IntroductionThe analysis of different kinds of multi-layer systems is of considerable interest in various industries. Particularly, the spatial distribution of specific substances, particles and defects needs to be measured in order to gain informa-tion about all kinds of material properties. Of interest are typically the chemical composition of different layers or the distribution and size of embedded particles resulting from pigments, fillers or impurities.The Bruker FT-IR microscope series HYPERION allows the analysis of large multilayer areas as well as the detection of smallest structures, defects and contaminations. HYPERION FT-IR microscopes offer the highest possible optical resolution which is only limited by the diffraction of light. With the dedicated OPUS software Bruker offers a powerful tool for measurement, evaluation and visualization of microscopy samples.

InstrumentationThe HYPERION FT-IR microscope series represents the most advanced level of FT-IR microscopy available today, utilizing state-of-the-art optics for optimal sample visualiza-tion and infrared data collection. Even at the highest spatial resolution the HYPERION microscopes exhibit an outstan-ding sensitivity. The innovative attenuated total reflectance

Application Note AN # 412Analysis of multi-layered paint chips

(ATR) objective is equipped with a very precise internal pressure sensor and can also be used as a 20 x visual objec-tive. Due to the special design of this objective it is possible to analyze even structured samples by automated ATR-mapping. Thin coatings on substrates, monolayers, surface contaminations and oxidation layers can be measured on reflective substrates with excellent sensitivity by means of the grazing angle objective. Furthermore the HYPERION microscopes can be equipped with a focal plane array (FPA) detector for spectral imaging that allows to record up to 16.384 spectra simultaneously.

Example measurementAs an example the analysis of a multi-layered paint chip is shown. The sample was embedded in a resin, cut and polished. It was analyzed with a Bruker HYPERION micro-scope. (Figure 1).

ATR mapping measurements were performed using an 20 x ATR-objective in combination with a motorized sample stage. Measurement positions and sampling areas were set specifically for each layer. An acquisition time of 14 sec at a spectral resolution of 4cm-1 was used. During the infrared measurement, the sample is brought into contact with the tip of the Germanium (Ge) crystal (100μm in diameter) of the ATR-objective on all predefined sampling positions. The effective field of view at all sampling positions is adjusted automatically by an motorized aperture.Figure 1b shows the visual image with the corresponding spectra of the upper 6 layers of the paint chip (the top layer is resin).

ATR imaging of a specific layer of the paint chip In the multilayer sample (Figure 1b) a wider white area is visible below the red layer. To determine whether this distinct layer includes only one component or if several constituents are included the ATR imaging technique was used. This state-of-the-art technique uses a focal plane array detector (FPA) with 64 x 64 pixels in combination with a 20 x ATR-objective. With this approach a pixel resolu-tion of 0.5μm is achieved. Each pixel of the FPA detector collects a complete FT-IR spectrum. A measurement area of 32 x 32μm is covered and 4096 spectra are recorded simultaneously. By combining “imaging” and “mapping” a multitude of single images can be merged automatically into a larger image with high resolution.

The analysis was performed by mapping an area of 2 x 8 images which results in a field of view (FOV) of 64 x 256μm. Figure 2 shows the visual image of the white layer from the multilayer. 65,000 spectra (2 x 8 x 4096 Spectra) at a spectral resolution of 8cm-1 were recorded in about 10min. In order to visualize these spectra, the intensities of sui-table absorption bands – characteristic for certain functional

Figure 2: Visible sample image. Red frames indicate the area which was analyzed by ATR-FPA-Imaging. The squares show the area which was covered by each FPA measurement resulting in 4,096 FT-IR spectra per square.

Figure 2

Figure 1b: Overview image A shows measurement positions with individual aperture size. B shows corresponding spectra of 6 layers.

