An Ultrasensitive Microfluidic Biosensor Based on Vertically-Aligned MoS2 Nanolayers

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Next-generation biosensors that exploit highly-sensitive, two-dimensional (2D) nanomaterials could provide superior analytical performance and thus enable rapid, ultrasensitive tests for a variety of applications in areas such as molecular diagnosis, environmental monitoring, and food safety inspection. Atomically-thin monolayer molybdenum disulfide (MoS2), as an emerging graphene-like 2D nanomaterial, has attracted significant attention from the biosensor community. Despite the recent advancement in developing high-performance monolayer MoS2 biosensors, previously reported devices suffer from low fabrication yield, challenging biofunctionalization, and low reproducibility; these issues can be largely attributed to some inherent property and preparation process of monolayer MoS2 that are not favorable in biosensor development. In this project, we propose, for the first time, to integrate a novel form of MoS2 nanostructure, vertically-aligned MoS2 nanolayers (VAMNs), into microfluidic field-effect-transistor (FET) biosensors. Because of its unique nanostructures, the VAMNs enable a few new features that do not exist in previous MoS2 biosensors, including facile and reliable covalent immobilization of biomolecules on its vertically-aligned, populated active edge sites and good computability with batch microfabrication. In the meanwhile, the proposed FET-biosensor will also retain the advantageous physical properties of monolayer MoS2 such as its direct bandgap, ultrahigh sensitivity to surface molecule binding, and fast response; therefore, it could provide significantly-enhanced biosensing performance including ultrahigh sensitivity and high stability/reproducibility. The microfluidic design of our biosensor also allows easy device operation, multiplexed assay, and low sample consumption. As the first demonstration, we will apply our FET-biosensor to rapid, ultrasensitive detection of brain injury protein markers for constant monitoring of patient brain conditions during cardiac surgery. This research will offer a powerful VAMN-based biosensing platform, which could find many important applications where ultrahigh sensitivity and very short array time are desired.