Probing antibody surface density and analyte antigen incubation time as dominant parameters influencing the antibody-antigen recognition events of a non-faradaic and diffusion-restricted electrochemical immunosensor.

Electrochemical sensors based on antibody-antigen recognition events are commonly used for the rapid, label-free, and sensitive detection of various analytes. However, various parameters at the bioelectronic interface, i.e., before and after the probe (such as an antibody) assembly onto the electrode, have a dominant influence on the underlying detection performance of analytes (such as an antigen). In this work, we thoroughly investigate the dependence of the bioelectronic interface characteristics on parameters that have not been investigated in depth: the antibody density on the electrode's surface and the antigen incubation time. For this important aim, we utilized the sensitive non-faradaic electrochemical impedance spectroscopy method. We showed that as the incubation time of the antigen-containing drop solution increased, a decrease was observed in both the solution resistance and the diffusional resistance with reflecting boundary elements, as well as the capacitive magnitude of a constant phase element, which decreased at a rate of 160 ± 30 kΩ/min, 800 ± 100 mΩ/min, and 520 ± 80 pF × s(α-1)/min, respectively. Using atomic force microscopy, we also showed that high antibody density led to thicker electrode coating than low antibody density, with root-mean-square roughness values of 2.2 ± 0.2 nm versus 1.28 ± 0.04 nm, respectively. Furthermore, we showed that as the antigen accumulated onto the electrode, the solution resistance increased for high antibody density and decreased for low antibody density. Finally, the antigen detection performance test yielded a better limit of detection for low antibody density than for high antibody density (0.26 μM vs 2.2 μM). Overall, we show here the importance of these two factors and how changing one parameter can drastically affect the desired outcome. Graphical abstract.