Plasmon-mediated photocatalytic conversion in Au or Ag nanorod aggregates by surface-enhanced Raman spectroscopy.

Plasmonic nanoparticles (NPs) hold considerable potential as photocatalysts owing to their robust light-matter interactions across diverse electromagnetic wavelengths, which significantly influence the photophysical characteristics of the adjacent molecular entities. Despite the widespread use of noble-metal NPs in surface-enhanced Raman scattering (SERS) applications, little is known about the kinetics of nanoparticle aggregation and how it affects their configurations. This study investigates the plasmon-driven photochemical conversion of 4-nitrobenzenethiol (NBT) to 4,4'-dimercaptoazobenzene (DMAB) on Au and Ag nanorods (NRs) through SERS. Significantly, photoconversion phenomena were observed on Ag NRs but not on Au NRs upon laser excitation at 633 nm. Finite-difference time-domain simulations revealed the presence of stronger electromagnetic fields on Ag NRs than on Au NRs. The aspect ratios and gaps between individual NPs in dimer configurations were determined to elucidate their effects on electromagnetic fields. The Ag NR dimer with an end-to-end configuration, an aspect ratio of 3.3, and a 1-nm gap exhibited the highest enhancement factor of 1.05 × 1012. Our results demonstrate that the primary contribution from diverse configurations in NR aggregates is the end-to-end configuration. The proposed NP design with adjustable parameters is expected to advance research in plasmonics, sensing, and wireless communications. These findings also contribute to the understanding of plasmon-driven photochemical processes in metallic nanostructures.

Silver nanoparticles modified with MoS2 and ß-cyclodextrin as SERS substrate for rapid determination of cysteamine hydrochloride in meat products.

An efficient Surface-enhanced Raman scattering (SERS) method for the detection of cysteamine hydrochloride (CSH) was developed by synthesizing a composite substrate comprising silver nanoparticles (AgNPs) functionalized with MoS2 and ß-cyclodextrin (ß-CD). The enhanced Raman signals of CSH by ß-CD/MoS2/AgNPs substrate were the contribution of electromagnetic enhancement (EM) as well as chemical enhancement (CM), and the enhancement factor (EF) can reach up to 3.11 × 106 (peak at 633 cm-1). Various instrumental techniques were used to characterize the substrate, such as X-ray diffraction (XRD), thermogravimetric analysis (TGA), transmission electron microscopy (TEM), high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) and ultraviolet visible (UV-vis). The binding of ß-CD/MoS2/AgNPs and CSH was confirmed by UV-vis and Fourier transform infrared (FT-IR). The optimal experimental conditions were determined by single factor experiments as well as response surface model. The influences of different metal ions and analogous drugs on the detection of CSH were investigated. Under optimum conditions, a good linear correlation (R = 0.9997) was established for CSH in the range of 10.00-1000.00 nmol/L, and the limit of detection (LOD) was as low as 0.78 nmol/L (S/N = 3). The contents of CSH in meat samples were detected. The recovery was 96.6-103.1 %, and the relative standard deviation (RSD) of the measurement was 0.7-3.9 % (n = 7).

3D hot spot construction on the hydrophobic interface with SERS tags for quantitative detection of pesticide residues on food surface.

The overuse of pesticides results in excessive pesticide residues, posing a potential threat to human health. Herein, this work proposes a SERS substrate for the quantitative analysis of pesticide residues on food surfaces. Au cores are assembled on PS microspheres, followed by the modification of Raman internal standards (1,4-BDT) on the gold core surface and the growth of the Au shell. After incubating the analytes with PS@Au@1,4-BDT@Au particles, the mixture is dropped on the hydrophobic gold film for drying before detection. The SERS substrates exhibited high sensitivity and stability, with a detection limit of 10-12 M and an RSD of less than 7 %. Combined with a portable Raman spectrometer, the SERS detection of pesticide residues on three kinds of food surfaces is carried out, with a sensitivity of 10-11 M, meeting the US MRLs regulations. Therefore, this strategy may possess significant potential for future food safety.

Silk Fabric Functionalized by Nanosilver Enabling the Wearable Sensing for Biomechanics and Biomolecules.

