Recent developments in quantitative SERS: Moving towards absolute quantification

Improving 5-halouracils SERS detection driven by Watson & Crick pairing recognition. A spectroscopic & DFT study

The halogenated C5-substituted uracil derivatives (5-fluor-, 5-chloro, and 5-bromouracil) have drawn attention recently due to their pharmacological uses, properties, and importance as biomarkers and water pollutants. From an analytical point of view, these species are expected to be at very low levels in biological and environmental samples, and the development of methodologies for their determination is a central goal in research. The Raman technique and one of its special effects, Surface-Enhanced Raman Scattering (SERS), is a very suitable approach for detecting and quantifying these compounds. In practice, enhancing Raman scattering requires a nanostructured noble metal surface with the species of interest attached to it. Still, to maximize the effect, a deeper comprehension of the nature of the analyte-metal surface interaction is desirable. The structural information SERS spectra provide can be complemented by theoretical approaches, such as the Density Functional Theory (DFT) calculations. This work studied three 5-halouracils attached to silver nanoparticles (AgNPs) from experimental and theoretical perspectives. The observed patterns in the spectroscopic behavior showed a trend related to the electronegativity at the halogenated moieties, suggesting their direct influence in enhancing CC and CO stretching modes. Then, the formation of base pairs with adenine through hydrogen bonding was studied as a strategy to improve the detectability through SERS, supported by the well-known high affinity of adenine towards metal nanoparticles. We show that adenine favors the orientation of the 5-halouracils, reaching an additional signal enhancement that is very useful for analytical purposes, as demonstrated for 5-FU, reaching a limit of detection (LOD) of 2.36 nmol L-1. Wavenumber shifts and intensification of NH modes observed in the SERS spectra, along with DFT calculations, strongly suggest that forming hydrogen bonding (NH----N) upon the interaction of the base pairs with an Ag20 cluster is key for improving the halouracils LOD through SERS.

Label-free surface-enhanced Raman scattering quantitative analysis of dual electromagnetically enhanced flexible core-shell nanoparticles containing internal standards

We designed and synthesized a flexible Au@PB@Ag NPs-CFs surface-enhanced Raman scattering (SERS) substrate with self-calibration functionality. Compared to traditional core-shell structured substrates with internal standards, our proposed substrate, which fully encapsulates a Prussian Blue (PB) layer, exhibits dual electromagnetic enhancement effects on both the PB self-calibration signal and the pesticide signal due to the localized surface plasmon resonance within the silver shell cavity. The results show that after signal calibration, the relative standard deviation decreased from 30.34 % to 11.24 %. The water-dispersible Au@0.8 PB@Ag NPs loaded on chitosan demonstrated extremely high sensitivity for the detection of alcohol-soluble pesticides thiram and thiabendazole, with detection limits as low as 0.015 μM and 0.098 μM, respectively. Additionally, due to the substrate's flexibility and excellent uniformity, it effectively addresses the "coffee ring" effect and enables quantitative detection through direct swabbing, with spiked recovery rates ranging from 81 % to 116.6 %.

The role of focused laser plasmonics in shaping SERS spectra of molecules on nanostructured surfaces

Over fifty years have passed since the groundbreaking discovery of Surface Enhanced Raman Scattering (SERS), yet many aspects of this phenomenon remain elusive. In this study, we unveil novel observations concerning the spatial variation of SERS signal profiles through vertical (Z axis) scans, performed by varying the distance between the laser focus and a solid, planar, nanostructured SERS substrate. The signal strength profile manifests a Lorentzian shape during axial scans along the Z direction, consistently peaking above the actual sample surface. More intriguingly, the intensity ratio of various spectral regions-including SERS bands and background-exhibits significant non-constancy along the Z axis. Finite-Difference Time-Domain (FDTD) simulations suggest that these variations can be attributed to specific plasmonic near-field responses induced by the focused/defocused beam at the SERS substrate. This research highlights the critical need to consider that focus imprecision can alter spectral profiles in SERS analyses on solid nanostructured SERS substrates, particularly when devising quantitative assays based on band intensity ratios.

Laser wavelength selection in Raman spectroscopy

Research in Raman spectroscopy continues to abound in a diverse range of application spaces and concurrently, components of Raman systems have become increasingly sophisticated. Laser wavelength choice is a key question in any Raman spectroscopy experiment, and the wavelength required, or indeed wavelengths, depends on a number of factors. For instance, are trace compounds being interrogated and thus plasmonic enhancement required? Or, are the experiments targeted at a specific molecule, or class of analytes, which are resonant at a specific wavelength range? Safety, resolution, and ease of post-processing spectra, can also be crucial in the decision process. While laser vendors commonly offer guidance in terms of what to consider when picking lasers for Raman studies, advice tends to be succinct. In this article, we discuss these variables more comprehensively, alongside the needs within certain kinds of experiments, to assist the Raman spectroscopist in their laser choice.

White Light Transmission Spectroscopy for Rapid Quality Control Imperfection Identification in Nanoimprinted Surface-Enhanced Raman Spectroscopy Substrates

Miniaturized biomedical sensor development requires improvements in lithographic processes in terms of cost and scalability. Of particular promise is nanoimprint lithography (NIL), but this can suffer from a lack of high-fidelity pattern reproducibility between master and imprinted substrates. Herein, we present a multidisciplinary investigation into gold- and iron-coated NIL sensors including custom optics and spectroscopy, scanning probe microscopy, and data analysis insights. Polyurethane NIL-made nanodome arrays were interrogated with white light transmission spectroscopy, coupled with principal component analysis (PCA) to investigate potential offsets in the photon-substrate plane interaction angle, an imperfection in NIL substrates. Large-angle mismatches (2-10°) were found to be easily discernible by PCA with statistically significant differences (p = 0.05). Unexpected dips in some spectra are postulated to be due to interacting localized and propagating plasmon polaritons, which is supported with a coupled two-oscillator model. General insights are made regarding the interpretation of PCA loadings, which should be related to physical phenomena, and where maximum variance is not necessarily the most meaningful criterion. Smaller angles (<1°) show no significant differences with overlapping confidence intervals in PCA space. Surface-enhanced Raman spectroscopy (SERS) measurements on gold-coated nanodomes returned relative standard deviations of 6-10% via analysis of gelatin, which is of interest as a nasal lining approximation. Interestingly, nanodomes coated in iron produced small, but useful SERS enhancements, which was subsequently interrogated via scanning thermal probe microscopy showing temperature increases of up to 5 °C over the area of one nanostructure (∼1 μm2). Nanostructures remained intact despite the surprising large local temperature increase relative to a gold-coated comparison sample (∼2 °C). The current study provides a framework for the rapid and accurate quality control assessment of imperfections in NIL-produced nanostructures for sensing applications in SERS and surface plasmon resonance, which may need precisely fabricated nanostructures.

Comparative Analysis of Machine Learning Algorithms Used for Translating Aptamer-Antigen Binding Kinetic Profiles to Diagnostic Decisions

Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitations, we developed a framework that facilitates the application of machine learning (ML) to diagnostic data for the binary classification of clinical samples, when using real-time electrochemical measurements. The framework was applied to a real-time multimeric aptamer assay (RT-MAp) that captures single-frequency (12.6 Hz) impedance data during the binding of viral protein targets to trimeric aptamers. The impedance data collected from 172 COVID-19 saliva samples were processed through multiple nonlinear regression models to extract nine key features from the transient signals. These features were then used to train three supervised ML algorithms─support vector machine (SVM), artificial neural network (ANN), and random forest (RF)─using a 75:25 training-testing ratio. Traditional ROC-based classification achieved an accuracy of 83.6%, while ML-based models significantly improved performance, with SVM, ANN, and RF achieving accuracies of 86.0%, 100%, and 100%, respectively. The ANN model demonstrated superior performance in handling complex and high-variance biosensor data, providing a robust and scalable solution for improving diagnostic accuracy in point-of-care settings.

