Plasmonic Metasurfaces for Taste Visualization

Discriminating taste information before food consumption is vital for mitigating health risks associated with factors such as virus infection, radioactive pollutants, and drug abuse. Plasmonic nanosensors based on refractive index sensing have emerged as a promising platform for taste molecular sensing due to their facile and modular sensing capabilities with low detection thresholds. However, a challenge for the plasmonic nanosensors lies in the lack of qualitative analysis of multiple target species.<br/><br/>Here, we present a breakthrough in plasmonic nanosensors that addresses the challenge of taste-sensing through a wafer-level plasmonic metasurface. This plasmonic metasurface is constructed in a scalable manner by coating metallic nanoparticles onto a metallic mirror, which are separated with a uniform solid nanogap. This design ensures an identical plasmonic cavity resonance (i.e., color) with enhanced sensitivity (&gt; 100 nm/RIU) and uniform surface-wetting properties across the entire wafer. Leveraging this plasmonic metasurface, we introduce the concept of 'binding-free' multiple molecular sensing by simply capturing 2D projection images of molecular droplets on the single plasmonic metasurface using a conventional optical microscope. We are then able to extract two essential physical properties: the molecular refractive index and surface tension, obtained from the droplet's color and size, respectively. The combinatorial analysis of these two properties offers a scalable and intuitive means of detecting and visualizing the five basic tastes, otherwise impossible from either physical property alone. To showcase the utility of our surface-sensitive sensing platform, we successfully identify the tastes of various commercially available liquids. This breakthrough holds significant potential in establishing an end-user-friendly potable taste-sensing platform.<br/><br/>In this presentation, the fabrication method of the plasmonic metasurfaces will be discussed along with their theoretical and experimental optical features and sensing performance. Furthermore, we will demonstrate how to qualitatively model and mathematically analyze the colors and sizes of molecular droplets as a function of the molecular concentrations of each taste molecule for taste visualization and discrimination.