may introduce simple and accurate tool for the detection of water contamination with heavy metals aqueous solutions with relatively high performance.