Search Results (735)

Surface-Enhanced Raman Spectroscopy (SERS) is highly attractive as an analytical technique owing to its high sensitivity, distinctive molecular specificity, and speed of analysis. It offers the potential to match the sensitivity and molecular specificity of established techniques like Gas Chromatography–Mass Spectrometry in a more affordable, faster, and portable format, providing unique solutions for challenging analytical problems such as bedside diagnostics and in-field forensic analysis. Despite these benefits, SERS currently remains a specialized technique and has not yet successfully entered the mainstream of analytical chemistry. This transition is hindered primarily by challenges in achieving robust, reliable, and especially quantitative measurements in real-world applications. Achieving quantitative SERS requires addressing core issues arising from the heterogeneous nature of enhancing substrates and the complexity of real-life samples. This perspective summarizes the fundamental challenges associated with signal variability and matrix interference. It then details modern strategies focused on standardizing performance metrics, with particular emphasis on the newly proposed SERS Performance Factor for substrate evaluation, alongside the development of advanced quantification methods (e.g., internal standardization and digital SERS) and rapid sample pretreatment protocols. Finally, emerging prospects, including the deployment of Artificial Intelligence for enhanced analysis and advancements in deep-tissue SERS sensing, are explored as critical drivers for integrating SERS into routine analytical practice. Full article

The extensive use of sulfathiazole in poultry farming has raised growing concerns regarding its residues in poultry-derived products, posing risks to human health and food safety. To overcome the limitations of conventional detection methods and address the analytical challenges posed by inherent complexity of chicken blood matrix for the detection of sulfathiazole residues in chicken blood, a rapid and sensitive surface-enhanced Raman spectroscopy (SERS) method was developed for detecting sulfathiazole residues in chicken blood. Four colloidal substrates, i.e., gold colloid A, gold colloid B, gold colloid C, and silver colloids, were synthesized and evaluated for their SERS enhancement capabilities. Key parameters, including electrolyte type (NaCl solution), colloidal substrate type (gold colloid A), volume of gold colloid A (550 μL), volume of NaCl solution (60 μL), and adsorption time (14 min), were systematically optimized to maximize SERS intensities at 1157 cm⁻¹. Furthermore, a genetic algorithm-support vector regression (GA-SVR) model integrated with adaptive iteratively reweighted penalized least squares (air-PLS) and multiplicative scatter correction (MSC) preprocessing demonstrated superior predictive performance with a prediction set coefficient of determination (R²_p) value of 0.9278 and a root mean square error of prediction (RMSEP) of 3.1552. The proposed method demonstrated high specificity, minimal matrix interference, and robustness, making it suitable for reliable detection of sulfathiazole residues in chicken blood and compliant with global food safety requirements. Full article

Single exosomes are detected via surface-enhanced Raman scattering (SERS) due to electromagnetic field accumulation on a specially designed flexible metasurface. This metasurface is a modulated silver nanofilm deposited on a thin, flexible plastic substrate. An explicit Equation for calculating the local electric field is given. The field reaches extremely high values under plasmon resonance conditions and fills the depressions of the metasurface. The thin, flexible metasurface can be incorporated into automated Lab-On-Chip analytical systems and used for spectroscopic studies of exosomes. We propose a method to distinguish individual exosomes from the HEK293T cell line on the metasurface and then obtain and assign their SERS spectra. An important advantage of the plasmonic metasurface presented in this work is its spatial complementarity to exosomes and other vesicle-like objects. The plasmonic metasurface is fabricated using holographic lithography and further investigated using a correlation approach combining atomic force microscopy, scanning spreading resistance microscopy, and surface-enhanced spectroscopy. Full article

Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive technique for detecting heavy metals through the plasmonic effect of metallic nanoparticles. In this study, TiO₂ nanotubes were used as substrates due to their stability, large surface area, and ordered morphology. Silver nanostructures were electrodeposited to enhance the SERS response by generating hot spots. The influence of voltage and Ag concentration on electrodeposition was analyzed using methylene blue (1 × 10⁻⁵ M) as a probe molecule. Higher voltages and concentrations promoted dendritic growth, reaching Raman intensities above 70,000 a.u., optimizing sensitivity. All experiments were conducted in triplicate to ensure reproducibility. Full article

