Plasmonic Superstructure Arrays Fabricated by Laser Near-Field Reduction for Wide-Range SERS Analysis of Fluorescent Materials

Decoding PFAS contamination via Raman spectroscopy: A combined DFT and machine learning investigation

In this study, density function theory (DFT) is employed to compute Raman spectra of 40 important Perfluoroalkyl substances (PFASs) as listed in Draft Method 1633 by U.S. Environmental Protection Agent. A systematic comparison of their spectral features is conducted, and Raman peaks and vibrational modes are identified. The Raman spectral regions for the main chemical bonds (such as C-C, CF2 & CF3, O-H) and main functional groups (such as -COOH, -SO3H, -C2H4SO3H, and -SO2NH2) are identified and compared. The impacts of branching location in isomer, molecular chain length, and functional groups on the Raman spectra are analyzed. Particularly, the isomers of PFOA alter the peak locations slightly in wavenumber regions of 200 - 800 and 1000 - 1400 cm-1, while for PFOS, spectral features in the 230 - 360, 470 - 680, and 1030 - 1290 cm-1 regions exhibit significant difference. The carbon chain length can significantly increase the number of Raman peaks, while different functional groups give significantly different peak locations. To facilitate differentiation, a spectral database is constructed by introducing controlled noise into the DFT-computed Raman spectra. Subsequently, two chemometric techniques, principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE), are applied to effectively distinguish among these spectra, both for 40 PFAS compounds and the isomers. The findings demonstrate the promising potential of combining Raman spectroscopy with advanced spectral analysis methods to discriminate between distinct PFAS compounds, holding significant implications for improved PFAS detection and characterization methodologies.

The Latest Sensor Detection Methods for per- and Polyfluoroalkyl Substances

Per- and polyfluoroalkyl substances (PFASs) have emerged as a prominent environmental pollutant in recent years, primarily due to their tendency to accumulate and magnify in both the environment and living organisms. The entry of PFASs into the environment can have detrimental effects on human health. Hence, it is crucial to actively monitor and detect the presence of PFASs. The current standard detection method of PFAS is the combination of chromatography and mass spectrometry. However, this requires expensive instruments, extra sample pretreatment steps, complicated operation and long analysis time. As a result, new methods that do not rely on chromatography and mass spectrometry have been developed and applied. These alternative methods mainly include optical and electrochemical sensor methods, which offer great potential in terms of real-time field detection, instrument miniaturization, shorter analysis time, and reduced detection cost. This review provides a summary of recent advancements in PFAS detection sensors. We categorize and explain the principles and mechanisms of these sensors, and compare their limits of detection and sensitivity. Finally, we discuss the future challenges and improvements needed for PFAS sensors, such as field application, commercialization, and other related issues.

Ultra-sensitive SERS detection of perfluorooctanoic acid based on self-assembled p-phenylenediamine nanoparticle complex

PFOA is a representative perfluorinated compound that is used as a surfactant in various industrial fields. However, because PFOA has severe side effects due to its strong toxicity, such as carcinogenesis, liver damage, and immune system damage, it is crucial to enable PFOA detection with high sensitivity. Herein, we developed a perfluorooctanoic acid (PFOA) surface-enhanced Raman scattering (SERS) sensor using self-assembled p-phenylenediamine (SAp-PD) nanoparticles and an Ag SERS substrate. For the ultra-sensitive detection of PFOA, we synthesized and optimized SAp-PD, which shows a decrease in SERS intensities when reacting with PFOA. Using the Ag nanograss SERS substrate, the change in intensity that resulted from the SAp-PD and PFOA reaction was amplified. Consequently, we detected the 1.28 pM (detection limit) of PFOA in distilled water. Moreover, PFOA molecules were successfully detected in samples of the PFOA-coated frying pan and rice extraction at concentrations up to 1.69 nM and 10.3 μM, respectively.

Periodic Surface Structuring of Copper with Spherical and Cylindrical Lenses

The use of a cylindrical lens in femtosecond laser surface structuring is receiving attention to improve the processing efficiency. Here, we investigate the structures produced on a copper target, in air, by exploiting both spherical and cylindrical lenses for beam focusing, aiming at elucidating similarities and differences of the two approaches. The morphological features of the surface structures generated by ≈180 fs laser pulses at 1030 nm over areas of 8 × 8 mm² were analyzed. For the spherical lens, micron-sized parallel channels are formed on the target surface, which is covered by subwavelength ripples and nanoparticles. Instead, the cylindrical lens leads to a surface decorated with ripples and nanoparticles with a negligible presence of micro-channels. Moreover, the morphological features achieved by focusing ≈180 fs laser pulses at 515 nm with the cylindrical lens and varying the scanning parameters were also studied. The experimental results evidence a direct effect of the hatch distance used in the scanning process on the target surface that contains dark and bright bands corresponding to regions where the rippled surface contains a richer decoration or a negligible redeposition of nanoparticles. Our findings can be of interest in large area surface structuring for the selection of the more appropriate focusing configuration according to the final application of the structured surface.

Picosecond Bessel Beam Fabricated Pure, Gold-Coated Silver Nanostructures for Trace-Level Sensing of Multiple Explosives and Hazardous Molecules

A zeroth-order, non-diffracting Bessel beam, generated by picosecond laser pulses (1064 nm, 10 Hz, 30 ps) through an axicon, was utilized to perform pulse energy-dependent (12 mJ, 16 mJ, 20 mJ, 24 mJ) laser ablation of silver (Ag) substrates in air. The fabrication resulted in finger-like Ag nanostructures (NSs) in the sub-200 nm domain and obtained structures were characterized using the FESEM and AFM techniques. Subsequently, we employed those Ag NSs in surface-enhanced Raman spectroscopy (SERS) studies achieving promising sensing results towards trace-level detection of six different hazardous materials (explosive molecules of picric acid (PA) and ammonium nitrate (AN), a pesticide thiram (TH) and the dye molecules of Methylene Blue (MB), Malachite Green (MG), and Nile Blue (NB)) along with a biomolecule (hen egg white lysozyme (HEWL)). The remarkably superior plasmonic behaviour exhibited by the AgNS corresponding to 16 mJ pulse ablation energy was further explored. To accomplish a real-time application-oriented understanding, time-dependent studies were performed utilizing the AgNS prepared with 16 mJ and TH molecule by collecting the SERS data periodically for up to 120 days. The coated AgNSs were prepared with optimized gold (Au) deposition, accomplishing a much lower trace detection in the case of thiram (~50 pM compared to ~50 nM achieved prior to the coating) as well as superior EF up to ~10⁸ (~10⁶ before Au coating). Additionally, these substrates have demonstrated superior stability compared to those obtained before Au coating.