A closer look at thin sections: White light profilometry applied for thickness estimation of embedded paint fragments

Detailed analysis of multilayer paint such as automotive paints often involves thin sectioning of the paint fragments through cross-sectional or in-plane cuts. Thin sectioning of monolayer paint such as tool paints is less common but useful for instance as a sample preparation method for Microspectrophotometric (MSP) analysis. Based on an internal validation, the current procedure for tool paint cuts in our laboratory describes the use of 5 µm thin sections as opposed to the ASTM E2808-21a standard recommending a section thickness of approximately 3 µm. However, further microscopic examination of these 5 µm tool paint thin sections has raised questions as strong variations in colour intensities were observed. During this process concerns related to the reliability of the microtome's 5 µm setting were also raised. The current study focuses on a new method application to accurately assess the thickness of thin sections. Thin sections from 20 tool paint samples were prepared using cured Technovit 2000 LC resin and a rotary microtome. These thin sections were mounted on a glass slide and height differences were measured using white light profilometry. Generated heatmaps and in-depth data analysis allowed for average thickness calculations and yielded some unexpected observations. The results reveal substantial variation in thin section thicknesses with a clear tendency towards thinner sections (< 5 µm) than the microtome's setting (5 µm), as well as frequent vertical dislocations of the embedded paint fragments compared to the surface height of the thin section. Complementarily, IR peak absorbance values (band integration) of some of the main thin sections' resin IR peaks were plotted against the thicknesses estimated with profilometry, revealing for most measurements a linear correlation. These findings give confidence to the applied methodology and provide a calibration curve for future thin section thickness estimations using FTIR spectroscopy.