This study presents the synthesis and comprehensive characterization of tin dioxide nanoparticles (SnO₂NPs). SnO₂NPs were obtained using a conventional wet-chemistry route and an environmentally friendly green-chemistry approach employing plant extracts from rooibos leaves (Aspalathus linearis), pomegranate seeds (Punica granatum), and kiwifruit peels (family Actinidiaceae). The thermal stability and decomposition profiles were analyzed by thermogravimetric analysis (TGA), while their structural and physicochemical properties were investigated using X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDS), ultraviolet–visible (UV–Vis) spectroscopy, dynamic light scattering (DLS), Raman spectroscopy, and attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy. Transmission electron microscopy (TEM) confirmed the nanoscale morphology and uniformity of the obtained particles. The photocatalytic activity of SnO₂NPs was evaluated via the degradation of methyl orange (MeO) under UV irradiation, revealing that nanoparticles synthesized using rooibos extract exhibited the highest efficiency (68% degradation within 180 min). Furthermore, surface-enhanced Raman scattering (SERS) spectroscopy was employed to study the adsorption behavior of L-phenylalanine (L-Phe) on the SnO₂NP surface. To the best of our knowledge, this is the first report demonstrating the use of pure SnO₂ nanoparticles as SERS substrates for biologically active, low-symmetry molecules. The calculated enhancement factor (EF) reached up to two orders of magnitude (10²), comparable to other transition metal-based nanostructures. These findings highlight the potential of SnO₂NPs as multifunctional materials for biomedical and sensing applications, bridging nanotechnology and regenerative medicine. Full article

Cancer is the disease found to be the reason for the largest portion of deaths in the world annually and these mortality values are expected to increase in the future. Early detection of cancer biomarkers may help save millions of lives, particularly by implementing non-invasive and economical detection methods. In this review, we tabulated and quantitatively compared the data collected in 173 rows from 124 publications, which describe the clinical application of various methods in detection of cancer biomarkers. Those methods include mass spectrometry (MS), immunoassays (IAs), enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), surface-enhanced Raman spectroscopy (SERS), and Fourier-transform infrared spectroscopy (FTIR). We found that direct methods may have an advantage over indirect methods. Direct SERS reported in clinical applications can also achieve a higher area under the curve, higher sensitivity, and specificity than those parameters for ELISA, PCR, MS, and FTIR applications. Based on the average area under the curve (AUC) values reported in the last 6–7 years for each method, the performance of the analytical methods for the clinical cancer detection increases from IAs (0.76), ELISA (0.83), MS (0.87), and PCR (0.89) to FTIR (0.95) and SERS (0.97). Full article

This research focused on the synthesis of triangular silver nanoplates (TSNPs) with sharp corners using a photomediated seed growth method. The TSNPs produced had an average edge length of 27.2 ± 9.2 nm and a (110) crystalline plane structure. In terms of optical properties, the TSNPs displayed three key absorbance peaks at approximately 400 nm, 500 nm, and 660 nm, which correspond to out-of-plane dipolar resonance, in-plane quadrupolar resonance, and in-plane dipolar resonance, respectively. The prepared TSNP colloidal solutions served as surface-enhanced Raman spectroscopy (SERS)-active materials for detecting paraquat residue in aqueous samples. We optimized the mixing time of the liquid SERS with the sample, maintaining a 1:1 volume ratio. The findings showed a remarkable enhancement of the Raman signal with 10 min mixing time using laser excitation at a wavelength of 785 nm. This study achieved the development of novel SERS-active substrates capable of detecting pesticides with excellent accuracy, sensitivity, and reproducibility for both qualitative and quantitative analysis in tap water, river water, drinking water, and cannabis water. Additionally, it paved the way for using the SERS technique as a promising approach in the areas of food safety and environmental monitoring, especially in the organic farming field. Full article

Raman spectroscopy has become a key tool for resolving the molecular behavior of interfaces due to its non-invasiveness, fingerprinting ability and in situ detection advantages. Surface-enhanced Raman scattering (SERS) and its derivative techniques (including SHINERS and TERS) have significantly overcome the challenges of weak interfacial signals and strong water interference through the synergistic effect of electromagnetic field enhancement and chemical enhancement. They have realized highly sensitive molecular detection at various interfaces such as solid–liquid, gas–liquid, water–oil, and so on. Despite the challenges of substrate stability and signal quantization, the deep integration of multi-technology coupling and theoretical computation will further promote the breakthrough of this technology in interface science. In this review, we systematically review the applications of Raman spectroscopy and SERS techniques in interface resolution, including key research directions such as analyzing interfacial molecular structures, detecting material reactions at water–oil interface, and tracking the evolution of electrochemical interfacial species, as well as exploring the technological bottlenecks and future development directions. Full article