Integrating biomechanical and biomolecular sensing mechanisms into wearable devices is a formidable challenge and key to acquiring personalized health management. To address this, we have developed an innovative multifunctional sensor enabled by plasma functionalized silk fabric, which possesses multimodal sensing capabilities for biomechanics and biomolecules. A seed-mediated in situ growth method was employed to coat silver nanoparticles (AgNPs) onto silk fibers, resulting in silk fibers functionalized with AgNPs (SFs@Ag) that exhibit both piezoresistive response and localized surface plasmon resonance effects. The SFs@Ag membrane enables accurate detection of mechanical pressure and specific biomolecules during wearable sensing, offering a versatile solution for comprehensive personalized health monitoring. Additionally, a machine learning algorithm has been established to specifically recognize muscle strain signals, potentially extending to the diagnosis and monitoring of neuromuscular disorders such as amyotrophic lateral sclerosis (ALS). Unlike electromyography, which detects large muscles in clinical medicine, sensing data for tiny muscles enhance our understanding of muscle coordination using the SFs@Ag sensor. This detection model provides feasibility for the early detection and prevention of neuromuscular diseases. Beyond muscle stress and strain sensing, biomolecular detection is a critical addition to achieving effective health management. In this study, we developed highly sensitive surface-enhanced Raman scattering (SERS) detection for wearable health monitoring. Finite-difference time-domain numerical simulations ware utilized to analyze the efficacy of the SFs@Ag sensor for wearable SERS sensing of biomolecules. Based on the specific SERS spectra, automatic extraction of signals of sweat molecules was also achieved. In summary, the SFs@Ag sensor bridges the gap between biomechanical and biomolecular sensing in wearable applications, providing significant value for personalized health management.

Imaging Metabolic Flow of Water in Plants with Isotope-Traced Stimulated Raman Scattering Microscopy.

Water plays a vital role in the life cycle of plants, participating in various critical biochemical reactions during both non-photosynthetic and photosynthetic processes. Direct visualization of the metabolic activities of water in plants with high spatiotemporal resolution is essential to reveal the functional utilization of water. Here, stimulated Raman scattering (SRS) microscopy is applied to monitor the metabolic processes of deuterated water (D2O) in model plant Arabidopsis thaliana (A. thaliana). The work shows that in plants uptaking D2O/water solution, proton-transfer from water to organic metabolites results in the formation of C-D bonds in newly synthesized biomolecules (lipid, protein, and polysaccharides, etc.) that allow high-resolution detection with SRS. Reversible metabolic pathways of oil-starch conversion between seed germination and seed development processes are verified. Spatial heterogeneity of metabolic activities along the vertical axis of plants (root, stem, and tip meristem), as well as the radial distributions of secondary growth on the horizontal cross-sections are quantified. Furthermore, metabolic flow of protons from plants to animals is visualized in aphids feeding on A. thaliana. Collectively, SRS microscopy has potential to trace a broad range of matter flows in plants, such as carbon storage and nutrition metabolism.

Real-Time Monitoring of Molecules in Aqueous Solution via a Surface-Functionalized Ag-Anodic Aluminum Oxide Surface-Enhanced Raman Scattering Platform.

Real-time monitoring of molecular species in aqueous solutions is crucial for diverse scientific applications, from biomedical diagnostics to environmental analysis. In this study, we investigate the selective detection and discrimination of specific molecules in aqueous solution samples using a Ag-coated anodized aluminum oxide (Ag-AAO) surface functionalized with thiol molecules. Our investigation harnesses the power of surface-enhanced Raman scattering (SERS) synergized with principal component analysis (PCA) to elucidate the distinctive signatures of aqueous dopamine and l-tyrosine molecules. By scrutinizing the Raman spectra of surface-treated molecules, we unveil nuanced variations driven by the unique functional groups of the thiol molecules and their dynamic interactions with the target molecules in solution. Notably, we observe different alterations in the SERS spectra of Ag-AAO surface-functionalized boronic acid molecules for detection of dopamine and l-tyrosine, even at a concentration as low as 10-8 M. Moreover, the spectral PCA elucidates the discrimination of dopamine and l-tyrosine within the aqueous environment attributed to the different molecular interactions near SERS-active hotspots. Our findings facilitate real-time monitoring of minute analytes with exceptional molecular selectivity, ushering in an era of precise chemical analysis in aqueous solutions.

Tuning Nanographene-Enhanced Raman Scattering for Rapid Label-Free Detection of Amino Acids.

