Stain-free tissue imaging with scalable plasmonic metasurfaces

Abstract

Label-free tissue diagnostics using plasmonics, a.k.a. histoplasmonics, enables morphological analysis of cells with colorful contrast in the refractive indices between cells and surroundings (Ref. Nature 598, 65, (2021)). However, this method still requires not only cell staining with molecular dyes (hematoxylin and eosin, H&E) for enhanced contrast, but also a regular array of plasmonic nanopatterns via nanolithography, limiting mass-production. We here describe a ‘lithography-free’ scalable fabrication of plasmonic metasurfaces using a rapid electrostatic coating of nanoparticles and their use for ‘stain-free’ colorful refractive index imaging of cells. The colloidal solution of negatively-charged plasmonic nanoparticles is casted onto a positively-charged metallic mirror, enabling the rapid (but massive) nanoparticle coating in a random fashion (> 10% surface coverage for 10 seconds) and thus formulating well-defined solid nanogaps between the nanoparticles and the mirror underneath through the centimeter scale film. Such plasmonic metasurfaces defined with a solid nanogap not only provides the uniform, vivid colors through the entire surface, but are also sensitive to the change in the surrounding refractive index so readily visualize its variation in the extremely localized area (ideally single nanoparticle level) in colors from red to green under an ambient light. More crucially, this metasurface offers the distinct color of the cultured animal cells (3t3-L1, adipose cell, n = 1.358-1.374) against the water environment (n = 1.33), otherwise impossible to be seen with standard optical microscopy. In this presentation, the fabrication method of the plasmonic metasurfaces and their theoretical and experimental optical features will be discuss. Furthermore, we will show how to qualitatively model the resonant plasmonic spectra as a function of the refractive index spectroscopically for in-situ colourful imaging of the cultured animal cells.