Coupling of chromatography with surface-enhanced Raman spectroscopy: trends and prospects

Surface-enhanced Raman spectroscopy is a powerful analytical technique for the determination of analytes with the advantages of sensitivity, portability, and simplicity, able to provide structural information for the identification of compounds. However, when it comes to the analysis of complex samples, matrix components may interfere with the analyte quantification. To overcome this shortcoming, a number of approaches have been proposed, such as extraction techniques. Among them, the coupling of chromatography with surface-enhanced Raman spectroscopy seems to be promising. It allows combining the advantages of both techniques, i.e., high efficiency of chromatographic separation and high sensitivity of surface enhanced Raman scattering detection, and makes possible simultaneous quantification of multiple analytes. The review summarizes the latest achievements in the combination of these techniques.

Use of analytical strategies to understand spatial chemical variation in bacterial surface communities

Not only do surface-growing microbes such as biofilms display specific traits compared to planktonic cells, but also they display many heterogeneous behaviors over many spatial and temporal contexts. While the application of molecular genetics tools to extract or visualize gene expression or regulatory function data is now common in studying surface growth, the use of analytical chemistry tools to visualize the spatiotemporal distribution of chemical products synthesized by these surface microbes is less common. Here, we review chemical imaging tools that have been used to inform our understanding of surface-growing microbes. We highlight the use of confocal Raman Microscopy, surface-enhanced Raman spectroscopy, matrix-assisted laser desorption/ionization, secondary ion mass spectrometry, desorption electrospray ionization, and electrochemical imaging that have been applied to assess two-dimensional chemical profiles of bacteria. We specifically discuss the use of these tools to study rhamnolipids, alkylquinolones, and phenazines of the bacterium Pseudomonas aeruginosa.

Rational side-by-side self-assembly of gold nanorods with short and medium aspect ratios via the self-evaporation method to boost their potential as a surface-enhanced Raman scattering (SERS) substrate

Surface-enhanced Raman scattering (SERS) represents a compelling detection methodology centered on the electromagnetic fields, commonly termed "hot spots", generated around noble nanoparticles. Nonetheless, the efficacy of electromagnetic field (EMF) amplification is constrained when utilizing individual nanoparticles. There has been a notable lack of experimental and theoretically simulated studies regarding the increase of the electromagnetic field when gold nanorods with different aspect ratios undergo self-assembly in either perpendicular or parallel orientations to substrates. This research presents a novel and facile methodology for fabricating SERS nanosubstrates. This method entails self-assembling gold nanorods (AuNRs) with short and medium aspect ratios (ARs) through natural evaporation. By manipulating the water-to-ethanol ratios, we ascertain the appropriate conditions for the rational alignment of the nanorods in both perpendicular and parallel orientations relative to the silicon substrate. These nanosubstrates have been experimentally evaluated for their ability to improve the Surface-Enhanced Raman Scattering (SERS) performance, presenting a novel perspective in this field. In addition, a computational analysis employing the finite-difference time-domain (FDTD) method was conducted to elucidate the electromagnetic field generated by nanoarrays when subjected to incident light of varying wavelengths, including 532 nm, 638 nm, and 785 nm. Notably, the FDTD simulation outcomes indicated that gold nanorods (AuNRs) possessing an aspect ratio of 3.0 and nanogaps of 2.0 nm exhibited exceptional electromagnetic field characteristics when aligned parallel to the substrate under 532 nm laser illumination. Conversely, when the AuNRs were oriented perpendicular to the substrates, they produced lower EMFs upon interaction with excitation laser light. These findings can potentially contribute to the advancement of SERS nanosubstrate design.

Factors that Affect Quantification in Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) is an analytical technique capable of detecting trace amounts of specific species. The uniqueness of vibrational signatures is a major advantage of SERS. This combination of sensitivity and specificity has motivated researchers to develop diverse analytical methodologies leveraging SERS. However, even 50 years after its first observation, SERS is still perceived as an unreliable technique for quantification. This perception has precluded the application of SERS in laboratories that rely on consistent quantification (for regulatory purposes, for instance). In this review, we describe some of the aspects that lead to SERS intensity variations and how those challenges were addressed in the 50 years of the technique. The goal is to identify the sources of variations in SERS intensities and then demonstrate that, even with these pitfalls, the technique can be used for quantification when factors such as nature of the substrate, experimental conditions, sample preparation, surface chemistry, and data analysis are carefully considered and tailored for a particular application.

Surface-enhanced Raman spectroscopy: a half-century historical perspective

Surface-enhanced Raman spectroscopy (SERS) has evolved significantly over fifty years into a powerful analytical technique. This review aims to achieve five main goals. (1) Providing a comprehensive history of SERS's discovery, its experimental and theoretical foundations, its connections to advances in nanoscience and plasmonics, and highlighting collective contributions of key pioneers. (2) Classifying four pivotal phases from the view of innovative methodologies in the fifty-year progression: initial development (mid-1970s to mid-1980s), downturn (mid-1980s to mid-1990s), nano-driven transformation (mid-1990s to mid-2010s), and recent boom (mid-2010s onwards). (3) Illuminating the entire journey and framework of SERS and its family members such as tip-enhanced Raman spectroscopy (TERS) and shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) and highlighting the trajectory. (4) Emphasizing the importance of innovative methods to overcome developmental bottlenecks, thereby expanding the material, morphology, and molecule generalities to leverage SERS as a versatile technique for broad applications. (5) Extracting the invaluable spirit of groundbreaking discovery and perseverant innovations from the pioneers and trailblazers. These key inspirations include proactively embracing and leveraging emerging scientific technologies, fostering interdisciplinary cooperation to transform the impossible into reality, and persistently searching to break bottlenecks even during low-tide periods, as luck is what happens when preparation meets opportunity.

Detection and quantification of ergothioneine in human serum using surface enhanced Raman scattering (SERS)

Ergothioneine (ERG) is a natural sulfur-containing amino acid found in many organisms, including humans. It accumulates at high concentrations in red blood cells and is distributed to various organs, including the brain. ERG has numerous health benefits and antioxidant capabilities, and it has been linked to various human physiological processes, such as anti-inflammatory, neuroprotective, and anti-aging effects. Accurate, rapid, and cost-effective quantification of ERG levels in human biofluids is crucial for understanding its role in oxidative stress-related diseases. Surface-enhanced Raman scattering (SERS) is an effective approach for measuring compounds at concentrations similar to those at which ERG is present in serum. However, while SERS has been used to characterize or detect ERG, quantification has not yet been achieved due to the variability in the signal enhancement that can arise during sample preparation and analysis. This study introduces a highly efficient and reliable technique for quickly (20 min is typical per sample) measuring ERG levels in human serum using SERS. This employs an internal standard highly specific for ERG which resulted in limit of quantification values of 0.71 μM. To validate this approach, we analysed real human serum with unknown ERG levels as a blind test set and primary reference levels of ERG were produced using a targeted UHPLC-MS/MS reference method.

A practical approach to quantitative analytical surface-enhanced Raman spectroscopy

Many of the features of SERS, such as its high sensitivity, molecular specificity and speed of analysis make it attractive as an analytical technique. However, SERS currently remains a specialist technique which has not yet entered the mainstream of analytical chemistry. Therefore, this review draws out the underlying principles for analytical SERS and provides practical tips and tricks for SERS quantitation. The aim is to show the readers how to rationally design their SERS experiments to improve quantitation performance. We begin by introducing the three core components in SERS analysis: (1) the enhancing substrate material, (2) the Raman instrument and (3) the processed data that is used to establish a calibration curve. This is followed by discussion of the analytical figures of merit relevant to SERS. In the following sections each of the three essential components in SERS quantitation and how they affect the quality of the analysis are described in more detail using examples from the literature. Finally, we highlight the current challenges in applying SERS to the analysis of complex real-life samples and briefly introduce the state-of-the-art developments on multifunctional substrates, digital SERS and AI-assisted data processing, which will help SERS rise to the challenge of moving out into routine real-world analysis.

