Zero-Background Surface-Enhanced Raman Scattering Detection of Cymoxanil Based on the Change of the Cyano Group after Ultraviolet Irradiation

Raman silent region - based method for detection of pesticides with cyano group

Based on the fact that not all chemical substances possess good Raman signals, this article focuses on the Raman silent region signals of pesticides with cyano group. Under the optimized conditions of methanol-water (1:1, v/v) as the solvent, irradiation at 302 nm light source for 20 min, and the use of 0.5 mol/L KI as the aggregating agent, Surface-enhanced Raman spectroscopy (SERS) method for azoxystrobin detection was developed by the Raman silent region signal of 2230 cm-1, and verified by detecting the spiked grapes with different concentrations of azoxystrobin. Other four pesticides with cyano group also could be identified at the peak of 2180 cm-1, 2205 cm-1, 2125 cm-1, and 2130 cm-1 for acetamiprid, phoxim, thiacloprid and cymoxanil, respectively. When azoxystrobin or acetamiprid was mixed respectively with chlorpyrifos without cyano group, their SERS signals in the Raman silent region of chlorpyrifos were not interfered, while mixed with cymoxanil in different ratios (1:4, 1:1 and 4:1), respectively, each two pesticides with cyano group could be distinguished by the changes in the Raman silent region. In further, four pesticides with or without cyano group were mixed together in 1:1:1:1 (acetamiprid, cymoxanil, azoxystrobin chlorpyrifos), and each pesticide still could be identified even at 0.5 mg/L. The results showed that the SERS method combined with UV irradiation may provide a new way to monitor the pesticides with C≡N performance in the Raman silent region without interference from the food matrix.

Biomedical applications, perspectives and tag design concepts in the cell - silent Raman window

Spectroscopic studies increasingly employ Raman tags exhibiting a signal in the cell - silent region of the Raman spectrum (1800-2800 cm-1), where bands arising from biological molecules are inherently absent. Raman tags bearing functional groups which contain a triple bond, such as alkyne and nitrile or a carbon-deuterium bond, have a distinct vibrational frequency in this region. Due to the lack of spectral background and cell-associated bands in the specific area, the implementation of those tags can help overcome the inherently poor signal-to-noise ratio and presence of overlapping Raman bands in measurements of biological samples. The cell - silent Raman tags allow for bioorthogonal imaging of biomolecules with improved chemical contrast and they have found application in analyte detection and monitoring, biomarker profiling and live cell imaging. This review focuses on the potential of the cell - silent Raman region, reporting on the tags employed for biomedical applications using variants of Raman spectroscopy.

Background-Free SERS Nanosensor for Endogenous Hydrogen Sulfide Detection Based on Prussian Blue-Coated Gold Nanobipyramids

Surface-enhanced Raman scattering (SERS) has great potential in biological analysis due to its specificity, sensitivity, and non-invasive nature. However, effectively extracting Raman information and avoiding spectral overlapping from biological background interference remain major challenges. In this study, we developed a background-free SERS nanosensor consisting of gold nanobipyramids (Au NBPs) core-Prussian blue (PB) shell (Au NBPs@PB), for endogenous H2S detection. The PB shell degraded quickly upon contact with endogenous H2S, generating a unique Raman signal response in the Raman silent region (1800-2800 cm-1). By taking advantage of the high SERS-activity of Au NBPs and H2S-triggered spectral changes of PB, these SERS nanosensors effectively minimize potential biological interferences. The nanosensor exhibits a detection range of 2.0 μM to 250 μM and a limit of detection (LOD) of 0.34 μM, with good reproducibility and minimal interference. We successfully applied this background-free SERS platform to monitor endogenous H2S concentrations in human serum samples with satisfied results.

