Hybrid plasmonic-semiconducting fractal metamaterials for superior sensing of volatile compounds

Localized surface plasmon resonance (LSPR) is a subwavelength optical phenomenon that has found widespread use in bio-and chemical-sensing applications thanks to the possibility to efficiently transduce refractive index changes into wavelength shifts. However, is it very hard to transpose the successes demonstrated in liquid and physiological environment toward the detection of gasous molecules. In fact, the latter typically adsorb in an unspecific manner and induce very minute refractive index changes tipicaly below the sensor sensitivity. Here, we show first insights on the aerosol large-scale self-Assembly of metasurfaces made of monocrystalline Au nanoislands with uniform disorder over large scale. Notably, these architectures show tuneable disorder levels and demonstrate high-quality LSPR, enabling the fabrication of highly performing optical gas sensors detecting down to 10-5 variations in refractive index. Next, we use our aerosol synthesis method to integrate tailored fractals of dielectric TiO2 nanoparticles onto resonant plasmonic metasurfaces. We show how this integration strongly enhances the interaction between the plasmonic field and volatile organic molecules and provides a means for their selective detection. Interesting, the improved performance is the result of a synergetic behavior between the dielectric fractals and the plasmonic metasurface: in fact, upon this integration, the enhancement of plasmonic field is drastically extended, all the way up to a maximum thickness of 1.8 μm. Optimal dielectric-plasmonic structures allow measurements of changes in the refractive index of the gas mixture down to <8x10^-6at room temperature and selective identification of three exemplary volatile organic compounds (VOCs). These findings provide a basis for the development of a novel family of hybrid dielectric-plasmonic materials with application extending from light harvesting and photo-catalysts to contactless sensors for non-invasive medical diagnostics.