Freshness in Salmon by Hand-Held Devices: Methods in Feature Selection and Data Fusion for Spectroscopy

Salmon fillet was analyzed via hand-held optical devices: fluorescence (@340 nm) and absorption spectroscopy across the visible and near-infrared (NIR) range (400-1900 nm). Spectroscopic measurements were benchmarked with nucleotide assays and potentiometry in an exploratory set of experiments over 11 days, with changes to spectral profiles noted. A second enlarged spectroscopic data set, over a 17 day period, was then acquired, and fillet freshness was classified ±1 day via four machine learning (ML) algorithms: linear discriminant analysis, Gaussian naïve, weighted K-nearest neighbors, and an ensemble bagged tree method. Dual-mode data fusion returned almost perfect accuracies (mean = 99.5 ± 0.51%), while single-mode ML analyses (fluorescence, visible absorbance, and NIR absorbance) returned lower mean accuracies at greater spread (77.1 ± 10.1%). Single-mode fluorescence accuracy was especially poor; however, via principal component analysis, we found that a truncated fluorescence data set of four variables (wavelengths) could predict "fresh" and "spoilt" salmon fillet based on a subtle peak redshift as the fillet aged, albeit marginally short of statistical significance (95% confidence ellipse). Thus, whether by feature selection of one spectral data set, or the combination of multiple data sets through different modes, this study lays the foundation for better determination of fish freshness within the context of rapid spectroscopic analyses.

Determination of multiple analytes in urine using label-free SERS coupled with simple sample pretreatments

BACKGROUND

A key restriction of label-free surface-enhanced Raman spectroscopy (SERS) in analysis of objects with complex composition (including with several target analytes) is the competition of mixture components for interaction with SERS-active surface. This leads to poor selectivity of the analysis of such mixtures (e.g., body fluids) and the need to use advanced sample pretreatment procedures such as HPLC or TLC. Therefore, this work aims to develop a set of simple and fast pretreatment steps (dilution, pH correction, etc.) to increase the sorption of the target analyte, reduce the sorption of admixtures, and prevent suppression of the target analyte SERS signal.

RESULTS

We have developed label-free SERS assay suitable for the determination of three analytes (methotrexate, cephalosporin antibiotic, and creatinine) in one real urine sample as a model matrix with complex and deviating composition. The choice of drugs is justified by the need to monitor their concentration in urine during joint drug treatment of cancer patients with concomitant bacterial infection, while monitoring creatinine concentration helps to evaluate kidney function of the patients. Additionally, three cephalosporin representatives were used in the study to maximize versatility of the assay. As a results, the optimized pretreatment steps enable to eliminate the negative influence of excess of interferences (including other analytes) and achieve precise (≤12 % RSD) and accurate (88-111 % recovery) determination of several analytes in the therapeutically relevant ranges: 300-3000 μg mL-1 for creatinine, 20-200 μg mL-1 for methotrexate and cephalosporins.

SIGNIFICANCE

Therefore, in addition to reporting a new SERS assay for the analysis of body fluids, this study clearly demonstrates the importance of taking into account competitive adsorption processes on the SERS substrate surface. We suggest making this practice mandatory when developing any label-free SERS assay because it enables to maximize the selectivity and accuracy of the analysis as well as to simplify the analysis procedure.

In situ study of the interactions between metal surfaces and cationic surfactant corrosion inhibitors by surface-enhanced Raman spectroscopy coupled with visible spectroscopy

Cationic surfactants are widely used as corrosion inhibitors for industrial tubings and pipelines. They protect the surface of steel pipes through a film-forming mechanism, providing both anodic and cathodic inhibition. To improve the efficiency of the corrosion protection, it is essential to understand the interactions between the surfactants and metal surfaces. To achieve this, surface enhanced Raman spectroscopy (SERS) can serve as a powerful tool due to its surface sensitivity and potential to detect trace amounts of analytes in complex media. In this contribution, we have investigated the behaviour of in situ prepared AgNPs in the presence of benzalkonium chloride as a model corrosion inhibitor using SERS coupled to visible spectroscopy and combined with light scattering methods. By combining these experimental methods, we were able to correlate the aggregation of silver particles with the concentration of added surfactant in the resulting mixture. Using this insight, we also established a SERS method for the detection of benzalkonium chloride traces in water. For this, we utilised the quenching of the SERS response of methylene blue by competitive adsorption of methylene blue and the surfactant on SERS active AgNPs. We believe that our approach can serve a variety of applications to improve the industrial water treatment. For example, the modelling of the interaction of different surfactants with SERS can be used for process intensification, and ultimately, to move towards the digital twinning of corrosion processes for more efficient corrosion inhibition. Furthermore, the ability to adapt our sensing protocol for on-line corrosion inhibitor monitoring allows a fast response to process changes, hence, enabling resource-efficient, continuous process control.

Surface-Enhanced Raman Spectroscopy at the Interface between Drug Discovery and Personalized Medicine

Personalized medicine and drug discovery are different, yet overlapping, fields, and information from each field is exchanged to improve the other. The current methods used for devising personalized therapeutic plans and developing drug discovery applications are costly, time-consuming, and complex; thus, their applicability is limited in both fields. However, surface-enhanced Raman spectroscopy (SERS) offers potential solutions to current challenges. This Mini-Review explores the utility of SERS in drug discovery and personalized medicine. The Mini-Review starts with a brief overview of these fields, including the main challenges and current methods, and then explores examples where SERS has been used to overcome some of the main challenges in both fields. It ends with brief conclusions, perspectives, and current challenges limiting the practical application of SERS.

Advancing SERS as a quantitative technique: challenges, considerations, and correlative approaches to aid validation

Surface-enhanced Raman scattering (SERS) remains a significant area of research since it's discovery 50 years ago. The surface-based technique has been used in a wide variety of fields, most prominently in chemical detection, cellular imaging and medical diagnostics, offering high sensitivity and specificity when probing and quantifying a chosen analyte or monitoring nanoparticle uptake and accumulation. However, despite its promise, SERS is mostly confined to academic laboratories and is not recognised as a gold standard analytical technique. This is due to the variations that are observed in SERS measurements, mainly caused by poorly characterised SERS substrates, lack of universal calibration methods and uncorrelated results. To convince the wider scientific community that SERS should be a routinely used analytical technique, the field is now focusing on methods that will increase the reproducibility of the SERS signals and how to validate the results with more well-established techniques. This review explores the difficulties experienced by SERS users, the methods adopted to reduce variation and suggestions of best practices and strategies that should be adopted if one is to achieve absolute quantification.

Metal-Organic Frameworks in Surface Enhanced Raman Spectroscopy-Based Analysis of Volatile Organic Compounds

Volatile Organic Compounds (VOC) are a major class of environmental pollutants hazardous to human health, but also highly relevant in other fields including early disease diagnostics and organoleptic perception of aliments. Therefore, accurate analysis of VOC is essential, and a need for new analytical methods is witnessed for rapid on-site detection without complex sample preparation. Surface-Enhanced Raman Spectroscopy (SERS) offers a rapidly developing versatile analytical platform for the portable detection of chemical species. Nonetheless, the need for efficient docking of target analytes at the metallic surface significantly narrows the applicability of SERS. This limitation can be circumvented by interfacing the sensor surface with Metal-Organic Frameworks (MOF). These materials featuring chemical and structural versatility can efficiently pre-concentrate low molecular weight species such as VOC through their ordered porous structure. This review presents recent trends in the development of MOF-based SERS substrates with a focus on elucidating respective design rules for maximizing analytical performance. An overview of the status of the detection of harmful VOC is discussed in the context of industrial and environmental monitoring. In addition, a survey of the analysis of VOC biomarkers for medical diagnosis and emerging applications in aroma and flavor profiling is included.