Python-assisted detection and photothermal inactivation of Salmonella typhimurium and Staphylococcus aureus on a background-free SERS chip

In this study, a background-free surface-enhanced Raman scattering (SERS) chip with a sandwich configuration was fabricated to enable reliable detection and photothermal inactivation of multiple bacteria. The SERS chip consists of a graphene-coated, phenylboronic-modified plasmonic gold substrate (pAu/G/PBA), and two aptamer-functionalized core (gold)-shell (Prussian blue/Poly-L-lysine and 4-mercaptobenzonitrile/polydopamine) SERS tags (Au@PB@PLL@Apt and Au@MB@PDA@Apt). The detection signals rely on the characteristic and nonoverlapping Raman bands of the SERS tags within the Raman-silent region (1800-2800 cm-1), where no background signals from the sample matrix are observed, leading to improved detection sensitivity and accuracy. Considering the relatively large size of bacteria (e.g., micron level), a rapid Raman mapping technique was chosen over conventional point-scan methods to achieve more reliable quantitative analysis of bacteria. This technique involves collecting and analyzing intensity signals of SERS tags from all the scattering points with an average ensemble effect, which is facilitated by the use of Python. As a proof-of-concept, model bacterium of Salmonella typhimurium and Staphylococcus aureus were successfully detected using the SERS chip with a dynamic range of 10-107 CFU/mL. Additionally, the SERS chip demonstrated successful detection of these bacteria in whole blood samples. Moreover, the photothermal effect of pAu/G led to efficient bacteria elimination, achieving approximately 100% eradication. This study integrated a background-free SERS chip with a Python-assisted rapid Raman mapping technique, resulting in a reliable, rapid and accurate method for detecting and eliminating multiple bacteria, which may provide a promising alternative for multiple screening of bacteria in real samples.

Research advances of SERS analysis method based on silent region molecules for food safety detection

Food safety is a critical issue that is closely related to people's health and safety. As a simple, rapid, and sensitive detection technique, surface-enhanced Raman scattering (SERS) technology has significant potential for food safety detection. Recently, researchers have shown a growing interest in utilizing silent region molecules for SERS analysis. These molecules exhibit significant Raman scattering peaks in the cellular Raman silent region between 1800 and 2800 cm-1 avoiding overlapping with the SERS spectrum of biological matrices in the range 600-1800 cm-1, which could effectively circumvent matrix effects and improve the SERS accuracy. In this review, the application of silent region molecules-based SERS analytical technique for food safety detection is introduced, detection strategies including label-free detection and labeled detection are discussed, and recent applications of SERS analysis technology based on molecules containing alkyne and nitrile groups, as well as Prussian blue (PB) in the detection of pesticides, mycotoxins, metal ions, and foodborne pathogens are highlighted. This review aims to draw the attention to the silent region molecules-based SERS analytical technique and to provide theoretical support for its further applications in food safety detection.

The impact of modified polystyrene on lysozyme fibrillation studied by surface-enhanced Raman spectroscopy (SERS)

Nanoplastics could modulate the fibrillation of amyloid proteins. However, many chemical functional groups are adsorbed to change the interfacial chemistry of nanoplastics in the real world. Herein, this study aimed to investigate the effects of polystyrene (PS), carboxyl modified PS (PS-COOH), and amino modified PS (PS-NH₂) on the fibrillation of hen egg-white lysozyme (HEWL). Due to the differences in the interfacial chemistry, concentration was considered an essential factor. PS-NH₂ (10 μg/mL) could promote the fibrillation of HEWL similar to PS (50 μg/mL) and PS-COOH (50 μg/mL). Moreover, promoting the primary nucleation step of amyloid fibril formation was the primary reason. The differences in spatial conformation of HEWL were characterized by Fourier transform-infrared spectroscopy and surface enhanced Raman spectroscopy (SERS). Strikingly, a particular signal of SERS of HEWL incubated with PS-NH₂ at 1610 cm^-1 was found due to the interaction between amino group of PS-NH₂ and tryptophan (or tyrosine) of HEWL. Therefore, a new perspective was provided to understand the regulation of interfacial chemistry of nanoplastics on the fibrillation of amyloid proteins. Additionally, this study suggested that SERS could be a powerful method to investigate the interactions between proteins and nanoparticles.

