부산대학교 도서관

In this work, we demonstrated an off-chip capacitance array biosensor with the limit of detection $1 ~\mu \text{m}$ of trimethylamine N-oxide (TMAO) to diagnose chronic metabolism disease in urine. Based on the improved Cole–Cole model, the parameters of ${R}$ _catalyzed and ${C}$ _catalyzed and ${R}_{p}$ _catalyzed can predict the catalytic resistance of enzyme and redox effects of the analyte and identify the ac properties of ion strength due to enzymatic catalysis. With the investigation of the off-chip capacitance biosensor electrical field change with respect to pixel geometry and associated driving and sensing electrode width in a pixel, the proposed off-chip biosensor with readout system-on-chip (SoC) exhibits the high sensitivity of 21 ADC counts/ $\mu \text{m}$ (or 25 mV/ $\mu \text{m}$ ), response time of 0.1 s, repetition of 98.9%, and drift over time of 0.5 mV. The proposed off-chip biosensor can distinguish TMAO in phosphate buffered saline (PBS) solution from the tiny capacitance change of TMAO induced by enzyme TorA with a difference of 2.15%, and the measurements have been successfully verified with traditional cyclic-voltammetry (CV) method, which shows a difference of only 0.024%. The off-chip biosensor is designed to specifically detect TMAO by excluding the redox reactions of TMAO-specific enzyme TorA with creatine and creatinine in urine. This exclusion ensures that the biosensor focuses solely on TMAO, enhancing its specificity for accurate and reliable TMAO detection.