Using surface-enhanced Raman scattering for simultaneous multiplex detection and quantification of thiols associated to axillary malodour

Axillary malodour is caused by the microbial conversion of human-derived precursors to volatile organic compounds. Thiols strongly contribute to this odour but are hard to detect as they are present at low concentrations. Additionally, thiols are highly volatile and small making sampling and quantification difficult, including by gas chromatography-mass spectrometry. In this study, surface-enhanced Raman scattering (SERS), combined with chemometrics, was utilised to simultaneously quantify four malodourous thiols associated with axillary odour, both in individual and multiplex solutions. Univariate and multivariate methods of partial least squares regression (PLS-R) were used to calculate the limit of detection (LoD) and results compared. Both methods yielded comparable LoD values, with LoDs using PLS-R ranging from 0.0227 ppm to 0.0153 ppm for the thiols studied. These thiols were then examined and quantified simultaneously in 120 mixtures using PLS-R. The resultant models showed high linearity (Q2 values between 0.9712 and 0.9827 for both PLS-1 and PLS-2) and low values of root mean squared error of predictions (0.0359 ppm and 0.0459 ppm for PLS-1 and PLS-2, respectively). To test this approach further, these models were challenged with 15 new blind test samples, collected independently from the initial samples. This test demonstrated that SERS combined with PLS-R could be used to predict the unknown concentrations of these thiols in a mixture. These results display the ability of SERS for the simultaneous multiplex detection and quantification of analytes and its potential for future development for detecting gaseous thiols produced from skin and other body sites.

Digital surface enhanced Raman spectroscopy for quantifiable single molecule detection in flow

Surface enhanced Raman scattering (SERS) provides a label free method of analyzing molecules from diverse and complex signals, potentially with single molecule sensitivity. The chemical specificity inherent in the SERS spectrum can identify molecules; however signal variability arising from the diversity of plasmonic environments can limit quantification, particularly at low concentrations. Here we show that digitizing, or counting SERS events, can decrease the limit of detection in flowing solutions enabling quantification of single molecules. By using multivariate curve resolution and establishing a score threshold, each individual spectrum can be classified as containing an event or not. This binary "yes/no" can then be quantified, and a linear region can be established. This method was shown to lower the limit of detection to the lowest physical limit, and lowered the limit of detection by an order of magnitude from the traditional, intensity based LOD calculations.

Label-free single-vesicle based surface enhanced Raman spectroscopy: A robust approach for investigating the biomolecular composition of small extracellular vesicles

Small extracellular vesicles (sEVs) are cell-released vesicles ranging from 30-150nm in size. They have garnered increasing attention because of their potential for both the diagnosis and treatment of disease. The diversity of sEVs derives from their biological composition and cargo content. Currently, the isolation of sEV subpopulations is primarily based on bio-physical and affinity-based approaches. Since a standardized definition for sEV subpopulations is yet to be fully established, it is important to further investigate the correlation between the biomolecular composition of sEVs and their physical properties. In this study, we employed a platform combining single-vesicle surface-enhanced Raman spectroscopy (SERS) and machine learning to examine individual sEVs isolated by size-exclusion chromatography (SEC). The biomolecular composition of each vesicle examined was reflected by its corresponding SERS spectral features (biomolecular "fingerprints"), with their roots in the composition of their collective Raman-active bonds. Origins of the SERS spectral features were validated through a comparative analysis between SERS and mass spectrometry (MS). SERS fingerprinting of individual vesicles was effective in overcoming the challenges posed by EV population averaging, allowing for the possibility of analyzing the variations in biomolecular composition between the vesicles of similar and/or different sizes. Using this approach, we uncovered that each of the size-based fractions of sEVs contained particles with predominantly similar SERS spectral features. Indeed, more than 84% of the vesicles residing within a particular group were clearly distinguishable from that of the other EV sub-populations, despite some spectral variations within each sub-population. Our results suggest the possibility that size-based EV fractionation methods produce samples where similarly eluted sEVs are correlated with their respective biochemical contents, as reflected by their SERS spectra. Our findings therefore highlight the possibility that the biogenesis and respective biological functionalities of the various sEV fractions may be inherently different.

Surface-Enhanced Raman Spectroscopy: Current Understanding, Challenges, and Opportunities

While surface-enhanced Raman spectroscopy (SERS) has experienced substantial advancements since its discovery in the 1970s, it is an opportunity to celebrate achievements, consider ongoing endeavors, and anticipate the future trajectory of SERS. In this perspective, we encapsulate the latest breakthroughs in comprehending the electromagnetic enhancement mechanisms of SERS, and revisit CT mechanisms of semiconductors. We then summarize the strategies to improve sensitivity, selectivity, and reliability. After addressing experimental advancements, we comprehensively survey the progress on spectrum-structure correlation of SERS showcasing their important role in promoting SERS development. Finally, we anticipate forthcoming directions and opportunities, especially in deepening our insights into chemical or biological processes and establishing a clear spectrum-structure correlation.

Quantitative and rapid detection of nanoplastics labeled by luminescent metal phenolic networks using surface-enhanced Raman scattering

The escalating prevalence of nanoplastics contamination in environmental ecosystems has emerged as a significant health hazard. Conventional analytical methods are suboptimal, hindered by their inefficiency in analyzing nanoplastics at low concentrations and their time-intensive processes. In this context, we have developed an innovative approach that employs luminescent metal-phenolic networks (L-MPNs) coupled with surface-enhanced Raman spectroscopy (SERS) to separate and label nanoplastics, enabling rapid, sensitive and quantitative detection. Our strategy utilizes L-MPNs composed of zirconium ions, tannic acid, and rhodamine B to uniformly label nanoplastics across a spectrum of sizes (50-500 nm) and types (e.g., polystyrene, polymethyl methacrylate, polylactic acid). Rhodamine B (RhB) functions as a Raman reporter within these L-MPNs-based SERS tags, providing the requisite sensitivity for trace measurement of nanoplastics. Moreover, the labeling with L-MPNs aids in the efficient separation of nanoplastics from liquid media. Utilizing a portable Raman instrument, our methodology offers cost-effective, swift, and field-deployable detection capabilities, with excellent sensitivity in nanoplastic analysis and a detection threshold as low as 0.1 μg/mL. Overall, this study proposes a highly promising strategy for the robust and sensitive analysis of a broad spectrum of particle analytes, underscored by the effective labeling performance of L-MPNs when coupled with SERS techniques.

Electrochemical synthesis of 2D-silver nanodendrites functionalized with cyclodextrin for SERS-based detection of herbicide MCPA

Surface enhanced Raman spectroscopy (SERS) is a powerful analytical technique that has found application in the trace detection of a wide range of contaminants. In this paper, we report on the fabrication of 2D silver nanodendrites, on silicon chips, synthesized by electrochemical reduction of AgNO3at microelectrodes. The formation of nanodendrites is tentatively explained in terms of electromigration and diffusion of silver ions. Electrochemical characterization suggests that the nanodendrites do not stay electrically connected to the microelectrode. The substrates show SERS activity with an enhancement factor on the order of 106. Density functional theory simulations were carried out to investigate the suitability of the fabricated substrate for pesticide monitoring. These substrates can be functionalized with cyclodextrin macro molecules to help with the detection of molecules with low affinity with silver surfaces. A proof of concept is demonstrated with the detection of the herbicide 2-methyl-4-chlorophenoxyacetic acid (MCPA).

