Multiband terahertz metamaterial perfect absorber for microorganisms detection

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Abstract

We report a multi-resonant terahertz (THz) metamaterial perfect absorber (MPA)-based biosensor in the working frequency range of 0 - 3.8 THz for sensing of microorganisms (such as fungi, yeast) and wheat pesticides. Nearly 100 % absorption is realized at f1= 1.7 THz, f2= 2.8 THz, f3= 3.2 THz, and f4= 3.5 THz . We designed our THz MPA sensor making resonators’ gap area compatible with the microorganisms’ size. To obtain optimum performance of the MPA, a mapping of amplitudes and shifts in the absorption resonance peaks with different structural parameters of the resonators is carried out. A very high-frequency shift is obtained for microorganisms such as Penicillium chrysogenum (fungi), yeast, and pesticides (Imidacloprid, N, N-Diethyldithiocarbamate sodium salt trihydrate, Daminozide, N, N-Diethyldithiocarbamate sodium salt hydrate, and Dicofol). An equivalent circuit model using Advance Design System (ADS) software is developed. The calculated results through the model show similar trends as obtained in the simulations using CST. Investigations of the effect of incidence angle of THz wave on the absorption spectra of the MPA are also carried out. It is found that incidence angle does not impact the stability of the lower resonance absorption peak (1.79THz). Due to the wide working frequency range, the proposed sensor is extremely suitable for the detection of all range of pesticides because their specific absorption fingerprint lies in the frequency range of 0–3.8THz. We believe that our sensor could be a potential detection tool for detecting pesticide residues in agriculture and food products. The THz MPA-based biosensor is capable of detecting a very small change in the effective dielectric constant of the MPA environment. Therefore, it can also offer huge opportunities in label-free biosensing for future biomedical applications.

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APA

Bhati, R., & Malik, A. K. (2023). Multiband terahertz metamaterial perfect absorber for microorganisms detection. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-46787-5

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