Endorsing a Hidden Plasmonic Mode for Enhancement of LSPR Sensing Performance in Evolved Metal-insulator Geometry Using an Unsupervised Machine Learning Algorithm.

Large-area nanoplasmonic structures with pillared metal-insulator geometry, also called nanomushrooms (NM), consist of an active spherical-shaped plasmonic material such as gold as its cap and silicon dioxide as its stem. NM is a geometry which evolves from its precursor, nanoislands (NI) consisting of aforementioned spherical structures on flat silicon dioxide substrates, via selective physical or chemical etching of the silicon dioxide. The NM geometry is well-known to provide enhanced localized surface plasmon resonance (LSPR) sensitivity in biosensing applications as compared to NI.