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.

Enhancement Factors: A Central Concept during 50 Years of Surface-Enhanced Raman Spectroscopy

In this Perspective, we provide an overview of the core concepts around surface-enhanced Raman spectroscopy (SERS) enhancement factors (EFs), including both theoretical and experimental considerations: EF definitions, the distinction between maximum and average EFs, EF distribution and hot-spot localization, EF measurement and its order of magnitude. We then highlight some of the current challenges in this field, focusing on a selection of topics that we feel are both topical and important: analyte-capture onto a SERS substrate, surface-enhanced resonant Raman scattering, orientation/tensorial effects, and nonradiative effects. We hope this Perspective can provide a platform to reflect on the past 50 years of SERS and its future.

A 3D printed sheath flow interface for surface enhanced Raman spectroscopy (SERS) detection in flow

Surface enhanced Raman spectroscopy (SERS) is an effective technique for detecting molecules in aqueous solutions due to its insensitivity to water, which makes it especially useful for biological samples. Utilizing SERS in flow can aid in a variety of applications such as metabolomics, pharmaceuticals, and diagnostics. The ability to 3D print complex objects enables rapid dissemination of prototypes. A 3D printed flow cell for sheath flow SERS detection has been developed that can incorporate a variety of planar substrates. The 3D printed flow cell incorporates hydrodynamic focusing, a sheath flow, that confines the analyte near the SERS substrate. Since the SERS signal obtained relies on the interaction between analyte molecules and nanostructures, sheath flow increases the detection efficiency and eliminates many issues associated with SERS detection in solution. This device was optimized by analyzing both molecules and particles with and without using sheath flow for SERS detection. Our results show that the flow rates can be optimized to increase the SERS signal obtained from a variety of analytes, and that the signal was increased when using sheath flow. This 3D printed flow cell offers a straightforward method to disseminate this technology and to facilitate online SERS detection.

In situ electrochemical regeneration of nanogap hotspots for continuously reusable ultrathin SERS sensors

Surface-enhanced Raman spectroscopy (SERS) harnesses the confinement of light into metallic nanoscale hotspots to achieve highly sensitive label-free molecular detection that can be applied for a broad range of sensing applications. However, challenges related to irreversible analyte binding, substrate reproducibility, fouling, and degradation hinder its widespread adoption. Here we show how in-situ electrochemical regeneration can rapidly and precisely reform the nanogap hotspots to enable the continuous reuse of gold nanoparticle monolayers for SERS. Applying an oxidising potential of +1.5 V (vs Ag/AgCl) for 10 s strips a broad range of adsorbates from the nanogaps and forms a metastable oxide layer of few-monolayer thickness. Subsequent application of a reducing potential of -0.80 V for 5 s in the presence of a nanogap-stabilising molecular scaffold, cucurbit[5]uril, reproducibly regenerates the optimal plasmonic properties with SERS enhancement factors ≈106. The regeneration of the nanogap hotspots allows these SERS substrates to be reused over multiple cycles, demonstrating ≈5% relative standard deviation over at least 30 cycles of analyte detection and regeneration. Such continuous and reliable SERS-based flow analysis accesses diverse applications from environmental monitoring to medical diagnostics.

'When is a hotspot a good nanospot' - review of analytical and hotspot-dominated surface enhanced Raman spectroscopy nanoplatforms

Substrate development in surface-enhanced Raman spectroscopy (SERS) continues to attract research interest. In order to determine performance metrics, researchers in foundational SERS studies use a variety of experimental means to characterize the nature of substrates. However, often this process would appear to be performed indiscriminately without consideration for the physical scale of the enhancement phenomena. Herein, we differentiate between SERS substrates whose primary enhancing structures are on the hundreds of nanometer scale (analytical SERS nanosubstrates) and those whose main mechanism derives from nanometric-sized gaps (hot-spot dominated SERS substrates), assessing the utility of various characterization methods for each substrate class. In this context, characterization approaches in white-light spectroscopy, electron beam methods, and scanning probe spectroscopies are reviewed. Tip-enhanced Raman spectroscopy, wavelength-scanned SERS studies, and the impact of surface hydrophobicity are also discussed. Conclusions are thus drawn on the applicability of each characterization technique regarding amenability for SERS experiments that have features at different length scales. For instance, while white light spectroscopy can provide an indication of the plasmon resonances associated with 10 s-100 s nm-scale structures, it may not reveal information about finer surface texturing on the true nm-scale, critical for SERS' sensitivity, and in need of investigation via scanning probe techniques.

Artificial Intelligence for Surface-Enhanced Raman Spectroscopy

Surface-enhanced Raman spectroscopy (SERS), well acknowledged as a fingerprinting and sensitive analytical technique, has exerted high applicational value in a broad range of fields including biomedicine, environmental protection, food safety among the others. In the endless pursuit of ever-sensitive, robust, and comprehensive sensing and imaging, advancements keep emerging in the whole pipeline of SERS, from the design of SERS substrates and reporter molecules, synthetic route planning, instrument refinement, to data preprocessing and analysis methods. Artificial intelligence (AI), which is created to imitate and eventually exceed human behaviors, has exhibited its power in learning high-level representations and recognizing complicated patterns with exceptional automaticity. Therefore, facing up with the intertwining influential factors and explosive data size, AI has been increasingly leveraged in all the above-mentioned aspects in SERS, presenting elite efficiency in accelerating systematic optimization and deepening understanding about the fundamental physics and spectral data, which far transcends human labors and conventional computations. In this review, the recent progresses in SERS are summarized through the integration of AI, and new insights of the challenges and perspectives are provided in aim to better gear SERS toward the fast track.

Aiming for Maximized and Reproducible Enhancements in the Obstacle Race of SERS

Surface enhanced Raman scattering (SERS), since its discovery in the mid-1970s, has taken on many roles in the world of analytical measurement science. From identifying known and unknown chemicals in mixtures such as pharmaceutical and environmental samples to enabling qualitative and quantitative analysis of biomolecules and biomedical disease markers (or biomarkers), furthermore expanding to tracking nanostructures in vivo for medical diagnosis and therapy. This is because SERS combines the inherent power of Raman scattering capable of molecular species identification, topped with tremendous amplification in the Raman signal intensity when the molecule of interest is positioned near plasmonic nanostructures. The higher the SERS signal amplification, the lower the limit of detection (LOD) that could be achieved for the above applications. Therefore, improving SERS sensing efficiencies is vital. The signal reproducibility and SERS enhancement factor (EF) heavily rely on plasmonic nanostructure design, which has led to tremendous work in the field. But SERS signal and EF reproducibility remain key limitations for its wider market usability. This Review will scrutinize factors, some recognized and some often overlooked, that dictate the SERS signal and are of utmost importance to enable reproducible SERS EFs. Most of the factors pertain to colloidal labeled SERS. Some critically reviewed factors include the nanostructure's surface area as a limiting factor, SERS hot-spots including optimizing the SERS EF within the hot-spot volume and positioning labels, properties of label molecules governing molecule orientation in hot-spots, and resonance effects. A better understanding of these factors will enable improved optimization and control of the experimental SERS, enabling extremely sensitive LODs without overestimating the SERS EFs. These are crucial steps toward identification and reproducible quantification in SERS sensing.

