Fig 1.
The schematic of the proposed biosensor’s fabrication.
Fig 2.
An equivalent Randles circuit model was used to fit the impedance spectra of the Mn:ZnS-CH/IDE biosensor in detecting tetracycline.
Fig 3.
(A) SEM image acquired using a HITACHI S-4800 system (Hitachi High-Tech, Japan) and (B) HRTEM image captured using a JEM 2100 microscope (JEOL Ltd., Japan) of the prepared materials.
Fig 4.
SEM images acquired using a HITACHI S-4800 system (Hitachi High-Tech, Japan) of the coated interdigitated electrodes.
(A) top-view image of the electrodes, with a higher-magnification zoom-in of a selected region on a representative single electrode finger shown in the lower corner; (B) side-view (cross-sectional) image of the coated electrodes.
Fig 5.
(A) XRD patterns acquired using a Rigaku MiniFlex 600 diffractometer (Rigaku Europe SE, Germany) and (B) EDX spectrum obtained using a HITACHI S-4800 system (Hitachi High-Tech, Japan) for the prepared materials.
Fig 6.
FTIR spectrum of the prepared materials acquired using a Jasco FTIR-4600 spectrometer (Jasco, Japan).
Fig 7.
Nyquist plots of Mn:ZnS-CH-based biosensors in deionized water at different tetracycline concentrations.
(A) 62.5 nM, (B) 125 nM, (C) 250 nM, (D) 500 nM, and (E) 1000 nM. The blue symbols represent the experimental data, and the red curves are the fitted responses obtained using the Randles equivalent circuit model shown in Fig 2.
Table 1.
Fitted impedance parameters and analytical metrics of the tetracycline biosensor at various concentrations, including Rct, ΔRct relative to the blank, χ², SNR, and CV, expressed as mean ± SD (n = 9, three replicates).
Fig 8.
Charge transfer resistance Rct of the biosensor as a function of the logarithm of tetracycline concentration, showing a linear calibration relationship.
Fig 9.
Schematic illustration of the proposed biosensor interface and its interaction with tetracycline molecules.
Fig 10.
Change in charge-transfer resistance Rct as a function of the logarithm of TET concentration for the proposed Mn:ZnS-CH biosensor and the Mn:ZnS-based sensor in DI water.
Error bars represent the standard deviations of three replicate measurements.
Table 2.
Validation of the calibration curve.
Table 3.
Linear regression equations for the proposed sensors at different analyte concentrations.
Fig 11.
Selectivity of the proposed sensor.
(A) Change in charge-transfer resistance Rct as a function of the logarithm of concentration logC for the proposed biosensor exposed to different antibiotics. (B) Corresponding linear correlation coefficients between Rct and logC for each antibiotic.
Table 4.
Fitted charge-transfer resistance Rct of sensors exposed to 250 nM TET at different time points.
Fig 12.
The change in Rct values with logC when the proposed sensors are exposed to TET in different water matrices.
Table 5.
Linear calibration parameters of the proposed biosensor for tetracycline detection in different media.