Investigation of Affordable Electrode Material Combinations in Electrochemical Biosensors ^†

This study investigated carbon-based electrode materials for the application of wearable biosensors measuring uric acid concentration. This investigation focused on assessing various combinations of carbon-based electrodes, such as CVD-graphite, graphene ink, and carbon nanotubes, aiming to enhance sensor performance. These carbon materials were deposited on stainless steel (SUS304 SS) plates (2 mm × 10 mm), and their sensitivity for detecting uric acid was evaluated by utilizing cyclic voltammetry (CV) and employing differential pulse voltammetry (DPV). Among the nine electrode combinations tested with potassium ferricyanide, two were identified that generated reversible CV waveforms, indicating their potential for uric acid detection. The effective combinations consisted of one set with CVD graphite for both the working and counter electrodes (WE and CE) and another set combining CVD graphite for the WE with carbon nanotube ink for the CE. The assessments demonstrated that these electrodes could efficiently detect the electron current from the redox reaction of ferricyanide, indicating their potential capability to measure uric acid concentrations effectively. Subsequent analysis using uric acid concentrations ranging from 100 µM to 400 µM showed that CVD-graphite electrodes provided distinct, quantifiable responses in both CV and DPV tests. Notably, the DPV profile for CVD-graphite displayed a significantly high peak current, facilitating the creation of a reliable calibration curve for uric acid concentration detection. The findings concluded that CVD-graphite stands out as the optimal material for both the WE and the CE in uric acid detection within sweat, with a practical detection limit (LOD) of 5.25 µM. This LOD is notably significant, aligning well with the average uric acid concentration in normal sweat, approximately 60 µM, thereby affirming the viability of these carbon-based electrodes for effective disease diagnosis and monitoring through wearable biosensors.