The rapid and sensitive detection of amino acids is important not only for fundamental studies but also for the establishment of a healthy society. However, conventional detection methods have been hampered by the difficulties of low sensitivity, long sampling and detection times, and expensive operation and instruments. Here, we report the plasma engineering of bioresource-derived graphene quantum dots (GQDs) as surface-enhanced Raman scattering (SERS)-active materials for the rapid and sensitive detection of amino acids. Surface-functionalized GQDs with tuned structures and band gaps were synthesized from earth-abundant bioresources by using reactive microplasmas under ambient conditions. Detailed microscopy and spectroscopy studies indicate that the SERS properties of the synthesized GQDs can be tuned by controlling the band gaps of synthesized GQDs. The plasma-synthesized metal-free GQDs with surface functionalities showed improved SERS properties for rapid amino acid detection with low detection limits of 10-5 M for tyrosine and phenylalanine. Theoretical calculations suggest that charge transfer between GQDs and amino acids can enhance the SERS response of the GQDs. Our work provides insights into the controlled engineering of SERS-active nanographene-based materials using the plasma-enhanced method.

Label-Free Exosome Analysis by Surface-Enhanced Raman Scattering Spectroscopy with Laser-Ablated Silver Nanoparticle Substrate.

Early diagnostics of breast cancer is crucial to reduce the risk of cancer metastasis and late relapse. Exosome, which contains distinct information of its origin, can be the target object as a liquid biopsy. However, its low sensitivity and inadequate diagnostic tools interfere with the point-of-care testing (POCT) of the exosome. Recently, Surface-enhanced Raman Scattering (SERS) spectroscopy, which amplifies the Raman scattering, has been proved as a promising tool for exosome detection. However, the fabrication process of SERS probe or substrate is still inefficient and far from large-scale production. This study proposes rapid and label-free detection of breast cancer-derived exosomes by statistical analysis of SERS spectra using silver-nanoparticle-based SERS substrate fabricated by selective laser ablation and melting (SLAM). Employing silver nanowires and optimizing laser process parameters enable rapid and low-energy fabrication of SERS substrate. The functionalities including sensitivity, reproducibility, stability, and renewability are evaluated using rhodamine 6G as a probe molecule. Then, the feasibility of POCT is examined by the statistical analysis of SERS spectra of exosomes from malignant breast cancer cells and non-tumorigenic breast epithelial cells. The presented framework is anticipated to be utilized in other biomedical applications, facilitating cost-effective and large-scale production performance.

Raman spectroscopy analysis combined with computed tomography imaging to identify microsatellite instability in gastric cancers.

Accurate determination of microsatellite instability (MSI) status is critical for tailoring treatment approaches for gastric cancer patients. Existing clinical techniques for MSI diagnosis are plagued by problems of suboptimal time efficiency, high cost, and burdensome experimental requirements. Here, we for the first time establish the classification model of gastric cancer MSI status based on Raman spectroscopy. To begin with, we reveal that tumor heterogeneity-induced signal variations pose a prominent impact on MSI classification. To eliminate this issue, we develop Euclidean distance-based Raman Spectroscopy (EDRS) algorithm, which establishes a standard spectrum to represent the "most microsatellite stable" status. The similarity between each spectrum of tissues with the standard spectrum is calculated to provide a direct assessment on the MSI status. Compared to machine learning-algorithms including k-Nearest Neighbors, Random Forest, and Extreme Learning Machine, the EDRS method shows the highest accuracy of 94.6 %. Finally, we integrate the EDRS method with the clinical diagnostic modality, computed tomography, to construct an innovative joint classification model with good classification performance (AUC = 0.914, Accuracy = 94.6 %). Our work demonstrates a robust, rapid, non-invasive, and convenient tool in identifying the MSI status, and opens new avenues for Raman techniques to fit into existing clinical workflow.

Metallo-Supramolecular Helicates as Surface-Enhanced Raman Scattering (SERS) Substrates with High Tailorability.

The exploration of novel functionalized supramolecular coordination complexes (SCCs) can enable new applications in domains that include purification and sensing. In this study, employing a coordination-driven self-assembly strategy, we designed and prepared a series of benzochalcogenodiazole-based metallohelicates as high-efficiency charge transfer surface-enhanced Raman scattering (SERS) substrates, expanding the range of applications for these metallohelicates. Through structural modifications, including the substitution of single heteroatoms on ligands, replacement of coordinating metals, and alteration of ligand framework linkages, the Raman performance of these metallohelicates as substrates were systematically optimized. Notably, the SERS enhancement factors (EFs) of the metallohelicate-based SERS substrates were significantly enhanced to levels as high as 1.03 × 107, which rivals the EFs of noble metals devoid of "hot spots". Additionally, the underlying Raman enhancement mechanisms of these metallohelicates have been investigated through a combination of control experiments and theoretical calculations. This study not only demonstrates the utility of metallohelicates as SERS substrates but also offers insights and materials for the development of high-efficiency new charge transfer SERS substrates.

