Using Automated IR Microscopy to Rapidly Characterize Multiple Regions of Interest in a Sample

Infrared (IR) microscopy is a well established analytical method that is widely used in the food, pharmaceutical, chemical, electronics, and polymer industries. It is used for identifying and measuring micrometer-sized samples and helps in detecting impurities or foreign objects of unidentified origin. This article shows the benefits of using an automated IR microscopy technique for defining foreign objects and particles in different kinds of materials.

In forensic applications, paint chips, drugs, fibers, residues and other small material particles are usually collected as proof of evidence and studied using IR microscopy. There are different types of IR microscopy techniques such as reflectance, transmission, and attenuated total reflectance (ATR) . The use of a specific type of IR microscopy technique will depend on the material’s type and size, and also the matrix containing the sample.

The Spotlight™ 200i IR microscope is an advanced, fully automated instrument that includes a number of features such as automatic illumination LEDs, automated X, Y, Z stage, auto correction, autofocus, automated switching between reflectance and transmission, and automated dropdown ATR crystal. The Spectrum 10 software is used to control these features.

Traditionally, a number of manual steps are involved when an IR microscope is used for sample measurement. These steps are required to find and specify the preferred regions for testing and manual processing of the data collected. However, such processes can take a significant amount of time. Now, with the help of intelligent detection routines, these processes have been completely automated in the Spectrum 10 software. The standard types of samples determined on an IR microscope include multilayer samples, particles, and sample inclusions.

Automated Detection and Analysis of Microplastics Extracted from a Cosmetic Formulation

The identification and classification of microplastic particles collected from a cosmetic formulation is one example of the automation process. Tiny microplastic particles are present in cosmetic exfoliating agents that serve as an abrasive material to wash the skin. These particles enter the river bodies and eventually affect the marine environment.

A commercially available product was mixed with hot water to dissolve the soluble ingredients in the formulation. A 50µm mesh was used to filter the resulting solution so that any insoluble components measuring more than 50µm are captured. The filter was allowed to dry before the remaining particles were transferred to an IR transmitting window featured on a microscope holder. A Visible Image Survey was recorded over the area containing the majority of the particles. The Spectrum 10 software includes an ‘Analyze Image icon’. Selecting this icon activates the intelligent and automated detection routine for image analysis (Figure 1).

The "Analyze Image" function detected filtered particles deposited on a KBr window.

Figure 1. The "Analyze Image" function detected filtered particles deposited on a KBr window.

This routine is capable of locating any type of particles in the visible image, and highlights them as regions of interest. It subsequently measures the highest rectangular aperture size, which can be fully accommodated within individual particles. This approach helps in reducing signal-to-noise when scanning the data.

Selecting ‘Scan Markers’ will start the collection of transmission spectra for individual sample, and real time ratioed sample spectra are shown as they are collected. Automatic processing of the spectra, such as Search, Compare or Verify, will be performed during data collection. During microplastic analysis, a spectral search was performed over a polymer spectral library to provide individual particle identity (Figure 2). In this sample, two types of polymer were detected, identified as polypropylene and polyethylene. The spectra are shown in Figure 3.

Results screen for detection and identification of particles.

Figure 2. Results screen for detection and identification of particles.

Spectra of the two different polymer types are shown here. Top: polypropylene, Bottom: polyethylene.

Figure 3. Spectra of the two different polymer types are shown here. Top: polypropylene, Bottom: polyethylene.

Automated Detection and Analysis of Contaminants on an Electronic Contact

It is important to ensure that electronic contacts are clean and contamination-free to prevent any operational issues. Visible contaminants were found on a sample submitted for analysis. The same was positioned in the Spotlight 200i IR microscope and a ‘Visible Image Survey’ was collected over the whole contact. In order to find out the presence of any contaminant, the image that was obtained was examined by means of the “Detect Particles” function in the Spectrum 10 software. Figure 4 shows the Visible Image Survey and an extended area showing the detected particles.

The Visible Image Survey and expanded region show automatic detection of contaminants.

Figure 4. The Visible Image Survey and expanded region show automatic detection of contaminants.

Once ‘Scan Markers’ has been selected, spectra and reflectance backgrounds for the particles are automatically collected by the Spectrum 10 software. Their spectra are illustrated in Figure 5.

Reflectance spectra of the two contaminant fibers.

Figure 5. Reflectance spectra of the two contaminant fibers.

It was observed that the spectra of both these materials are analogous with the lower spectrum, displaying a further broad peak centered about 700cm-1. After exploring the spectrum against a spectral library of polymer additives and polymers, the top spectrum was determined to be a acrylonitrile-butyl methacrylate copolymer. As another component was present in the lower spectrum, a mixture search was done on this spectrum, which revealed that the sample contained tin oxide.

Automated ATR Analysis of Layers in a Polymer Laminate

ATR is a convenient sampling technique requiring minimal sample preparation that has been routinely applied within the polymer industry. An IR microscope equipped with an automated drop-down ATR crystal enables automated determination of polymer samples such as layers of multilayer laminates. In this case, a sample holder clamped with a multilayer polymer card was positioned on the stage of the Spotlight 200i system. A ‘Visible Image Survey’ was collected across a 2x2mm sample area, followed by the application of automated ‘Detect Layers’ function in the Spectrum 10 software (Figure 6).

Automated detection feature of the Spotlight 200i show multiple layers in a polymer laminate

Figure 6. Automated detection feature of the Spotlight 200i show multiple layers in a polymer laminate.

In the image, five different layers were identified and markers were placed in the middle of individual layer. Selection of the ‘Scan Markers’ icon will enable automatic collection of the background scans, subsequently moving to each marker, lowering the ATR crystal on the sample (Figure 7), and determining the spectra.

The automated dropdown ATR crystal

Figure 7. The automated dropdown ATR crystal

Figure 8 shows the spectra collected from individual layers, and the same were detected by comparing against search libraries. From top to bottom, the layers were identified as ethylene-vinyl acetate (EVA) co-polymer, polyethylene terephthalate (PET), silica-loaded polyethylene, another EVA layer, and another PET layer.

Spectra of the five layers

Figure 8. Spectra of the five layers

Conclusion

With the help of the Spotlight 200i intelligent automated IR microscope, spectra from a wide range of samples can be collected and analyzed quickly and easily. In this analysis, all sampling modes have been automated, such as reflectance, transmission, ATR, in addition to a wide range of samples, such as multi-layers, particles, and fibers.

This information has been sourced, reviewed and adapted from materials provided by PerkinElmer.

For more information on this source, please visit PerkinElmer.

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