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 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 (<5 %) were obtained for the concentration prediction of newly prepared FQs. This study demonstrates the promising prospect of applying the multiband TMS combined with the MRR-CSF framework for accurate biochemical sensing and detection. • A multi-band THz metamaterial sensor was prepared for trace FQs detection. • A multivariate fusion framework was proposed to enhance detection accuracy. • The proposed method outperformed all univariate regressions in improving accuracy. • The detection limit of antibiotic reached 5 ng/L by proposed method. [ABSTRACT FROM AUTHOR]