A Machine Learning-Driven Surface-Enhanced Raman Scattering Analysis Platform for the Label-Free Detection and Identification of Gastric Lesions.

Background: Gastric lesions pose significant clinical challenges due to their varying degrees of malignancy and difficulty in early diagnosis. Early and accurate detection of these lesions is crucial for effective treatment and improved patient outcomes. Methods: This paper proposed a label-free and highly sensitive classification method for serum of patients with different degrees of gastric lesions by combining surface-enhanced Raman scattering (SERS) and machine learning analysis. Specifically, we prepared Au lotus-shaped (AuLS) nanoarrays substrates using seed-mediated and liquid-liquid interface self-assembly method for measuring SERS spectra of serum, and then the collected spectra were processed by principal component analysis (PCA) - multi-local means based nearest neighbor (MLMNN) model to achieve differentiation. Results: By employing this pattern analysis, AuLS nanoarray substrates can achieve fast, sensitive, and label-free serum spectral detection. The classification accuracy can reach 97.5%, the sensitivity is higher than 96.7%, and the specificity is higher than 95.0%. Moreover, by analyzing the PCs loading plots, the most critical spectral features distinguishing different degrees of gastric lesions were successfully captured. Conclusion: This discovery lays the foundation for combining SERS with machine learning for real-time diagnosis and recognition of gastric lesions.

Au/Ag@ZIF-8 nanocomposite as solid phase extraction adsorbent and SERS substrate for tacrolimus label-free therapeutic drug monitoring in human serum.

Surface Enhanced Raman Scattering (SERS) has been extensively utilized in therapeutic drug monitoring (TDM) due to its rapid detection speed, high sensitivity and straightforward sample pretreatment. In this study, Au/AgNPs were obtained through the reduction of AgNO3 on the surface of AuNPs. Subsequently, Au/AgNPs were embedded into the tetrahedral lattice of ZIF-8 MOFs, resulting in the formation of Au/Ag@ZIF-8 nanocomposites. The Au/Ag@ZIF-8 nanocomposites exhibit a robust electromagnetic enhancement of Au/Ag bimetallic nanoparticles and a considerable adsorption capacity of ZIF-8 MOFs. This enables the pre-enrichment of target molecules in the vicinity of the electromagnetic field of the Au/AgNPs, thereby enhancing the sensitivity of SERS detection. The SERS substrate also exhibits high stability and reproducibility, as well as molecular sieving effects, due to the fact that Au/AgNPs are embedded into the tetrahedral lattice of ZIF-8. A TDM method for tacrolimus (FK506) in human serum was developed by using Au/Ag@ZIF-8 nanocomposites as solid phase extraction (SPE) adsorbent and SERS substrates. The results showed that under the optimized conditions, tacrolimus exhibited satisfactory linearity within the concentration range of 10-5-10-11 mol L-1, with a correlation coefficient (R2) of 0.9944, and the limit of detection (LOD) was as low as 6.4 pg mL-1. The recoveries were observed to range between 92 % and 105 %, with an RSD of below 8 %. The method is highly sensitive, exhibiting a sensitivity that is 3-6 orders of magnitude higher than that of existing analytical techniques. It has the potential to be applied in a clinical setting to biological samples.

Integrating, Validating, and Expanding Information Space in Single-Molecule Surface-Enhanced Raman Spectroscopy for Biomolecules.

Single-molecule surface-enhanced Raman spectroscopy (SM-SERS) is an ultrahigh-resolution spectroscopic method for directly obtaining the complex vibrational mode information on individual molecules. SM-SERS offers a wide range of submolecular information on the hidden heterogeneity in its functional groups and varying structures, dynamics of conformational changes, binding and reaction kinetics, and interactions with the neighboring molecule and environment. Despite the richness in information on individual molecules and potential of SM-SERS in various detection targets, including large and complex biomolecules, several issues and practical considerations remain to be addressed, such as the requirement of long integration time, challenges in forming reliable and controllable interfaces between nanostructures and biomolecules, difficulty in determining hotspot size and shape, and most importantly, insufficient signal reproducibility and stability. Moreover, utilizing and interpreting SERS spectra is challenging, mainly because of the complexity and dynamic nature of molecular fingerprint Raman spectra, and this leads to fragmentary analysis and incomplete understanding of the spectra. In this Perspective, we discuss the current challenges and future opportunities of SM-SERS in views of system approaches by integrating molecules of interest, Raman dyes, plasmonic nanostructures, and artificial intelligence, particularly for detecting and analyzing biomolecules to realize the validation and expansion of information space in SM-SERS.

