Editor’s Note: This column is a summary by the authors of the Analytical Series article of the same name, which was published in the May 2019 issue of CoatingsTech. To download the complete article, visit https://docs.paint.org/Ct-Analytical-Series/Analytical-Series_May2019.pdf.
Confocal microscopes are useful research tools for spatial characterization of heterogeneous coating systems. In a confocal microscope, emitted, reflected, or scattered light from the sample is detected through a spatial pinhole, which blocks most of the out-of-focus lights to enhance depth resolution and image quality. The depth profiling feature essentially enables optical sectioning of samples without destructive sample preparation, like cross-section microtoming. The article described three illustrative applications of confocal Raman microscopy (CRM) and confocal laser scanning microscopy (CLSM) to investigate some common coatings phenomena.
Quantification of Component Distribution Using Raman Intensity Ratio
In Example 1, lateral and depth mapping of a styrenated additive was performed by comparing the intensities of Raman transitions associated with phenyl ring of the additive with that of the carbonyl groups of the acrylic polymer. In pigmented coatings, titanium dioxide (TiO2) is a strong absorber at low wavenumbers, and film opacity causes depth attenuation of spectral intensities. By focusing on the spectral range for organic components, the authors monitored the intensity ratios of styrene to acrylic signature bands at various depths to minimize the influence of signal attenuation. As a result, spatial analysis of the additive present at only 2 wt % in the pigmented acrylic paint formulation was determined (semi)quantitatively. The additive concentration, reflected by a constant intensity ratio throughout the film, confirmed its uniform distribution in non-transparent, pigmented coatings.
Visualization and Quantification Using CLSM
Compared with CRM, CLSM using reflection or fluorescence contrast can provide real-time 3D imaging with greatly improved speed and spatial resolution. An example is shown in Figure 1 (Figure 9 in the original article), which depicts layer-by-layer optical sectioning of latex film stained by grape juice. The intrinsically fluorescent color compounds in the grape juice provided distinct microscopic contrast and spatial differentiation in the color-coded spectral images. CLSM therefore enabled direct visualization and quantification of stain penetration in the polymer matrix.
(Semi)quantitative Analysis Through Novel Data Processing Methods
When standard peak-fitting or intensity ratio calculation is not possible, special data processing techniques are required to extend the use of CRM for quantitative and semi-quantitative analyses. In Example 2, the authors explored the second derivative analysis of Raman spectra to resolve low concentration of a surfactant leached out on the film surface of a semi-gloss white paint. In Example 3, a novel data analysis method was developed to take advantage of the fluorescence emission of grape juice. Fluorescence is generally an unwanted limitation encountered often in Raman spectroscopy. The area ratio of the fluorescence envelope to the C-H region was exploited to characterize adsorption, penetration, and removal of grape juice stains. Figure 2 (Figure 16a in the original article) illustrates a typical example of CRM extracted data. The intensity ratio at zero depth was related to the surface concentration of grape juice. The minimum in the depth profile plot was taken as the end point of grape juice penetration. Using this approach, effects of different binder polymers, staining time, and washing protocols were investigated. The CRM semi-quantitative analysis yielded excellent agreement with color measurements from the empirical washability test, while providing deeper insight into the staining and stain removal processes.
In summary, the article demonstrated that confocal microscopes can be employed to skillfully map spatial locations of various chemical species even in pigmented, multi-component coating systems.
Wenjun Wu, Arkema, Inc., Arkema Coating Resins. Email: firstname.lastname@example.org. Dana Garcia, Arkema, Inc. Jeffrey Schneider, Arkema, Inc., Arkema Coating Resins.