Recent advances in single-molecule spectroscopic imaging techniques, such as spectrally resolved stochastic optical reconstruction microscopy (SR-STORM), have been effective for obtaining detailed spectral information at the molecular level. However, its application for single-molecule sensing is highly challenging owing to its complicated configuration and limited spectral information. In this study, we demonstrated single-molecule polarity sensing by combining grating-based SR-STORM with the solvatochromic dye, Nile red. The spatial and spectral resolutions of the custom-built grating-based SR-STORM were examined for various color ranges of fluorescent dyes, and this approach was successfully applied for sensing nanoscale local polarity of various organic solvent molecules and surfactant molecules. Furthermore, we demonstrated that the proposed method effectively distinguished the different polarities of functional groups within surfactant molecules at the single-molecule level. We anticipate that the proposed approach can be combined with other chromic molecules for application to many other chemical systems.

With the rapid development of the nanofabrication of polymer materials, the local measurement of the chemical properties of polymer nanostructures has become crucial because they can be highly heterogeneous at the nanoscale. We developed a spectroscopic imaging approach to characterize the nanoscale local polarity of polymer films via spectrally resolved super-resolution microscopy. We demonstrate the capability of the recently developed single-molecule sensing and imaging method to probe the polarity of polymers either inside a polymer matrix or on the external surface of a polymer. The nanoscale polarity sensing capability of our method facilitates the differentiation of various polymer surfaces based on chemical polarities, and it can further differentiate the polarity of functional side chain groups. Moreover, we demonstrate that a two-component polymer mixture can be locally distinguished based on the contrasting polarities of the lateral phase separation, further allowing for the investigation of nanoscale phase separation depending on the composition of the polymer blend film. This approach is anticipated to open the door to further characterizations of various nanocomposite materials.

The increase in the number and complexity of process levels in semiconductor production has driven the need for the development of new measurement methods that can evaluate semiconductor devices at the critical dimensions of fine patterns and simultaneously inspect nanoscale contaminants or defects. However, conventional optical inspection methods often fail to resolve device patterns or defects at the level of tens of nanometers required for device development owing to their diffraction-limited resolutions. In this study, we used the stochastic optical reconstruction microscopy (STORM) technique to image semiconductor nanostructures with feature sizes as small as 30 nm and detect individual 20 nm-diameter contaminants. STORM imaging of semiconductor nanopatterns is based on the development of a selective labeling method of fluorophores for a negative silicon oxide surface using the charge interaction of positive polyethylenimine molecules. This study demonstrates the potential of STORM for nanoscale metrology and in-line defect inspection of semiconductor integrated circuits.

The recent development of super-resolution fluorescence microscopy (SRM) has drastically improved the resolution of light microscopy to the order of tens of nanometers. However, the application of SRM to semiconductor materials remains challenging because fluorophore labeling on inorganic materials with a high labeling density required for nanoimaging has been limited with conventional surface functionalization methods. Here, a novel approach for highly dense material-specific fluorophore labeling methods on silicon-based materials has been developed and demonstrated for SRM imaging of semiconductor line patterns. This approach is shown to selectively and sensitively probe different-sized silicon and silica line patterned arrays including edge structures on a wafer in three dimension, which has not been resolved by a conventional metrology system. Furthermore, we successfully demonstrate that this new method can detect nanoparticle defects with high sensitivity, suggesting its capability as an inspection tool for semiconductor defects. This new nanomaterial imaging approach is expected to drive further innovations in metrology tools and applications.