Polymer Identification Using Raman Spectroscopy

This article discusses the identification of polymers such as ABS, PE, PS, PET, and PMMA in various dyes using Raman spectroscopy.

Rapid and non-destructive identification is achieved once a suitable spectral database has been established. Measurements with the Mira M-1 Raman spectrometer require no sample preparation and deliver immediate, unambiguous results.

Raman spectra of differente polystyrene samples

Figure 1. Raman spectra of different polystyrene samples. Image Credit: Metrohm Middle East FZC

Polymers are a fundamental component of modern industry. Handheld Raman spectroscopy is particularly well-suited for identifying commonly used polymers, providing results within seconds. Furthermore, as Raman analysis is nondestructive, the samples can be reused or recycled.

In the study outlined in this article, a library of common polymers in various colors was developed and utilized for the classification of unknown polymer samples.

Methods

All spectra were measured using the Mira M-1 handheld Raman spectrometer in auto-acquisition mode, allowing for integration times to be determined automatically.

A laser wavelength of 785 nm and the orbital raster scan (ORS) method was used.

As several of the polymer samples were very thin, spectra were recorded with the point-and-shoot adapter, which is appropriate for short working distances (SWD).

An extensive collection of ABS (Acrylonitrile butadiene styrene), PA (Polyamide), PC (Polycarbonate), PE (Polyethylene), PP (Polypropylene), PS (Polystyrene), PET (Polyethylene terephthalate), PVC (Poly(vinyl chloride)), and PMMA (Poly(methyl methacrylate)) polymer standards and samples of different colors was used to build a comprehensive library with the Mira Cal software.

Results and Discussion

Overlay of the spectra of selected polymer samples (plot made with MATLAB)

Figure 2. Overlay of the spectra of selected polymer samples (plot made with MATLAB). Image Credit: Metrohm Middle East FZC

For each type of polymer, one spectrum or color was chosen and superimposed. The overlay (Figure 2) demonstrates that each of the polymers has a unique spectrum that distinguishes it from the others.

The spectral area comprising the majority of the peaks ranges from 600 to 1800 cm-1, demonstrating that the spectral range of Mira M-1 is suitable for the studied polymer samples.

Items measured against the library

Figure 3. Items measured against the library. Image Credit: Metrohm Middle East FZC

The spectra of various common and laboratory items of unknown polymers and different colors (Figure 3) were tested against the library.

The library, constructed using polymer standards of different colors, was useful for identifying the test samples. Opaque samples could be identified color-specifically, while transparent and translucent samples were often only identified as such.

Overlay of the spectra various dark-colored polymers

Figure 4. Overlay of the spectra of various dark-colored polymers. Image Credit: Metrohm Middle East FZC

As Figure 4 shows, the signals of the dark samples (such as black, grey, and dark blue) were very low in intensity; no polymer-specific peak could be seen. This phenomenon can be found in many spectroscopic methods and is due to the absorption of the laser light by carbon black.

As identification of the dark samples (mainly dark grey and black) was not achievable, they were excluded; only transparent, translucent, and light-colored samples were retained in the library.

The spectral correlation values, indicating how well the sample spectrum matches the reference spectrum in the library, were higher than 0.90 for all measured samples (including but not limited to those shown in Figure 3). All polymer samples were thus unambiguously classified using the Mira M-1 spectrometer.

Conclusions

Overall, this study shows that Mira M-1 can be utilized to classify unambiguously various polymers of different colors by measuring their spectra and matching them with samples from a library in a process that takes only a few seconds.

Issues may appear only when dark-colored polymers must be analyzed. Such samples strongly absorb the spectrometer’s laser light, and thus, some polymer-specific peaks do not appear in the spectrum. Samples that are dark in color, therefore, cannot be identified by Raman spectroscopy.

This information has been sourced, reviewed and adapted from materials provided by Metrohm Middle East FZC.

For more information on this source, please visit Metrohm Middle East FZC.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Metrohm Middle East FZC. (2024, October 09). Polymer Identification Using Raman Spectroscopy. AZoM. Retrieved on October 23, 2024 from https://www.azom.com/article.aspx?ArticleID=23842.

  • MLA

    Metrohm Middle East FZC. "Polymer Identification Using Raman Spectroscopy". AZoM. 23 October 2024. <https://www.azom.com/article.aspx?ArticleID=23842>.

  • Chicago

    Metrohm Middle East FZC. "Polymer Identification Using Raman Spectroscopy". AZoM. https://www.azom.com/article.aspx?ArticleID=23842. (accessed October 23, 2024).

  • Harvard

    Metrohm Middle East FZC. 2024. Polymer Identification Using Raman Spectroscopy. AZoM, viewed 23 October 2024, https://www.azom.com/article.aspx?ArticleID=23842.

Ask A Question

Do you have a question you'd like to ask regarding this article?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.