Nano-engineered sensor systems represent a paradigm shift in disease diagnostics, offering unprecedented capabilities for precision medicine. This review methodically evaluates these advanced platforms, consolidating recent advancements across four critical clinical domains: diabetes monitoring, cancer detection, infectious disease diagnostics and cardiac/genetic health. We demonstrate how the unique properties of nanomaterials, such as graphene, quantum dots and plasmonic nanoparticles, are being harnessed to achieve remarkable gains in analytical sensitivity, selectivity and real-time monitoring. Specific breakthroughs include graphene-based sensors attaining clinically significant limits for continuous glucose monitoring, quantum dot bioconjugates enabling ultrasensitive imaging of cancer biomarkers and surface-enhanced Raman spectroscopy (SERS) probes facilitating early tumor identification. Furthermore, nanosensors exhibit exceptional precision in detecting viral antigens and genetic mutations, underscoring their robust translational potential. Collectively, these developments signal a clear trajectory toward integrated, intelligent healthcare ecosystems. However, for these promising technologies to transition into accessible and cost-effective diagnostic solutions, persistent challenges in scalability, manufacturing reproducibility and long-term biocompatibility must be addressed through continued interdisciplinary innovation. Full article

Hexaconazole, a triazole-class fungicide, demonstrates broad-spectrum protective and therapeutic activity against fungal pathogens, particularly those from Basidiomycota and Ascomycota, such as brown spot and powdery mildew. Despite its efficacy in controlling Actinidia brown spot disease in kiwifruit, excessive hexaconazole residues pose significant health risks due to its high toxicity. To address this challenge, a rapid analytical method for detecting hexaconazole residues in kiwifruit was developed using surface-enhanced Raman spectroscopy (SERS). The methodology employed silver colloid (C-AgNPs) as the active substrate and 1 mol/L NaCl as the aggregation agent, optimized through systematic testing, resulting in an optimal volume ratio of 400:225 between C-AgNPs and hexaconazole solution and a sequential mixing order of C-AgNPs + NaCl + Hexaconazole, followed by a 20 min incubation period. The characteristic Raman peak at 1584 cm⁻¹ was identified as the spectral signature for hexaconazole quantification. Analytical validation revealed a linear detection range of 0.25–2.25 mg/L (R² = 0.9870), precision with a relative standard deviation (RSD) of 1.7%, and an average recovery rate of 88.40–105.50%, confirming the method’s robustness. This approach enables rapid, non-destructive analysis with minimal sample pretreatment, offering high sensitivity and stability. This method demonstrates great potential for detecting hexaconazole residues in agricultural products. Full article

The Raman spectrum of adenine and the surface-enhanced Raman spectrum (SERS) upon adsorption of adenine on an Ag₈ cluster in aqueous solution were calculated using the DFT/PBE0/Def2-TZVP method with the IEF-PCM solvent model. TD-DFT calculations were performed to determine the excitation wavelengths of adenine and the Ag₈•A complex, thereby selecting excitation wavelengths compatible with available experimental Raman spectroscopy instruments. In addition, excitation wavelengths with the maximum oscillator strength were chosen to propose characteristic spectra for experimental studies. The calculated Raman activities were converted into Raman scattering intensities, and the enhancement factor EF_int was determined. The results show that an excitation wavelength of 325 nm gives the strongest and most distinct SERS signal, 532 nm provides stable signals suitable for commercial instruments, while 442 nm significantly reduces several characteristic vibrational bands. Moreover, the Ag₈ cluster exhibits excellent enhancement of the Raman signal for adenine. This study provides a basis for selecting excitation wavelengths and characteristic vibrational modes to identify adenine, supporting the development of label-free biosensors based on silver clusters. Full article

Rapid and accurate diagnostics for influenza viruses are essential for preventing future epidemics. Surface-enhanced Raman spectroscopy (SERS) presents a promising alternative to conventional techniques, offering a rapid, cost-effective, and highly sensitive platform for influenza virus detection. It is a highly sensitive analytical technique that enables the detection of minute chemical substances through significant signal enhancement. It operates by illuminating a sample with a laser and analyzing the scattered light to generate a unique molecular Raman spectrum. The sensitivity of SERS is derived from its use of metal nanoparticles, which amplify the weak Raman signals, making it particularly effective for detecting low-concentration targets such as viruses. Avian influenza (AI) is a major threat to domestic poultry, leading to large-scale culling during outbreaks. It leads to economic losses globally and can also infect pigs and humans, potentially causing a pandemic. Migratory birds spread various strains, leading to the development of highly pathogenic viruses. Viral monitoring is crucial for prevention strategies and understanding the virus evolution. This review outlines the challenges in detecting AI virus in chickens and critically assesses the established and emerging diagnostic technologies, with a specific focus on the factors influencing detection and recent advances in SERS-based AI detection. Ultimately, this review aims to provide insights that will assist the influenza research community in developing novel strategies for monitoring and preventing AI outbreaks in chickens and mitigating zoonotic transmission. Full article

