Super-Resolution Imaging of Plasmonic Near-fields: Overcoming Emitter Mislocalizations
Plasmonic nano-objects have shown great potential in enhancing sensing, energy transfer and computing, and there has been much e↵ort to optimize plasmonic systems and exploit their field enhancement properties. Super-resolution imaging with quantum dots (QDs) is a promising method to probe plasmonic near-fields. However, due to the strong coupling between QDs and plasmons, this technique is hindered by the formation of distorted point spread functions (PSFs) and QD mislocalizations. Chapter 4 of this dissertation investigates the coupling between QDs and ‘L-shaped’ gold nanostructures, and demonstrates both theoretically and experimentally that this strong coupling can induce polarization- / wavelength-dependent changes to the apparent QD emission intensity, polarization and position. From the magnitude and direction of the PSF shift under emission polarization modulation, the coupling strength can be extracted, and the true PSF location can be back-calculated from tabulated theoretical and experimental values. This discovery helps to better apply super-resolution imaging techniques to detect the plasmonic near-fields.Besides using fluorescence intensity as the local-field intensity indicator, photophysical properties of the emitter (e.g. on-time ratio) have shown to be a great candidate as well. Super-resolution fluctuation imaging (SOFI) has great potential in extracting the photophysical properties of emitters with super-resolution. In chapter 5, I discuss an open-source, modular SOFI analysis package we built for both reconstructing super-resolved plasmonic near-fields and engaging the SOFI community with a wide range of applications. Chapter 6 demonstrates how we characterize the photophysical properties of a specific fluorescent protein suitable for SOFI analysis. Our work provides a practical method with higher precision for plasmonic near-field mapping, which benefits many applications like biosensing and optical quantum computing.