Pinpointing Alkane Chain Length, Saturation, and Double Bond Regio- and Stereoisomers by Liquid Interfacial Plasmonic Enhanced Raman Spectroscopy

Quantitative Analysis of Trace Analytes with Highly Sensitive SERS Tags on Hydrophobic Interface

Surface-enhanced Raman scattering (SERS) presents a promising avenue for trace matter detection by using plasmonic nanostructures. To tackle the challenges of quantitatively analyzing trace substances in SERS, such as poor enrichment efficiency and signal reproducibility, this study proposes a novel approach using Au@internal standard@Au nanospheres (Au@IS@Au NSs) for realizing the high sensitivity and stability in SERS substrates. To verify the feasibility and stability of the SERS performances, the SERS substrates have exhibited exceptional sensitivity for detecting methyl blue molecules in aqueous solutions within the concentration range from 10-4 M to 10-13 M. Additionally, this strategy also provides a feasible way of quantitative detection of antibiotic in the range of 10-4 M to 10-10 M. Trace antibiotic residue on the surface of shrimp in aquaculture waters was successfully conducted, achieving a remarkably low detection limit of 10-9 M. The innovative approach has great potential for the rapid and quantitative detection of trace substances, which marks a noteworthy step forward in environmental detection and analytical methods by SERS.

Ultrasensitive discrimination of volatile organic compounds using a microfluidic silicon SERS artificial intelligence chip

Current gaseous sensors hardly discriminate trace volatile organic compounds at the ppt level. Herein, we present an integrated platform for simultaneously enabling rapid preconcentration, reliable surface-enhanced Raman scattering, (SERS) detection and automatic identification of trace aldehydes at the ppt level. For rapid preconcentration, we demonstrate that the nozzle-like microfluidic concentrator allows the enrichment of rare gaseous analytes by five-fold in only 0.01 ms. The enriched gas is subsequently captured and detected by an integrated silicon-based SERS chip, which is made of zeolitic imidazolate framework-8 coated silver nanoparticles grown in situ on a silicon wafer. After SERS measurement, a fully connected deep neural network is built to extract faint features in the spectral dataset and discriminate volatile organic compound classes. We demonstrate that six kinds of gaseous aldehydes at 100 ppt could be detected and classified with an identification accuracy of ∼80.9% by using this platform.

Monitoring the lipid oxidation and fatty acid profile of oil using algorithm-assisted surface-enhanced Raman spectroscopy

Deep-fat frying of food develops lipid oxidation products that deteriorate oil and pose a health risk. This necessitates the development of a rapid and accurate oil quality and safety detection technique. Herein, surface-enhanced Raman spectroscopy (SERS) and sophisticated chemometric techniques were used for rapid and label-free determination of peroxide value (PV) and fatty acid composition of oil in-situ. In the study, plasmon-tuned and biocompatible Ag@Au core-shell nanoparticle-based SERS substrates were used to obtain optimum enhancement despite matrix interference to efficiently detect the oil components. The potent combination of SERS and the Artificial Neural Network (ANN) method could determine the fatty acid profile and PV with upto 99% accuracy. Moreover, the SERS-ANN method could quantify the low level of trans fats, i.e., < 2%, with 97% accuracy. Therefore, the developed algorithm-assisted SERS system enabled the sleek and rapid monitoring and on-site detection of oil oxidation.

Establishing carbon-carbon double bond position and configuration in unsaturated fatty acids by gas-phase infrared spectroscopy

Fatty acids are an abundant class of lipids that are characterised by wide structural variation including isomeric diversity arising from the position and configuration of functional groups. Traditional approaches to fatty acid characterisation have combined chromatography and mass spectrometry for a description of the composition of individual fatty acids while infrared (IR) spectroscopy has provided insights into the functional groups and bond configurations at the bulk level. Here we exploit universal 3-pyridylcarbinol ester derivatization of fatty acids to acquire IR spectra of individual lipids as mass-selected gas-phase ions. Intramolecular interactions between the protonated pyridine moiety and carbon-carbon double bonds present highly sensitive probes for regiochemistry and configuration through promotion of strong and predictable shifts in IR resonances. Gas-phase IR spectra obtained from unsaturated fatty acids are shown to discriminate between isomers and enable the first unambiguous structural assignment of 6Z-octadecenoic acid in human-derived cell lines. Compatibility of 3-pyridylcarbinol ester derivatization with conventional chromatography-mass spectrometry and now gas-phase IR spectroscopy paves the way for comprehensive structure elucidation of fatty acids that is sensitive to regio- and stereochemical variations and with the potential to uncover new pathways in lipid metabolism.

Online Quantitative Analysis of Chlorine Contents in Chlorinated Paraffins by Facile Raman Spectroscopy

Online analysis of industrial chemicals is extremely important for managing product quality and performance. The chlorine (Cl) content is one of the most important technical metrics for chlorinated paraffins (CPs), and the conventional approaches to estimate Cl contents require transforming the Cl element to chloride followed by quantitative analysis with either titration or instrumentation, which are normally tedious and time-consuming and cannot simultaneously guide the industrial production. Here, we developed a rapid, real-time, and online approach to determine the Cl content of CPs with facile Raman spectroscopy. The chlorination of paraffins generated two new Raman peaks at 610-618 and 668-690 cm^-1, which are associated with the vibrational modes of the S_HH and S_HC conformations of the C-Cl bond in CPs, respectively. More importantly, the corresponding peak of the S_HH conformation decreased and that of the S_HC conformation increased with the enhancement of the chlorination degree of CPs. The ratiometric calculation of the two respective Raman peak areas leads to a quantitative analysis of the Cl content of CPs. The developed approach can online provide the Cl contents of CPs within seconds accurately but without the tedious sample treatment required by conventional approaches. The strategy of integrating Raman analysis with the industrial pipeline will help in managing the production and quality control of industrial chemicals.

Terahertz spectral identification and low-frequency vibrational analysis of dinitrotoluene isomers

Identifying dinitrotoluene (DNT) isomers has always been a challenging problem. In this study, five DNT isomers were investigated using terahertz time-domain spectroscopy (THz-TDS), which demonstrated significant spectral differences including variations in absorption positions and intensities. This suggests that THz-TDS is ideal for rapid identification of DNT isomers. We also employed density functional theory to further discuss the origin of these spectral differences. The results indicate that steric effects between substitute groups, rather than inter-molecular hydrogen bonding, lead to differences in low-frequency vibrations.