Begin by collecting the spectra of a vertical line of the VS-FG signals on the charged coupled device or CCD. Collect non-resonant intensity images by scanning the sample perpendicularly to the beam scanner direction. To spectrally unmix the data using the MATLAB imaging toolbox hyperspectral imaging library workflow.
Use the hypercube function in the library to create a four-dimensional hypercube where X and Y are spatial, Z corresponds to the frequency dependent intensity, and omega is the frequency. Identify the number of unique spectra with the count end members HFC function, with a probability of false alarm or PFA value of 10 to the negative seven. Then identify unique spectra using the N-finder spectral unmixing function.
Using the SID function, associate each pixel with one of the previously identified unique spectra. Finally, fit the sum data for each isolated sheet to the Voit function. VS-FG images of self-assembled sheets dispersed on a cover slip were captured.
And through spectral identification, it was found that all sheets could be categorized into two types, one with higher VS-FG intensity and the other with lower intensity. By inspecting and comparing with the optical image, the large sheet at the center of the images appeared to have stacked double sheets, thereby attributing the smaller VS-FG intensity to destructive interference. Two of the sheets were measured by various VS-FG polarizations and the spectra were fitted using the Voit functions.
