On-Antenna Multi-Analyte Biochemical Sensing (ASense)

ended

Lab-on-chip (LOC) devices are useful for manipulating, analyzing, and interacting with small samples in a wide range of applications. Wireless LOC devices have been developed for remote and distributed analysis purposes where wired measurements are not feasible or cost-effective. The devices consist of a miniaturized array of biochemical sensors connected to a low-power radio transceiver. The current trend in wireless LOC devices is to miniaturize the sizes, lower the power consumption, and increase the processor capacity while driving down costs which are rapidly approaching their practical and theoretical limits. These raise the need for a new design to support the future sustainability of these devices to facilitate the current and upcoming massive deployments for use in various applications. Triggered by this, the project explores the revolutionary secondary use of the wireless antenna for multi-analyte active sensing purposes by deploying case-tailored sensing nanomaterials on the antenna surfaces current spots with each targeting a specific analyte using a Molecular Imprinting Polymer (MIP) layer grown above a highly conductive 2D transduction nanomaterial layer. The idea is to move the complexity from the wireless LOC to the computation of the gateway station, where signal processing and machine learning techniques are employed to remotely sense the targeted analytes. This is done by detecting changes on the radiation characteristics of the antenna caused by the applied sensing materials. The idea of using the antenna as a multi-analyte active sensor is an absolute novelty. If successful, the approach will have a huge contribution in reducing the hardware complexity of standard wireless LOC devices by at least 50% (no need to sensor integrated circuits, microcontrollers, and their associated power consumption), resulting in more than doubling their battery lifetime due to less power consumption, making large-scale mass deployment economically feasible.