Large‐Scale Plasmonic Nanodisk Structures for a High Sensitivity Biosensing Platform Fabricated by Transfer Nanoprinting. Issue 7 (18th February 2019) - Liang, Yuzhang; Cui, Wenli; Li, Lixia; Yu, Zhiyong; Peng, Wei; Xu, Ting
Abstract: Surface plasmon resonance in plasmonic nanostructures has become a powerful analytical tool in ultrasensitive label‐free biomolecule sensing. However, the fabrication of plasmonic nanostructure sensors relies on lithography‐based top‐down nanofabrication approaches, which have inherent shortcomings, such as high manufacturing cost, time‐consuming fabrication, and a small fabrication footprint. In particular, the small footprint of fabricated plasmonic nanostructures has significantly restrained the study of their angle‐dependent sensitivity. Here, a centimeter‐scale, high sensitivity sensing platform with low cost and high yield is experimentally demonstrated, fabricated through a transfer nanoprinting approach based on an ultrathin anodic aluminum oxide membrane. Two angle‐dependent resonant modes from the plasmonic nanodisk structure are observed at nonzero incidence angles. The dependence of the bulk sensitivity and surface sensitivity on the incidence angle under these two modes is systematically investigated. By functionalizing the plasmonic nanostructure, monitoring of binding of protein at dilute concentration is performed in real time at different incidence angles. The specific label‐free lowest detection limit is found to be 1.8 nanomolar for the longer wavelength resonant mode at a 10° incidence angle. This plasmonic nanostructure sensing platform should hold promise in the development of low cost and high throughput biosensing chips. Abstract : A centimeter‐scale, high sensitivity sensing platform with low cost and high yield fabricated through a transfer nanoprinting approach based on an ultrathin anodic aluminum oxide membrane is demonstrated. The sensing properties of this platform are investigated systematically at various incidence angles. The results show that the incidence angle can be optimized as a general approach to improve sensing performance.