Improving self-supported nanowire arrays using response surface methodology for the synthesis of a H2O2 nanostructured sensor

Abstract

In this paper, we introduce a data-driven approach for optimizing the design of highly sensitive hydrogen peroxide (H2O2) sensors based on self-supported nickel nanowire (Ni NW) arrays using response surface methodology (RSM). Our goal is to enhance the performance of the sensor by customizing the length of Ni NW while optimizing the working conditions, including the H2O2 concentration and applied potential. Focusing solely on the commercially available porous membranes, we successfully employ RSM to identify the optimal conditions for the sensor: a NW length of 2.64 μm, an optimal concentration of 3.25 mM H2O2, and a detection potential of 0.02 V. We fabricate a sensor with the optimal NW length and validate its performance through comparison to sensors with different NW lengths, such as a planar Ni sensor and a previously investigated nanostructured sensor. Our optimized sensor achieves a 50% reduction in the limit of detection (LOD) and an 18% increase in sensitivity compared with the previously investigated nanostructured sensor. Moreover, the optimized sensor is at least 35 times more sensitive for H2O2 detection than sensors with planar geometries, which are standard in commercial applications. Our results highlight the potential of RSM as a powerful, cost-effective, and theoretically agnostic tool for optimizing nanostructured sensors and accelerating the design-build-test cycle. The optimized H2O2 sensor can be applied in various fields, including the food industry, medical diagnostics, and environmental monitoring. This sensor can significantly enhance glucose detection in non-invasive samples such as tears and saliva when combined with immobilized glucose oxidase enzymes, which is crucial for continuous glucose monitoring in diabetes mellitus patients. The methodology presented in this study allows further extensions to investigate other design variables and sensing materials as well as optimize sensors for detecting different substances, fostering advancements in sensor technologies.