Thiol-ene click derivatization reaction coupled with ratiometric surface-enhanced Raman scattering for reproducible and accurate determination of acrylamide

Acrylamide (AA) is a carcinogen mainly ingested through food and drinking water, making its accurate determination crucial for both food safety and environmental protection. Herein, we proposed a derivatization-based ratiometric surface-enhanced Raman scattering (SERS) method for the quantification of AA. High density Au NPs were anchored to the surface of Cu-TCPP MOF nanosheets (MOFNs) to form the SERS sensor. The abundant Raman "hot spots" at the nanogaps generated by the Au NPs and the internal standard (IS) signal provided by Cu-TCPP MOFNs improved the sensitivity and quantitative accuracy of the method. Following the thiol-ene click derivatization reaction between p-aminothiophenol (PATP) and AA, the Raman peak intensity ratio (I1080/I395) was employed to quantify AA. The linear range was 0.1 nM to 10 μM, and the limit of detection (LOD) was as low as 0.08 nM. Trace amounts of AA in food and water samples were successfully determined using this method.

Application of microfluidic technology based on surface-enhanced Raman scattering in cancer biomarker detection: A review

With the continuous discovery and research of predictive cancer-related biomarkers, liquid biopsy shows great potential in cancer diagnosis. Surface-enhanced Raman scattering (SERS) and microfluidic technology have received much attention among the various cancer biomarker detection methods. The former has ultrahigh detection sensitivity and can provide a unique fingerprint. In contrast, the latter has the characteristics of miniaturization and integration, which can realize accurate control of the detection samples and high-throughput detection through design. Both have the potential for point-of-care testing (POCT), and their combination (lab-on-a-chip SERS (LoC-SERS)) shows good compatibility. In this paper, the basic situation of circulating proteins, circulating tumor cells, exosomes, circulating tumor DNA (ctDNA), and microRNA (miRNA) in the diagnosis of various cancers is reviewed, and the detection research of these biomarkers by the LoC-SERS platform in recent years is described in detail. At the same time, the challenges and future development of the platform are discussed at the end of the review. Summarizing the current technology is expected to provide a reference for scholars engaged in related work and interested in this field.

From the lab to the field: handheld surface enhanced Raman spectroscopy (SERS) detection of viral proteins

Translating sensors from the lab benchtop to a readily available point-of-need setting is desirable for many fields, including medicine, agriculture, and industry. However, this transition generally suffers from loss of sensitivity, high background signals, and other issues which can impair reproducibility. Here we adapt a label-free surface-enhanced Raman spectroscopy (SERS) sensor for SARS-CoV-2 antigens from a lab-based assay to a handheld device. Utilizing a peptide capture molecule, which we previously employed for a surface-based assay, we optimize a simpler and more cost-efficient nanoparticle-based assay. This new assay allows for the direct detection of these viral antigens by SERS, now with the advantages of robustness and portability. We highlight considerations for nanoparticle modification conditions and warn against methods which can interfere with accurate detection. The comparison of these two assays will help guide further development of SERS-based sensors into devices that can be easily used in point-of-care settings, such as by emergency room nurses, farmers, or quality control technicians.

Ultrasensitive detection of thiram based on surface-enhanced Raman scattering via Au@Ag@Ag core/shell/shell bimetallic nanorods

We developed a highly sensitive and stable SERS-active substrate of Au@Ag@Ag core/shell/shell nanorods, formed by encapsulating Au nanorods (Au NRs) into a bilayer silver shell with Raman reporter molecules (4-mercaptobenzoic acid (4-MBA) and thiram) in the shell-shell gap. The core/shell/shell nanostructures demonstrated a high SERS enhancement and easy assembly. The important role of the bilayer silver shell in boosting the SERS intensity and detection sensitivity was revealed by comparing the performances of the Au@Ag@4-MBA@Ag NRs, Au@Ag@4-MBA NRs, and Au@4-MBA NRs. The obtained Au@Ag@4-MBA@Ag NRs exhibited a significantly promoted SERS intensity, which could reach around 2.6 times and 240 times that of the Au@Ag@4-MBA NRs and Au@4-MBA NRs, where the enhancement factor was found to be strongly correlated with the shell thickness. The controllable plasma properties and SERS effect of the Au@Ag@4-MBA@Ag NRs could be optimized by adjusting the dose of silver nitrate. The SERS substrate comprising core/shell/shell nanorods was highly reproducible and stable (retaining 83% SERS intensity after one month). Moreover, the highly sensitive detection of the pesticide thiram with a detection limit as low as 1.74 × 10-9 M was achieved by taking advantage of the great SERS response of the core/shell/shell nanostructures, which was 1-2 orders of magnitude lower than for other SERS substrates. The developed SERS substrate could be readily extended to embed other target analytes into the core/shell/shell nanostructure for novel and sensitive detection. This study could enable fresh approaches toward next-generation ultrasensitive analyte detection.

Focusing ion funnel-assisted ambient electrospray enables high-density and uniform deposition of non-spherical gold nanoparticles for highly sensitive surface-enhanced Raman scattering

Surface-enhanced Raman scattering (SERS) is a powerful technique for detecting trace amounts of analytes. However, the performance of SERS substrates depends on many variables including the enhancement factor, morphology, consistency, and interaction with target analytes. In this study, we investigated, for the first time, the use of electrospray deposition (ESD) combined with a novel ambient focusing DC ion funnel to deposit a high density of gold nanoparticles (AuNPs) to generate large-area, uniform substrates for highly sensitive SERS analysis. We found that the combination of ambient ion focusing with ESD facilitated high-density and intact deposition of non-spherical NPs. This also allowed us to take advantage of a polydisperse colloidal solution of AuNPs (consisting of nanospheres and nanorods), as confirmed by finite-difference time domain (FDTD) simulations. Our SERS substrate exhibited excellent capture capacity for model analyte molecules, namely 4-aminothiophenol (4-ATP) and Rhodamine 6G (R6G), with detection limits in the region of 10-11 M and a relative standard deviation of <6% over a large area (∼500 × 500 μm2). Additionally, we assessed the quantitative performance of our SERS substrate using the R6G probe molecule. The results demonstrated excellent linearity (R2 > 0.99) over a wide concentration range (10-4 M to 10-10 M) with a detection limit of 80 pM.

A LoC-SERS platform based on triple signal amplification for highly sensitive detection of colorectal cancer miRNAs

In this work, based on a dual signal amplification strategy of enzyme-assisted signal amplification (EASA) and catalytic hairpin assembly (CHA), combined with the magnetic attraction effect, a capillary pump-driven surface-enhanced Raman scattering (SERS) microfluidic chip (LoC-SERS) platform was developed for the sensitive detection of colorectal cancer-associated (CRC) microRNA (miRNA). During the detection process, the miRNA first undergoes an EASA reaction with hairpin DNA1 (hpDNA1) under the action of endonuclease, which generates a large amount of DNA2 cyclically. After that, DNA2 triggers the CHA reaction to proceed, which leads to the ligation of the SERS nanoprobes and the capture nanoprobes (hpDNA2-hpDNA3 complexes). Finally, as the reactant solution flows through the collection zone, the end products are magnetically attracted by the micro-magnets, generating many "hot spots" and leading to a triple amplification of the SERS signal. By quantitative analysis, the platform achieved ultra-low detection limits of miR-122 (4.26 aM) and miR-192 (4.71 aM) within a linear range of 10 aM-10 pM. In addition, the platform's results for clinical samples are highly consistent with those measured by qRT-PCR methods. Overall, the proposed LoC-SERS platform is expected to be an important tool for the early screening of CRC.