Design and Detection of Cyanide Raman Tag pH-Responsive SERS Probes

As one of the most important parameters of biochemical analysis and detection, the pH value plays a very important role in cell function, food preservation and production, soil and water sources, and other applications. This makes it increasingly important to explore pH detection methods in depth. In this paper, a pH-responsive SERS probe based on the cyano Raman Tag was designed to realize pH sensing detection through the influence of the pH value of analytes on the displacement of the cyano Raman peak in the SERS probe. This cyano Raman tag exhibited not only excellent sensitivity in the liner range of pH 3.0-9.0 with a limit of detection (LOD) of pH 0.33, but also the anti-interference performance and stability (the relative standard deviation (RSD) was calculated to be 6.68%, n = 5). These results indicated that this pH SERS probe with the Raman cyano tag can provide new research ideas for future biological detection, bioimaging, and environmental detection.

Surface-enhanced Raman scattering (SERS) from low-cost silver nanoparticle-decorated cicada wing substrates for rapid detection of difenoconazole in potato

Potato is one of the most important food crops worldwide in terms of human consumption. However, potato farmers employ a variety of pesticides to protect crops from harmful insects and illnesses, and difenoconazole is a commonly used one that has severe effects on human health and the environment. Therefore, detecting difenoconazole quickly and correctly is critical. In this work, we fabricated AgNPs/cicada wing substrates using natural cicada segments, decorated with silver nanoparticles for surface-enhanced Raman scattering (SERS) measurements to detect trace amounts of difenoconazole in potatoes. Results indicated that a linear relationship with the coefficient of detection (R²) of 0.987 and the detection limit (LOD) of 0.016 ppm was observed by targeting a distinctive peak at 808 cm^-1 and logarithmic difenoconazole concentrations of 0.1 to 100 ppm. In addition, difenoconazole LODs in potatoes were 63 μg/kg, lower than those specified by the EU (0.1 mg/kg) and Vietnam (4 mg/kg) utilizing this new technique. Therefore, this proposed SERS method could be used to detect difenoconazole in potatoes at trace levels.

Rapid Surface-Enhanced Raman Spectroscopy Detection of Chlorothalonil in Standard Solution and Orange Peels with Pretreatment of Ultraviolet Irradiation

At present, the detection of chlorothalonil is generally based on chromatography and immunoassay; both of which are time-consuming and costly. In this study, Surface-enhanced Raman Spectroscopy (SERS) has been successfully utilized in the detection of chlorothalonil coupled with photochemistry and meanwhile, gold nanoparticles were prepared to enhance the Raman signal. Two Raman peaks (2246 cm^- 1 and 2140 cm^- 1) of chlorothalonil were appeared after ultraviolet (UV) irradiation compared to the original solution. Chlorothalonil generated excited and weakened C≡N bonds in its structure by absorbing UV energy, thus leading to two kinds of corresponding peaks. These two kinds of peaks were both selected as analytical peaks in chlorothalonil detection. Different light sources and solvents were made different contributions to the final spectra. Chlorothalonil methanol solution under 302 nm wavelength irradiation was performed the best. The 2246 cm^- 1 sharp peak represented to the normal C≡N bond appeared at first, which overall trend was significantly increased followed by a gradual decrease. The 2140 cm^- 1 broad peak represented to the weakened C≡N bond appeared later, which overall trend was increased as the irradiation time passing by and then kept stable. Natural bond orbital (NBO) analysis indicates that the downshift of C≡N bond from 2246 cm^- 1 to 2140 cm^- 1 is due to the increase of electronic populations of π* orbital of C≡N bond transited from π orbital excited by UV irradiation. The positively charged C≡N bond had more chance to approach negatively charged gold nanoparticles. The detection limit of chlorothalonil was as low as 0.1 ppm in the standard solution. Orange peels spiked with chlorothalonil oil were also detected in this paper to confirm the practical operability of this method. The SERS method may be further developed as a rapid detection of pesticides that contains a triple bond by utilizing photochemistry.