A multiband terahertz metamaterial sensor evaluated using a multiresponse variable fusion framework for the precise detection of trace fluoroquinolone antibiotics
A specific structural multiband terahertz (THz) metamaterial sensor (TMS) was designed herein to improve the sensitivity of detecting multiple trace fluoroquinolone (FQ) antibiotics in water, and a multiple resonance response competition and selection fusion (MRR-CSF) framework was proposed for accu...
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Veröffentlicht in: | Sensors and actuators. B, Chemical Chemical, 2024-11, Vol.419, p.136446, Article 136446 |
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Sprache: | eng |
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Zusammenfassung: | A specific structural multiband terahertz (THz) metamaterial sensor (TMS) was designed herein to improve the sensitivity of detecting multiple trace fluoroquinolone (FQ) antibiotics in water, and a multiple resonance response competition and selection fusion (MRR-CSF) framework was proposed for accurate FQ analysis. The TMS based on three-concentric C4-symmetrical split-ring (TC4) structures generated five bands at 0.797, 0.900, 1.097, 1.198, and 1.777 THz. The multiband resonance signals for three types of FQs, including enrofloxacin (ENR), pefloxacin (PEF), and nadifloxacin (NAD), were detected by the TMS, which increased as the antibiotic concentrations increased (5–140 ng/L). The proposed method can solve the problems of low accuracy and poor robustness of conventional single-response regression by combining selected and fused TMS-effective resonance response variables with three multivariate regression strategies. The calculated comprehensive metrics also provide an objective evaluation of multiband TMS performance. The designed TMS combined with the proposed MRR-CSF framework showed 21 %–27 %, 13 %–17 %, and 12 %–13 % improvements in the detection accuracy for ENR, PEF, and NAD, respectively, according to the univariate regression results. The limit of detection for the ENR, PEF, and NAD antibiotic solutions was achieved at 5 ng/L, and the reliable range of recoveries (100 % ± 25 %), average recoveries (>90 %), and relative standard deviation values ( |
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ISSN: | 0925-4005 |
DOI: | 10.1016/j.snb.2024.136446 |