Breakthrough Raman Spectroscopy Study Reveals Key to Advanced PFAS Detection

Raman spectroscopy and chemometrics, when combined together, can help identify and distinguish between different perfluoroalkyl substances (PFAS), according to a new study published in the Journal of Hazardous Materials (1).

PFAS substances are difficult to identify and differentiate despite their prevalence in the environment (1–3). Traditional detection methods often fall short when faced with complex sample matrices or when distinguishing between structurally similar isomers (1). By using Raman spectroscopy, the researchers were able to overcome these obstacles.

Perfluoroalkyl and Polyfluoroalkyl substances. Hazardous materials for water resistance. Generated using AI. Image Credit: © Emin - stock.adobe.com

This study was led by lead researchers Hong Zhang from Sichuan University and Yiping Zhao from the University of Georgia. In their study, the research team used density function theory (DFT) to compute and analyze the Raman spectra of 40 significant PFAS compounds, as outlined in the U.S. Environmental Protection Agency’s (EPA) Draft Method 1633 (1).

By systematically comparing the Raman spectra of various PFASs, the researchers identified specific spectral regions linked to critical chemical bonds, such as carbon-carbon (C-C), CF₂, and CF₃, as well as key functional groups like -COOH, -SO₃H, and -SO₂NH₂ (1).

Their findings indicated that subtle shifts in peak locations occur when analyzing isomers, particularly with compounds like PFOA and PFOS. For instance, PFOA’s isomers showed slight peak variations in the 200–800 and 1000–1400 cm⁻¹ wavenumber regions, while PFOS revealed more pronounced differences in its spectra, especially in the 230–360, 470–680, and 1030–1290 cm⁻¹ ranges (1).

Amongst their findings, the researchers found that the Raman spectra were influenced by two factors: 1) the presence of various functional groups and 2) the length of the carbon chain. Longer carbon chains led to an increase in the number of observable Raman peaks, providing more data points for analysis (1). Distinguishing between PFASs with different functional groups also yielded markedly different peak locations (1).

To facilitate the comparison and identification of these complex spectra, the research team constructed a comprehensive spectral database. This database was enhanced by introducing controlled noise to the DFT-calculated Raman spectra, mimicking real-world analytical conditions and ensuring robust applicability (1). Principal component analysis (PCA) and t-distributed stochastic neighbor embedding were applied to this data set, demonstrating their efficacy in distinguishing between the spectra of different PFASs and their isomers (1).

This study is a microcosm of an ongoing trend in analytical science, where advanced techniques are being used more frequently in PFAS detection. Advancements in technology have allowed other spectroscopic techniques, such as surface-enhanced Raman spectroscopy (SERS), to emerge in this space. Using SERS as an example, it can strengthen Raman signals by 6–9 orders of magnitude when PFAS molecules are adsorbed onto nanostructured surfaces, making it possible to detect trace amounts of these substances (1). This capability is crucial for environmental monitoring, where even low concentrations of PFASs can have significant health and ecological impacts (1).

Another advantage of SERS technology is its potential for miniaturization. Because of the trend toward portable instrumentation, scientists seek instruments that allow for on-site analysis. Once SERS instrumentation becomes more portable and miniature, these devices could revolutionize field assessments by allowing real-time monitoring of PFAS contamination in water sources and other environments (1). This rapid response capability would be essential for mitigating the risks associated with environmental incidents and protecting ecosystems (1).

As this study shows, Raman spectroscopy has great potential in environmental analysis. The detailed vibrational modes and chemical bond sensitivities captured by Raman make it a standout tool compared to traditional methods (1).

References

1. Chen, Y.; Yang, Y.; Cui, J.; et al. Decoding PFAS Contamination via Raman Spectroscopy: A Combined DFT and Machine Learning Investigation. J. Hazard. Mater. 2024, 465, 133260. DOI: 10.1016/j.jhazmat.2023.133260
2. Wetzel, W. The Impact of PFAS in Biosolids on Land Reclamation. LCGC Suppl. 2024, 20–23. https://www.chromatographyonline.com/view/the-impact-of-pfas-in-biosolids-on-land-reclamation
3. Hroncich, C. Analyzing PFAS in Soil and Water Using ICP-MS. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/pfas-in-soil-and-water-using-icp-ms (accessed 2024-11-05).