Monitoring Hot Holes in Plasmonic Catalysis on Silver Nanoparticles by Using an Ion Label.

Energetic carriers generated by localized surface plasmon resonance (LSPR) provide an efficient way to drive chemical reactions. However, their dynamics and impact on surface reactions remain unknown due to the challenge in observing hot holes. This makes it difficult to correlate the reduction and oxidation half-reactions involving hot electrons and holes, respectively. Here we detect hot holes in their chemical form, Ag(I), on a Ag surface using surface-enhanced Raman scattering (SERS) of SO32- as a hole-specific label. It allows us to determine the dynamic correlations of hot electrons and holes. We find that the equilibrium of holes is the key factor of the surface chemistry, and the wavelength-dependent plasmonic chemical anode refilling (PCAR) effect plays an important role, in addition to the LSPR, in promoting the electron transfer. This method paves the way for visualizing hot holes with nanoscale spatial resolution toward the rational design of a plasmonic catalytic platform.

Molecular-Sieving Label-Free Surface-Enhanced Raman Spectroscopy for Sensitive Detection of Trace Small-Molecule Biomarkers in Clinical Samples.

Small-molecule biomarkers are ubiquitous in biological fluids with pathological implications, but major challenges persist in their quantitative analysis directly in complex clinical samples. Herein, a molecular-sieving label-free surface-enhanced Raman spectroscopy (SERS) biosensor is reported for selective quantitative analysis of trace small-molecule trimetazidine (TMZ) in clinical samples. Our biosensor is fabricated by decorating a superhydrophobic monolayer of microporous metal-organic frameworks (MOF) shell-coated Au nanostar nanoparticles on a silicon substrate. The design strategy principally combines the hydrophobic surface-enabled physical confinement and preconcentration, MOF-assisted molecular enrichment and sieving of small molecules, and sensitive SERS detection. Our biosensor utilizes such a "molecular confinement-and-sieving" strategy to achieve a five orders-of-magnitude dynamic detection range and a limit of detection of ≈0.5 nM for TMZ detection in either urine or whole blood. We further demonstrate the applicability of our biosensing platform for longitudinal label-free SERS detection of the TMZ level directly in clinical samples in a mouse model.

Rapid determination of phenolic composition in chamomile (Matricaria recutita L.) using surface-enhanced Raman spectroscopy.

Flavonoids and hydroxycinnamic acids are the main responsible of the antioxidant activity of chamomile (Matricaria recutita L.). Traditional methods for the analysis of the phenolic content in vegetables often suffer from limitations such as being expensive, time-consuming, and complex. In this study, we propose, for the first time, the use of surface-enhanced Raman spectroscopy (SERS) for the rapid determination of the main components of the polyphenolic fraction in chamomile. Results demonstrate that SERS can serve as an alternative or complementary technique to main analytical strategies for qualitative and quantitative determination of polyphenol compounds in plant extracts. The method can be proposed for quasi real-time analysis of herbal teas and infusions, facilitating rapid screening of their main antioxidant components.

Rapid detection of maleic hydrazide based on the hydrogel SERS platform.

Maleic hydrazide (MH) is a commonly used plant growth regulator and herbicide. However, due to its potential mutagenicity, carcinogenicity, genotoxicity, and cytotoxicity, sensitive and rapid detection of MH residues in foods is crucial. Herein, a sensitive and reliable surface-enhanced Raman scattering (SERS) sensor for MH based on a self-constructed hydrogel SERS platform is proposed for the first time. The used hydrogel SERS chips contain aggregated Ag nanoparticles (a-AgNPs). Under the irradiation of 785 nm laser, the a-AgNPs provide a large quantity of plasmonic hots to produce strong electromagnetic enhancement. Thus, strong SERS signal of MH can be gained on the hydrogel SERS platform. In addition, the unique network structure of hydrogel greatly improves the anti-interference ability to the complex sample matrix. As a result, the developed SERS sensor for MH shows the advantages of high sensitivity (a low detection limit of 50 ppb), fast response (10 min), and high selectivity. The reliability of the sensor is supported by the satisfactory recoveries of 92.80 - 105.6 % in actual samples (tea and potato). The constructed SERS sensor provides a promising approach for rapid on-site testing of MH residues.