Figure 1bA B

Figure 1a: Visual image of a paint chip. Sampling positions with their individual size are indicated. Field of view (FOV): 2000 x 450μm

Figure 1a

groups – were plotted in false color over the analyzed area. The resulting IR images show high concentrations of the found components in red and low concentrations in blue (rainbow scaling; Figure 3). Contrary to the low visual con-trast these IR images reveal clearly the chemical complexity of this layer and the inhomogeneous distribution of all the components. Besides the acrylate other substances like carbonates, carbohydrates and calciumsulfate are present. The smallest particles detected within this layer are from calciumsulfate with less than 5μm in diameter.

Polymer laminates in transmission High resolution IR images can also be collected in transmis-sion if the sample is transparent in this spectral range. The advantage of this method is a contact-free measurement.

Figure 5: FT-IR spectra of the four polymer layers in a laminate (see Figure 4). A brown layer, B black layer, C grey layer and D white layer

Figure 5

Figure 6: 3D-IR-image of one polymer layer on top of the visual image (for details see text).

Figure 6Figure 4

Figure 4: Visual image and false color plot of the 4-layer paint chip sample with the intensity distribution relating to the white layer. FOV 340 x 340 μm.

Visual image Acrylate

Figure 3: IR images of the found components in false color (rainbow scaling). Analyzed area: 64 x 256 μm; pixel resolution: 0.5 μm. Note: Even particles smaller than 5 μm in diameter were clearly resolved spatially.

Carbonate Carbohydrate Calciumsulfate~3x5 μm

~5x6 μm

Figure 3

As an example a 4 layered polymer laminate (microtom section of 10μm) was analyzed (Figure 4). By using the 15 x objective a transmission-image with a FOV of 170 x 170μm and a pixel resolution of 2.7μm was obtained. To acquire the full width of the sample a 2 x 2 image-map with a FOV of 340 x 340μm was measured. The total acqui-sition time was 3min at a spectral resolution of 4cm-1.In Figure 5 representative pixelspectra are shown, indicating characteristic absorption features of the four layers.

IR images were generated by plotting the intensities for those characteristic absorption bands above the analyzed sample area. Figure 4 displays the IR image of one included polymer as a false color plot in 2D (“contour plot”). This per-spective is very suitable to correlate structures in the visible

with those in the IR image. The OPUS software offers a wide range of display and visualization functions. Figure 6 shows the IR Image of an absorption band correlated to one polymer in 3D on top of the visual image of the sample.

Single spectra from any position of the acquired image can be further used for identification purposes e.g. via a library search. To combine information from several IR images, both RGB (Red-Green-Blue, Figure 7) and WTA (Winner-takes-it-all, Figure 8) images can be created. In an RGB picture up to three sample components are assigned to

Figure 9: Cluster Analysis shows five different classes (four different layers + polymer free region) defined by spectral similarity.

Figure 9

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Figure 7

Figure 7: Distribution of all polymer layers dis-played in a RGB-plot based on the IR-images.

RGB colors that are merged at each image pixel. The WTA-model assigns the color of the dominant component to each individual image pixel thereby allowing to display more than three components in one picture. 3D cluster analysis can be performed to evaluate FT-IR imaging data by unsupervised algorithms. The user has to define the number of components in the sample. All indi-vidual spectra are grouped into this predefined number of classes according to their spectral similarity (using Euclidian distance or Principal Component Analysis (PCA).

Figure 8: Distribution of all polymer layers dis-played in a WTA-plot based on the IR-images.

Figure 8

SummaryThese results demonstrate that FT-IR-mapping and imaging are powerful, flexible and fast technologies for the characte-rization of multilayer samples. The IR-imaging is able to show structures in a sample that are completely invisible in the visible image. Additionally, it is even possible to identify the detected substances by means of the library search function. To achieve highest spatial resolution modern focal plane array detector technology can be used resulting in pixel resolu-tions down to 0.5μm. The combination of IR-imaging and mapping allows to measure large areas up to several mm in size. For the evaluation of the acquired data the Bruker OPUS software offers a wide range of tools. This ranges from single band integrations to advanced multivariate methods like multilinear regression, 3D-cluster analysis and principal component analysis (PCA). Data can further be visualized in multiple 2D and 3D plots, different color schemes, overlay of VIS and IR-images as well as RGB and WTA-Images.