Single Nanostructure Extinction Spectroscopy

Abstract

Molecules and nanoparticles exhibit unique properties such as emission intermittency (i.e. blinking) and spectral wandering which are only observable at the single molecule level. Until recently, single molecule detection has mainly been restricted to fluorescent entities. Now techniques such as photothermal imaging and spatial modulation microscopy allow single molecules and nanoparticles to be detected, regardless of their ability to emit light. This opens up the possibility of discovering new absorptive properties and even photophysics that have previously been masked within ensemble measurements. In this talk, I describe the use of these direct absorption techniques for two case studies. The first is on CdSe nanowires, a material that has potential uses in renewable energy applications. Through direct absorption measurements, we obtain the first absorption size series of any nanowire system and reveal the complex interplay between competing effects such as confinement and dielectric contrast, which determine the optical response of the wires. In a second case study, we focus on graphene oxide, an important precursor in the production of chemically-derived graphene, another important material for renewable energy applications. We show, for the first time, the direct observation of laser-induced, single layer GO reduction through correlated changes to its absorption and emission. Acquired absorption/emission movies illustrate the initial stages of single layer GO reduction, its transition to reduced-GO (rGO) as well as its subsequent decomposition upon prolonged laser illumination. These studies reveal GO’s photoreduction life cycle and through it native GO/rGO absorption coefficients as well as their intrasheet distributions and spatial heterogeneities. Beyond these two case studies, the demonstrated single nanostructure absorption technique offers exciting possibilities for directly interrogating other systems that are not necessarily fluorescent, revealing insights beyond simple ensemble averages.