Growth of Single Crystals of (K1-xNax)NbO3 by the Self-Flux Method and Characterization of Their Phase Transitions.

In this study, single crystals of (K1-xNax)NbO3 are grown by the self-flux crystal growth method and their phase transitions are studied using a combination of Raman scattering and impedance spectroscopy. X-ray diffraction shows that single crystals have a perovskite structure with monoclinic symmetry. Single crystal X-ray diffraction shows that single crystals have monoclinic symmetry at room temperature with space group P1211. Electron probe microanalysis shows that single crystals are Na-rich and A-site deficient. Temperature-controlled Raman scattering shows that low temperature monoclinic-monoclinic, monoclinic-tetragonal and tetragonal-cubic phase transitions take place at -20 °C, 220 °C and 440 °C. Dielectric property measurements show that single crystals behave as a normal ferroelectric material. Relative or inverse relative permittivity peaks at ~-10 °C, ~230 °C and ~450 °C with hysteresis correspond to the low temperature monoclinic-monoclinic, monoclinic-tetragonal and tetragonal-cubic phase transitions, respectively, consistent with the Raman scattering results. A conduction mechanism with activation energies of about 0.5-0.7 eV was found in the paraelectric phase. Single crystals show polarization-electric field hysteresis loops of a lossy normal ferroelectric. The combination of Raman scattering and impedance spectroscopy is effective in determining the phase transition temperatures of (K1-xNax)NbO3.

Assessment of Optical and Phonon Characteristics in MOCVD-Grown (AlxGa1-x)0.5In0.5P/n+-GaAs Epifilms.

Quaternary (AlxGa1-x)yIn1-yP alloys grown on GaAs substrates have recently gained considerable interest in photonics for improving visible light-emitting diodes, laser diodes, and photodetectors. With two degrees of freedom (x, y) and keeping growth on a lattice-matched GaAs substrate, the (AlxGa1-x)0.5In0.5P alloys are used for tuning structural, phonon, and optical characteristics in different energy regions from far-infrared (FIR) → near-infrared (NIR) → ultraviolet (UV). Despite the successful growth of (AlxGa1-x)0.5In0.5P/n+-GaAs epilayers, limited optical, phonon, and structural characteristics exist. Here, we report our results of carefully examined optical and vibrational properties on highly disordered alloys using temperature-dependent photoluminescence (TD-PL), Raman scattering spectroscopy (RSS), and Fourier-transform infrared reflectivity (FTIR). Macroscopic models were meticulously employed to analyze the TD-PL, RSS, and FTIR data of the (Al0.24Ga0.76)0.5In0.5P/n+-GaAs epilayers to comprehend the energy-dependent characteristics. The Raman scattering and FTIR results of phonons helped analyze the reflectivity spectra in the FIR region. Optical constants were carefully integrated in the transfer matrix method for evaluating the reflectivity R(E) and transmission T(E) spectra in the NIR → UV regions, validating the TD-PL measurements of bandgap energies (EgPL).

NiO/AgNPs nanowell enhanced SERS sensor for efficient detection of micro/nanoplastics in beverages.

The ubiquity of plastic products has led to an increased exposure to micro and nano plastics across diverse environments, presenting a novel class of pollutants with substantial health implications. Emerging research indicates their capacity to infiltrate human organs, posing risks of tissue damage and carcinogenesis. Given the prevalent consumption of beverages as a primary vector for these plastics' entry into the human system, there is an imperative need for the advancement of precise detection methodologies in liquids. In this study, we introduce a substrate comprising a Nickel Oxide (NiO) nanosheet array decorated with Silver Nanoparticles (AgNPs) for the Surface-Enhanced Raman Spectroscopy (SERS) analysis of micro//nano plastics. This configuration, leveraging a unique nanowell architecture alongside silver plasmonic enhancement, demonstrates unparalleled sensitivity and repeatability in signal, facilitating the accurate quantification of these contaminants. Through the application of a portable Raman apparatus, this study successfully identifies prevalent micro/nano plastics including polystyrene (PS), polyethylene (PE), and polypropylene (PP), achieving detection sensitivities of 5 µg/mL, 25 µg/mL, and 25 µg/mL, respectively. Moreover, the substrate's efficacy extends to the detection of PS within commonly consumed beverages such as water, milk, and liquor with sensitivities of 25 µg/mL, 50 µg/mL, and 50 µg/mL, respectively. These findings highlight the substrate's potential as an expedient and effective sensor for the real-time monitoring of micro/nano plastic pollutants.