A terahertz multi-band metamaterial absorber and its synthetic evaluation method based on multivariate resonant response fusion for trace pesticide detection

Qu, Fangfang; Lin, Lei; Chen, Zhuoyi; Abdalla, Alwaseela; Nie, Ping

doi:10.1016/j.snb.2021.129726

Cited by 18 publications

(4 citation statements)

References 22 publications

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“…The covariance function is a symmetric function that satisfies the Mercer condition, such as the square exponential covariance function and the Matern5/2 covariance function. The covariance function selected in this paper is Matern5/2 (Qu et al, 2021).…”

Section: Gaussian Process Regressionmentioning

confidence: 99%

Yield prediction and water‐nitrogen management of Chinese jujube based on machine learning

Tao

Zeng

et al. 2023

Irrigation and Drainage

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Jujubes are a crucial characteristic industry in China. Predicting jujube production in various regions of China is significant to developing the jujube industry. This study aims to predict jujube yields across China by machine learning and optimize water‐nitrogen applications to achieve the highest yields. We utilized four machine learning methods (i.e., linear regression, support vector machine, ensemble learning and Gaussian process regression) to create predictive models based on the jujube production, irrigation, fertilization and planting density data sets. The results showed that the Gaussian process regression model best predicted jujube yield by comparing the predicted and measured data. The ensemble learning and Gaussian process regression model best optimized the optimal water and nitrogen application range. On the whole, the Gaussian process regression model is more suitable for yield prediction and water‐nitrogen management. The water‐nitrogen coupling function based on the Gaussian process regression model for predicting jujube yield in Xinjiang, Gansu and Shaanxi was developed to make suitable irrigation and fertilizer regimes. This study can provide a theoretical basis for predicting jujube production and water‐nitrogen management in China.

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Section: Gaussian Process Regressionmentioning

confidence: 99%

Yield prediction and water‐nitrogen management of Chinese jujube based on machine learning

Tao

Zeng

et al. 2023

Irrigation and Drainage

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“…Most of the THz absorbers researched in the literatures operate at frequencies beyond 1.0 THz; however, since many high-power THz sources based on opto-electronics technology are working at a frequency range below 1.0 THz [22][23][24][25]62], it is essential to design a device that has optical absorption for both TE and TM polarization modes in the frequency range of the sub-THz band. Our multi-band proposed microstructure design operates below 1 THz, having N-band absorption peak resonances, which is so valuable in high-power THz sources and optical sensing and detection applications.…”

Section: Spectral Responsesmentioning

confidence: 99%

“…Therefore, multi-band absorbers have also been designed in GHz [20], THz [21][22][23][24][25], nearinfrared (NIR) [3,26,27], visible [28,29], far-infrared (FIR) [30], mid-infrared (MIR) [31,32], and infrared (IR) [33][34][35] ranges.…”

Section: Introductionmentioning

confidence: 99%

“…Associated with metasurface research and applications, it is essential to facilitate metasurface designs to be of the utmost flexible properties. Most of the multi-band THz absorber designed structures work at frequencies over 1.0 THz [22][23][24][25]62], while most of the high-power THz sources, based on opto-electronics technology, operate at the frequency range of the sub-THz band; therefore, it is essential to design THz absorber structures that have optical absorbance peaks in the frequency range below 1 THz.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cost-Effective Bull’s Eye Aperture-Style Multi-Band Metamaterial Absorber at Sub-THz Band: Design, Numerical Analysis, and Physical Interpretation

Vafapour

2022

Sensors

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Theoretical and numerical studies were conducted on plasmonic interactions at a polarization-independent semiconductor–dielectric–semiconductor (SDS) sandwiched layer design and a brief review of the basic theory model was presented. The potential of bull’s eye aperture (BEA) structures as device elements has been well recognized in multi-band structures. In addition, the sub-terahertz (THz) band (below 1 THz frequency regime) is utilized in communications and sensing applications, which are in high demand in modern technology. Therefore, we produced theoretical and numerical studies for a THz-absorbing-metasurface BEA-style design, with N-beam absorption peaks at a sub-THz band, using economical and commercially accessible materials, which have a low cost and an easy fabrication process. Furthermore, we applied the Drude model for the dielectric function of semiconductors due to its ability to describe both free-electron and bound systems simultaneously. Associated with metasurface research and applications, it is essential to facilitate metasurface designs to be of the utmost flexible properties with low cost. Through the aid of electromagnetic (EM) coupling using multiple semiconductor ring resonators (RRs), we could tune the number of absorption peaks between the 0.1 and 1.0 THz frequency regime. By increasing the number of semiconductor rings without altering all other parameters, we found a translation trend of the absorption frequencies. In addition, we validated our spectral response results using EM field distributions and surface currents. Here, we mainly discuss the source of the N-band THz absorber and the underlying physics of the multi-beam absorber designed structures. The proposed microstructure has ultra-high potentials to utilize in high-power THz sources and optical biomedical sensing and detection applications based on opto-electronics technology based on having multi-band absorption responses.

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Ultrahigh sensitivity nitrogen-doping carbon nanotubes-based metamaterial-free flexible terahertz sensing platform for insecticides detection

Zhang

Liu

et al. 2022

Food Chemistry

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A terahertz multi-band metamaterial absorber and its synthetic evaluation method based on multivariate resonant response fusion for trace pesticide detection

Cited by 18 publications

References 22 publications

Yield prediction and water‐nitrogen management of Chinese jujube based on machine learning

Yield prediction and water‐nitrogen management of Chinese jujube based on machine learning

Cost-Effective Bull’s Eye Aperture-Style Multi-Band Metamaterial Absorber at Sub-THz Band: Design, Numerical Analysis, and Physical Interpretation

Ultrahigh sensitivity nitrogen-doping carbon nanotubes-based metamaterial-free flexible terahertz sensing platform for insecticides detection

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