The voltammetric performance of interdigitated electrodes
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This thesis explores ways to improve the performance of electrochemical affinity sensors by integrating cyclic voltammetric (CV) method and nano or micro interdigitated electrodes (IDEs) in a generator-collector mode. Affinity-based biosensors are based on the interactions between complementary molecules such as antibody-antigen coupling, aptamer-protein recognition, or DNA hybridization. In these sensors, the functionalization of electrodes will reduce the access for electron-transfer from the electrolyte to the electrode, or vice versa. This, in turn, will decrease the electron transfer rate (or k0 value) at the surface of the electrode. Hence, for successful applications of IDEs in affinity-based biosensors, it is important to know the effect of changing k0 on the current performance of IDEs. When it comes to nano-IDEs, the effect of electrical double layer (EDL) will become dominant. Therefore, the k0 value effect at nano-IDEs needs to be considered along with the EDL effect. In this study, we developed a complete computational model to address the above issues. To confirm the simulation results, IDEs with 4.25 m electrode size and gap spacing are fabricated and characterized by CV method in a generator-collector mode and a single-electrode mode. The electrode surface of IDEs is then successively modified by probe molecules sulfo- NHS-SS-Biotin (Sulfosuccinimidyl 2-(biotinamido)-ethyl-1, 3-dithiopropionate) self assembled monolayer (SAM) and bond by the target molecules avidin at various concentrations. The CV responses are measured stepwise after each modification of electrodes. The simulation results shows that the CV responses of micro or submicron IDEs are more sensitive to k0 value change than the response of single electrodes of microscopic dimension. At micro IDEs the relationship between CV limiting (or peak) current and k0 value is strongly dependent on the electrode size and spacing. And at nano IDEs, this relationship also varies with charge valence of the redox species. The simulation results are confirmed by the experiment. We thus conclude that the performance of electrochemical affinity sensors can be improved by integrating CV method and micro IDEs. Based one the simulation analysis and experimental results we also speculate that integrating CV method and nano IDEs will further improve the sensing performance of IDEs-based affinity sensors. This study presents some important information for improving the design and development of future electrochemical-based biosensors.