Conic hyperspectral dispersion mapping applied to semiconductor plasmonics

Abstract

The surface plasmon resonance tracking over metal surfaces is a well-established, commercially available, biochemical quantification tool primarily applied in research. The utilization of such a tool is, however, constrained to highly specialized industries, capable of justifying the human and instrumental resource investments required by the characterization method. We have proposed to expand the field of application of this biosensing approach by redesigning this method through the integration and miniaturization within a semiconductor platform. Uncollimated and broadband emission from a light-emitting semiconductor is employed to couple a continuum of surface plasmon modes over a metal–dielectric architecture interfaced with a GaAs–AlGaAs substrate. A tensor version of rigorous coupled wave theory is employed to optimize the various fabrication specifications and to predict the light scatterings over a wide range of variables. We then present a hyperspectral characterization microscope capable of directly mapping the dispersion relation of scattered light, including diffracted surface plasmons, as an intensity distribution versus photon energy and surface wavevectors. Measurements carried out in a buffered solution demonstrate the accurate description of the uncollimated and broadband surface plasmon states. Finally, we introduce a simplified method of dispersion mapping, in which quasi-conic cross-sections of the light's scattering can be acquired directly, thus monitoring surficial responses in as fast as 1.2 s. This is over 300 times faster than required by implementing full dispersion mapping. While compromising on the volume of collected information, this method, combined with the solid-state integration of the platform, shows great promise for the fast detection of biochemical agents. Researchers have miniaturized surface plasmon resonance experiments by using microchips embedded with gallium arsenide ‘quantum wells’. One of the best ways to track biochemical agents is through surface plasmon resonance spectroscopy, a technique that uses vibrations from a thin metal layer to detect specific molecular adsorption events. However, observing surface plasmons for biosensing traditionally requires the use of large, precisely tuned light sources. The scheme developed by Dubowski and co-workers employs hyperspectral imaging—a means of measuring data from hundreds of different spectral bands—to record how the broadband light of quantum well nanostructures scatters after striking a metal film. Advanced algorithms then pick out surface plasmons from the light-scattering data and enable near real-time analysis. Solid-state integration and pre-analysed output make this device ideal for future commercial ventures that could go beyond the application of surface plasmon resonance for biosensing.