Application of Paper-Based Microfluidic Analytical Devices (µPAD) in Forensic and Clinical Toxicology: A Review

The need for providing rapid and, possibly, on-the-spot analytical results in the case of intoxication has prompted researchers to develop rapid, sensitive, and cost-effective methods and analytical devices suitable for use in nonspecialized laboratories and at the point of need (PON). In recent years, the technology of paper-based microfluidic analytical devices (μPADs) has undergone rapid development and now provides a feasible, low-cost alternative to traditional rapid tests for detecting harmful compounds. In fact, µPADs have been developed to detect toxic molecules (arsenic, cyanide, ethanol, and nitrite), drugs, and drugs of abuse (benzodiazepines, cathinones, cocaine, fentanyl, ketamine, MDMA, morphine, synthetic cannabinoids, tetrahydrocannabinol, and xylazine), and also psychoactive substances used for drug-facilitated crimes (flunitrazepam, gamma-hydroxybutyric acid (GHB), ketamine, metamizole, midazolam, and scopolamine). The present report critically evaluates the recent developments in paper-based devices, particularly in detection methods, and how these new analytical tools have been tested in forensic and clinical toxicology, also including future perspectives on their application, such as multisensing paper-based devices, microfluidic paper-based separation, and wearable paper-based sensors.

Plasmonic Nanomaterials in Dark Field Sensing Systems

Plasma nanoparticles offer promise in data storage, biosensing, optical imaging, photoelectric integration, etc. This review highlights the local surface plasmon resonance (LSPR) excitation mechanism of plasmonic nanoprobes and its critical significance in the control of dark-field sensing, as well as three main sensing strategies based on plasmonic nanomaterial dielectric environment modification, electromagnetic coupling, and charge transfer. This review then describes the component materials of plasmonic nanoprobes based on gold, silver, and other noble metals, as well as their applications. According to this summary, researchers raised the LSPR performance of composite plasmonic nanomaterials by combining noble metals with other metals or oxides and using them in process analysis and quantitative detection.

Unraveling surface-enhanced Raman spectroscopy results through chemometrics and machine learning: principles, progress, and trends

Surface-enhanced Raman spectroscopy (SERS) has gained increasing attention because it provides rich chemical information and high sensitivity, being applicable in many scientific fields including medical diagnosis, forensic analysis, food control, and microbiology. Although SERS is often limited by the lack of selectivity in the analysis of samples with complex matrices, the use of multivariate statistics and mathematical tools has been demonstrated to be an efficient strategy to circumvent this issue. Importantly, since the rapid development of artificial intelligence has been promoting the implementation of a wide variety of advanced multivariate methods in SERS, a discussion about the extent of their synergy and possible standardization becomes necessary. This critical review comprises the principles, advantages, and limitations of coupling SERS with chemometrics and machine learning for both qualitative and quantitative analytical applications. Recent advances and trends in combining SERS with uncommonly used but powerful data analysis tools are also discussed. Finally, a section on benchmarking and tips for selecting the suitable chemometric/machine learning method is included. We believe this will help to move SERS from an alternative detection strategy to a general analytical technique for real-life applications.

A review on current progress of Raman-based techniques in food safety: From normal Raman spectroscopy to SESORS

Frequently occurrence of food safety incidents has induced global concern over food safety. To ensure food quality and safety, an increasing number of rapid and sensitive analytical methods have been developed for analysis of all kinds of food composition and contaminants. As one of the high-profile analytical techniques, Raman spectroscopy has been widely applied in food analysis with simple, rapid, sensitive, and nondestructive detection performance. Research on Raman techniques is a direction of great interest to many fields, especially in food safety. Hence, it is crucial to gain insight into recent advances on the use of Raman-based techniques in food safety applications. In this review, we introduce Raman techniques from normal Raman spectroscopy to developed ones (e.g., surface enhanced Raman scattering (SERS), spatially offset Raman spectroscopy (SORS), surface-enhanced spatially offset Raman spectroscopy (SESORS)), in view of their history and development, principles, design, and applications. In addition, future challenges and trends of these techniques are discussed regarding to food safety.

Chemical conjugation to differentiate monosaccharides by Raman and surface enhanced Raman spectroscopy

Sugars play important roles in numerous biological processes, from providing energy to modifying proteins to alter their function. Glycosylation, the attachment of a sugar residue to a protein, is the most common post translational modification. Identifying the glycans on a protein is a useful tool both for pharmaceutical development as well as probing the proteome and glycome further. Sugars, however, are difficult analytes to probe due to their isomeric nature. In this work, Raman spectroscopy and surface enhanced Raman spectroscopy (SERS) are used to identify different monosaccharide species based on the vibrational modes of these isomeric analytes. The weak scattering of the sugars was overcome through conjugation with phenylboronic acid to provide a larger Raman scattering cross section and induce slight changes in the observed spectra associated with the structure of the monosaccharides. Spontaneous Raman, SERS in flow, and static SERS detection were performed in order to discriminate between arabinose, fructose, galactose, glucose, mannose, and ribose, as well as provide a method for identification and quantification for these sugar conjugates.

Design of Raman reporter-embedded magnetic/plasmonic hybrid nanostirrers for reliable microfluidic SERS biosensors

Magnetic-based microfluidic SERS biosensors hold great potential in various biological analyses due to their integrated advantages including easy manipulation, miniaturization and ultrasensitivity. However, it remains challenging to collect reliable SERS nanoprobe signals for quantitative analysis due to the irregular aggregation of magnetic carriers in a microfluidic chamber. Here, magnetic/plasmonic hybrid nanostirrers embedded with a Raman reporter are developed as capture carriers to improve the reliability of microfluidic SERS biosensors. Experimental results revealed that SERS signals from magnetic hybrid nanostirrers could serve as microenvironment beacons of their irregular aggregation, and a signal filtering method was proposed through exploring the relationship between the intensity range of beacons and the signal reproducibility of SERS nanoprobes using interleukin 6 as a model target analyte. Using the signal filtering method, reliable SERS nanoprobe signals with high reproducibility could be picked out from similar microenvironments according to their beacon intensity, and then the influence of irregular aggregation of magnetic carriers on the SERS nanoprobe could be eliminated. The filtered SERS nanoprobe signals also exhibited excellent repeatability from independent tests, which lay a solid foundation for a reliable working curve and subsequent accurate bioassay. This study provides a simple but promising route for reliable microfluidic SERS biosensors, which will further promote their practical application in biological analysis.

Point-of-care community drug checking technologies: an insider look at the scientific principles and practical considerations

Drug checking is increasingly being explored outside of festivals and events to be an ongoing service within communities, frequently integrated within responses to illicit drug overdose. The choice of instrumentation is a common question, and the demands on these chemical analytical instruments can be challenging as illicit substances may be more complex and include highly potent ingredients at trace levels. The answer remains nuanced as the instruments themselves are not directly comparable nor are the local demands on the service, meaning implementation factors heavily influence the assessment and effectiveness of instruments. In this perspective, we provide a technical but accessible introduction to the background of a few common drug checking methods aimed at current and potential drug checking service providers. We discuss the following tools that have been used as part of the Vancouver Island Drug Checking Project in Victoria, Canada: immunoassay test strips, attenuated total reflection IR-absorption spectroscopy, Raman spectroscopy from powder samples, surface-enhanced Raman scattering in a solution of colloidal gold nanoparticles, and gas chromatography-mass spectrometry. Using four different drug mixtures received and tested at the service, we illustrate the strengths, limitations, and capabilities of such instruments, and expose the scientific theory to give further insight into their analytical results. Each case study provides a walk-through-style analysis for a practical comparison between data from several different instruments acquired on the same sample. Ideally, a single instrument would be able to achieve all of the objectives of drug checking. However, there is no clear instrument that ticks every box; low cost, portable, rapid, easy-to-use and provides highly sensitive identification and accurate quantification. Multi-instrument approaches to drug checking may be required to effectively respond to increasingly complex and highly potent substances demanding trace level detection and the potential for quantification.