This paper provides an overview of thin-layer chromatography (TLC) and high-performance thin-layer chromatography (HPTLC) methods for analyzing plant materials and herbal formulations, as described in scientific publications from January 2022 to July 2025. It describes the use of TLC in the qualitative and quantitative examination of plant materials and pharmaceutical preparations containing herbs, including profiling plant materials using TLC and applying it to HPTLC plates. It also describes other modern methods that improve component separations, such as applying TLC to profile plant formulations and detect adulterations and contaminants in them. Additionally, it discusses TLC coupled with other methods, such as principal component analysis (PCA), hierarchical cluster analysis (HCA), orthogonal partial least squares discriminant analysis (OPLS-DA), mass spectrometry (MS), nuclear magnetic resonance (NMR), surface-enhanced Raman spectroscopy (SERS), and image analysis (IA). The quantitative determination of biologically active compounds in herbs and herbal formulations is presented based on methods that combine TLC with densitometry. The paper also discusses TLC with effect-oriented analysis, including the detection of antimicrobial, antioxidant, enzyme-inhibiting, endocrine-disrupting, genotoxic, and cytotoxic substances. The advantages, disadvantages, and prospects of analyzing plant material using the TLC technique are indicated. TLC/HPTLC has great prospects for use by regulatory authorities due to the low cost of analysis and high throughput. Full article

Rapid detection and identification of airborne bacteria are critical for safeguarding human health, yet current technologies remain inadequate. To address this gap, we developed a multifunctional biochip that synergistically integrated a heptagonal micropillar array with a silver nanostructure–polydopamine–co–chitosan (AgNS@PDA–co–CS) composite gel to achieve highly efficient sampling, capture, enrichment, and in situ SERS detection of airborne bacteria. The integrated micropillar array increased the capture efficiency of S. aureus in aerosols from 11.4% (with a flat chip) to 86.3%, owing to its high specific surface area and its ability to generate chaotic vortices that promote bacterial impaction. Subsequent functionalization with the AgNS@PDA–co–CS gel improved the capture efficiency further to >99.9%, due to the synergistic effect of the gel’s adhesive properties and the abundant capture sites provided by the nanostructure, which collectively ensure robust bacterial retention. The incorporated AgNS also served as SERS-active sites, enabling direct identification of captured S. aureus at concentrations as low as 10⁵ CFU m⁻³ after 20 min of sampling. Furthermore, the platform successfully distinguished among three common bacterial species—S. aureus, E. coli, and Bacillus cereus—based on their SERS spectral profiles combined with principal component analysis (PCA). This work presents a synergistic strategy for simultaneous bacterial sampling, capture, enrichment, and detection, offering a promising platform for rapid airborne pathogen monitoring. Full article

Surface-enhanced Raman spectroscopy (SERS) has rapidly emerged as a powerful analytical technique for the sensitive and selective detection of organophosphorus pesticides (OPPs) in complex food matrices. This review summarizes recent advances in substrate engineering, emphasizing structure–performance relationships between nanomaterial design and molecular enhancement mechanisms. Functional groups such as P=O, P=S, and aromatic rings are highlighted as key determinants of Raman activity through combined chemical and electromagnetic effects. State-of-the-art substrates, including noble metals, carbon-based materials, bimetallic hybrids, MOF-derived systems, and emerging liquid metals, are critically evaluated with respect to sensitivity, stability, and applicability in typical matrices such as fruit and vegetable surfaces, juices, grains, and agricultural waters. Reported performance commonly achieves sub-μg L⁻¹ to low μg L⁻¹ detection limits in liquids and 10⁻³ to 10 μg cm⁻² on surfaces, with reproducibility often in the 5–15% RSD range under optimized conditions. Persistent challenges are also emphasized, including substrate variability, quantitative accuracy under matrix interference, and limited portability for real-world applications. Structure–response correlation models and data-driven strategies are discussed as tools to improve substrate predictability. Although AI and machine learning show promise for automated spectral interpretation and high-throughput screening, current applications remain primarily proof-of-concept rather than routine workflows. Future priorities include standardized fabrication protocols, portable detection systems, and computation-guided multidimensional designs to accelerate translation from laboratory research to practical deployment in food safety and environmental surveillance. Full article