Stability and performance of titanium dioxide nanoparticle biosensor platforms for rapid detection of human serum...

The development of electrical biosensors for serum albumin detection has gained significant attention due to their high sensitivity, low cost, and simplicity. However, studies addressing the structural stability and platform regeneration of such sensors remain limited. This study presents a nanoscale titanium dioxide (TiO₂) nanoparticle-based interdigitated electrode (IDE) amperometric biosensor for the rapid detection of human serum albumin (HSA). Molecular docking simulations were first employed to investigate the structural and electrostatic characteristics of the antibody-antigen interface. The simulations confirmed that APTES-functionalized nanostructured TiO₂ IDE surfaces enhance antibody binding stability at pH 7 under the experimental conditions, providing molecular-level validation of the robustness of antibody immobilization on TiO₂ surface. The biosensor's performance was evaluated through electrical current response resulting from the antibody-antigen interaction on a TiO₂ nanoparticle thin-film platform, achieving detection of HSA concentrations ranging from 10 µg mL^-1 down to 1 pg mL^-1, with a coefficient of determination (R ²) of 0.98 and a low limit of detection (LOD) of 0.33 pg mL^-1. Sensor reproducibility was examined using five independently prepared samples, yielding consistent current-voltage (I-V) profiles and relative standard deviation of 9.25% and 12.26% at 1 ng mL^-1 and 1 µg mL^-1 HSA concentrations, respectively. The structural robustness of the sensor platform was further evaluated through controlled surface cleaning. While regeneration has been explored in other biosensor types, systematic electrical evaluation of reused TiO₂ nanoparticle IDE platforms has not been well established. The regenerated devices maintained stable I-V trends and functional detection capability. These findings highlight the promise of TiO₂ nanoparticle IDE systems for cost-effective and resource-limited diagnostic applications.