Unbiased Glucose Biosensing Based on a Schottky Junction Comprised of Au Nanoparticle-Decorated TiO2-Coated Al Films

Abstract

Photoelectrochemical (PEC) biosensors show great potential in biochemical molecular detection due to the advantages of low background noise, high sensitivity, and easy integration. However, the current PEC glucose biosensors are subject to the deficiencies of the relatively large limit of detection, small detectable range of concentration, and requirement of an operation voltage. Herein, we construct an unbiased glucose biosensor both in three- and two-electrode configurations using a glucose oxidase (GOx)-modified Schottky junction comprised of Au nanoparticle (NP)-decorated TiO2-coated Al films. A wide detectable range of concentration (0.3–104 μM) is achieved at relatively zero bias versus the reference electrode in a three-electrode configuration under AM 1.5G illumination along with a fitted sensitivity of 3780 μA mM–1 cm–2 (in the concentration range of 0.3–1.0 μM) and a limit of detection down to 0.05 μM. The photocurrents corresponding to typical interfering substances (e.g., uric acid and ascorbic acid) are less than 10% of that to glucose. Moreover, the constructed sensor achieves almost no attenuation in photocurrent under light ON/OFF circular irradiation for 30 min and shows a photocurrent around 92% of the initial value after 30-day storage in air at room temperature. The satisfactory sensing performance is ascribed to the following three aspects: (1) the optical absorption is enhanced due to the formation of a plane-parallel resonance cavity and the reduced band gap of the TiO2 material, (2) the separation and extraction of the photogenerated carriers are facilitated due to the Al doping and the embedded Schottky junction, and (3) the carrier transfer from the photoelectrode surfaces into the electrolyte is boosted because of the Au NPs and nanostructured GOx decoration. This work provides an alternative route to prepare high-performance and self-powered glucose sensors for diabetes diagnosis.