Rapid detection and quantification of paracetamol and its major metabolites using surface enhanced Raman scattering

Paracetamol (also known as acetaminophen) is an over-the-counter (OTC) drug that is commonly used as an analgesic for mild pain, headache, cold and flu. While in the short term it is a safe and effective medicine, it is sometimes used for attempted suicides particularly in young adults. In such circumstances it is important for rapid diagnosis of overdoses as antidotes can be given to limit liver damage from one of its primary metabolites N-acetyl-p-benzoquinone imine (NAPQI). Unfortunately, the demand for rapid and sensitive analytical techniques to accurately monitor the abuse of OTC drugs has significantly risen. Ideally these techniques would be highly specific, sensitive, reproducible, portable and rapid. In addition, an ideal point of care (PoC) test would enable quantitative detection of drugs and their metabolites present in body fluids. While Raman spectroscopy meets these specifications, there is a need for enhancement of the signal because the Raman effect is weak. In this study, we developed a surface-enhanced Raman scattering (SERS) methodology in conjunction with chemometrics to quantify the amount of paracetamol and its main primary metabolites (viz., paracetamol sulfate, p-acetamidophenyl β-D-glucuronide and NAPQI) in water and artificial urine. The enhancement of the SERS signals was achieved by mixing the drug or xenometabolites with a gold nanoparticle followed by aggregation with 0.045 M NaCl. We found that the SERS data could be collected directly, due to immediate analyte association with the Au surface and colloid aggregation. Accurate and precise measurements were generated, with a limit of detection (LoD) of paracetamol in water and artificial urine at 7.18 × 10^-6 M and 2.11 × 10^-5 M, respectively, which is well below the limit needed for overdose and indeed normal levels of paracetamol in serum after taking 1 g orally. The predictive values obtained from the analysis of paracetamol in water and artificial urine were also excellent, with the coefficient of determination (Q²) being 0.995 and 0.996, respectively (1 suggests a perfect model). It was noteworthy that when artificial urine was spiked with paracetamol, no aggregating agent was required due to the salt rich medium, which led to spontaneous aggregation. Moreover, for the xenometabolites of paracetamol excellent LoDs were obtained and these ranged from 2.6 × 10^-4 M to 5 × 10^-5 M with paracetamol sulfate and NAPQI having Q² values of 0.934 and 0.892 and for p-acetamidophenyl β-D-glucuronide this was slightly lower at 0.6437.

New Model for Quantifying the Nanoparticle Concentration Using SERS Supported by Multimodal Mass Spectrometry

Surface-enhanced Raman scattering (SERS) is widely explored for the elucidation of underlying mechanisms behind biological processes. However, the capability of absolute quantitation of the number of nanoparticles from the SERS response remains a challenge. Here, we show for the first time the development of a new 2D quantitation model to allow calibration of the SERS response against the absolute concentration of SERS nanotags, as characterized by single particle inductively coupled plasma mass spectrometry (spICP-MS). A novel printing approach was adopted to prepare gelatin-based calibration standards containing the SERS nanotags, which consisted of gold nanoparticles and the Raman reporter 1,2-bis(4-pyridyl)ethylene. spICP-MS was used to characterize the Au mass concentration and particle number concentration of the SERS nanotags. Results from laser ablation inductively coupled plasma time-of-flight mass spectrometry imaging at a spatial resolution of 5 μm demonstrated a homogeneous distribution of the nanotags (between-line relative standard deviation < 14%) and a linear response of ¹⁹⁷Au with increasing nanotag concentration (R² = 0.99634) in the printed gelatin standards. The calibration standards were analyzed by SERS mapping, and different data processing approaches were evaluated. The reported calibration model was based on an "active-area" approach, classifying the pixels mapped as "active" or "inactive" and calibrating the SERS response against the total Au concentration and the particle number concentration, as characterized by spICP-MS. This novel calibration model demonstrates the potential for quantitative SERS imaging, with the capability of correlating the nanoparticle concentration to biological responses to further understand the underlying mechanisms of disease models.

Toward Quantitative Surface-Enhanced Raman Scattering with Plasmonic Nanoparticles: Multiscale View on Heterogeneities in Particle Morphology, Surface Modification, Interface, and Analytical Protocols

Surface-enhanced Raman scattering (SERS) provides significantly enhanced Raman scattering signals from molecules adsorbed on plasmonic nanostructures, as well as the molecules' vibrational fingerprints. Plasmonic nanoparticle systems are particularly powerful for SERS substrates as they provide a wide range of structural features and plasmonic couplings to boost the enhancement, often up to >10⁸-10¹⁰. Nevertheless, nanoparticle-based SERS is not widely utilized as a means for reliable quantitative measurement of molecules largely due to limited controllability, uniformity, and scalability of plasmonic nanoparticles, poor molecular modification chemistry, and a lack of widely used analytical protocols for SERS. Furthermore, multiscale issues with plasmonic nanoparticle systems that range from atomic and molecular scales to assembled nanostructure scale are difficult to simultaneously control, analyze, and address. In this perspective, we introduce and discuss the design principles and key issues in preparing SERS nanoparticle substrates and the recent studies on the uniform and controllable synthesis and newly emerging machine learning-based analysis of plasmonic nanoparticle systems for quantitative SERS. Specifically, the multiscale point of view with plasmonic nanoparticle systems toward quantitative SERS is provided throughout this perspective. Furthermore, issues with correctly estimating and comparing SERS enhancement factors are discussed, and newly emerging statistical and artificial intelligence approaches for analyzing complex SERS systems are introduced and scrutinized to address challenges that cannot be fully resolved through synthetic improvements.

An efficient and simple SERS approach for trace analysis of tetrahydrocannabinol and cannabinol and multi-cannabinoid detection

Many countries have legalized cannabis and its derived products for multiple purposes. Consequently, it has become necessary to develop a rapid, effective, and reliable tool for detecting delta-9-tetrahydrocannabinol (THC) and cannabinol (CBN), which are important biologically active compounds in cannabis. Herein, we have fabricated SERS chips by using glancing angle deposition and tuned dimensions of silver nanorods (AgNRs) for detecting THC and CBN at low concentrations. Experimental and computational results showed that the AgNR substrate with film thickness (or nanorod length) of 150 nm, corresponding to nanorod diameter of 79 nm and gap between nanorods of 23 nm, can effectively sense trace THC and CBN with good reproducibility and sensitivity. Due to limited spectral studies of the cannabinoids in previous reports, this work also explored towards identifying characteristic Raman lines of THC and CBN. This information is critical to further reliable data analysis and interpretation. Moreover, multianalyte detection of THC and CBN in a mixture was successfully demonstrated by applying an open-source independent component analysis (ICA) model. The overall method is fast, sensitive, and reliable for sensing trace THC and CBN. The SERS chip-based method and spectral results here are useful for a variety of cannabis testing applications, such as product screening and forensic investigation.

Investigation of SERS Frequency Fluctuations Relevant to Sensing and Catalysis

The excitation of plasmon resonances on nanoparticles generates locally enhanced electric fields commonly used for sensing applications and energetic charge carriers can drive chemical transformations as photocatalysts. The surface-enhanced Raman scattering (SERS) spectra from mercaptobenzoic acid (MBA) adsorbed to gold nanoparticles (AuNP) and silica encapsulated gold nanoparticles (AuNP@silica) can be used to assess the impact of energetic charge carriers on the observed signal. Measurements were recorded using a traditional point focused Raman spectroscopy and a wide-field spectral imaging approach to assess changes in the spectra of the different particles at increasing power density. The wide-field approach provides an increase in sampling statistics and shows evidence of SERS frequency fluctuations from MBA at low power densities, where it is commonly difficult to record spectra from a point focused spot. The increased spectral resolution of the point spectroscopy measurement provides improved peak identification and the ability to correlate the frequency fluctuations to charged intermediate species. Interestingly, our work suggests that isolated nanoparticles may undergo frequency fluctuations more readily than aggregates.