Investigating the Performances of Wide-Field Raman Microscopy with Stochastic Optical Reconstruction Post-Processing

Super-resolution imaging of micro- and nanoplastics using confocal Raman with Gaussian surface fitting and deconvolution

Confocal Raman imaging can directly identify and visualise microplastics and even nanoplastics. However, due to diffraction, the excitation laser spot has a size, which defines the image resolution. Consequently, it is difficult to image nanoplastic that is smaller than the diffraction limit. Within the laser spot, fortunately, the excitation energy density behaves an axially transcended distribution, or a 2D Gaussian distribution. By mapping the emission intensity of Raman signal, the imaged nanoplastic pattern is axially transcended as well and can be fitted as a 2D Gaussian surface via deconvolution, to re-construct the Raman image. The image re-construction can intentionally and selectively pick up the weak signal of nanoplastics, average the background noise/the variation of the Raman intensity, smoothen the image surface and re-focus the mapped pattern towards signal enhancement. Using this approach, along with nanoplastics models with known size for validation, real samples are also tested to image microplastics and nanoplastics released from the bushfire-burned face masks and water tanks. Even the bushfire-deviated surface group can be visualised as well, to monitor the different degrees of burning by visualising micro- and nanoplastics. Overall, this approach can effectively image regular shape of micro- and nanoplastics, capture nanoplastics smaller than the diffraction limit, and realise super-resolution imaging via confocal Raman.

A Wide-Field Imaging Approach for Simultaneous Super-Resolution Surface-Enhanced Raman Scattering Bioimaging and Spectroscopy

High spatial resolution imaging and chemical-specific detection in living organisms is important in a wide range of fields from medicine to catalysis. In this work, we characterize a wide-field surface-enhanced Raman scattering (SERS) imaging approach capable of simultaneously capturing images and SERS spectra from nanoparticle SERS tags in cancer cells. By passing the image through a transmission diffraction grating before it reaches an array detector, we record the image and wavelength dispersed signal simultaneously on the camera sensor. Optimization of the experiment provides an approach with better spectral resolution and more rapid acquisition than liquid crystal tunable filters commonly used for wide-field SERS imaging. Intensity fluctuations inherent to SERS enabled localization algorithms to be applied to both the spatial and spectral domain, providing super-resolution SERS images that are correlated with improved peak positions identified in the spectrum of the SERS tag. The detected Raman signal is shown to be sensitive to the focal plane, providing three-dimensional (3D) sectioning abilities for the detected nanoparticles. Our work demonstrates spectrally resolved super-resolution SERS imaging that has the potential to be applied to complex physical and biological imaging applications.