MICROCHEMICAL JOURNAL
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2025
·
IF 5.1
Zengshan Yu,Xuemei Lin,Zelong Li,Shan Guo,Jiahao Cui,Jianjun Gu,Mingli Wang,Guochao Shi
Carcinoembryonic antigen (CEA), a critical colorectal cancer biomarker, playing a pivotal role in the early diagnosis, therapeutic intervention and longitudinal monitoring of malignancies. Conventional detection methods such as ELISA exhibit inherent limitations including inadequate analytical sensitivity and prolonged assay duration. This study proposes the development of a SERS-based immunosensor integrated with artificial intelligence (AI) frameworks, aiming to achieve precise and quantitative detection of CEA. The antibody-conjugated gold nanoprobes (Au NPs/4-MBA/Ab 1 ) were immobilized onto the surface of another antibody-functionalized Ag/Cu/PSS substrate (Ab 2 /Ag/Cu/PSS) via specific biorecognition. This sandwich-structured immunosensor, engineered with blockage of non-specific binding sites, demonstrated enhanced capacity to capture CEA antigens through dual antibody recognition layers. The immunosensor enabled efficient amplification of SERS signals and exhibited excellent linearity within the CEA concentration range of 0.1–1000 ng/mL. Importantly, Support Vector Machines (SVM), Convolutional Neural Networks (CNN) and Transformer frameworks, were employed for hierarchical processing of CEA Raman data. The Transformer model demonstrated superior performance with a classification accuracy of 99.06 % and a low loss value of 0.1056. These results underscore the model's exceptional capability to discriminate CEA concentrations with high precision and robustness. The integration of AI-driven signal processing boosts analytical sensitivity of SERS-based immunosensors. This synergy between nanophotonic sensing and deep learning algorithms represents a transformative leap in early cancer detection via non-invasive biofluid analysis.
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JOURNAL OF FOOD COMPOSITION AND ANALYSIS
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2025
·
IF 4.6
Qian Liu,Xiaoying Yang,Longhui Luo,Wei Tian,Chao Kang,Tao Sun,Yuegang Chen,Juan Tao,Dongmei Chen
Benzimidazole fungicides are widely used in agriculture, and residues in food will threaten public health and safety. In this study, MXene@PEI@AgNPs composites were successfully constructed by electrostatic self-assembly method using polyethyleneimine (PEI) as a linker and used as a surface-enhanced Raman scattering (SERS) active substrate. The material combines the electromagnetic enhancement of silver nanoparticles and the chemical enhancement mechanism of MXene, showing excellent SERS performance. The experimental results show that the SERS substrate has excellent enhancement performance and successfully obtains the characteristic spectra of six target fungicides. After that, it was combined with chemometrics methods, through principal component analysis (PCA), it was found that the SERS spectra of different fungicides showed obvious clustering distribution. The constructed support vector machine (SVM) classification model shows excellent prediction performance, with an accuracy rate of 100 %. In terms of quantitative analysis, the method showed good sensitivity, and the detection recoveries of benzimidazole fungicides in actual samples such as kiwifruit, tomato and citrus were 81.62 % −113.87 %. Finally, in order to verify the reliability of the method, the high performance liquid chromatography (HPLC) method was used for comparative verification. The results showed that the two methods had good consistency.
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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
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2025
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IF 4.6
Wei Zhang,Kuang Luo,Wenjie Chen,Min Chen,Ning Cai,Jumei Li
In surface-enhanced Raman scattering (SERS) measurements, the creation of “hot spots” and the effective concentration of analytes in these areas are crucial for enhancing detection sensitivity. In this work, a novel composite with highly SERS activity, Ag nanospheres decorated Ag nanostar/ZIF-8 composite (Ag NS/ZIF-8/Ag) was achieved via first coating the Ag nanostars with the metal-organic framework ZIF-8, known for its strong molecular adsorption capabilities, followed by the electrostatic self-assembly of Ag nanospheres. The composites produce numerous hotspots due to the abundant plasmonic nanogaps, including the interstitial space between the Ag nanostar and Ag nanospheres, as well as internanogaps between neighboring Ag nanospheres, resulting in outstanding SERS performance. It was successfully applied for the quantitative and simultaneous detection of diquat and thiram in fruit juice, achieving detection limits of 5.0 × 10 −8 mol/L and 1 × 10 −8 mol/L, respectively, with recovery rates ranging from 86.6 % to 118.4 %. Notably, under UV light exposure, the composite was able to degrade pesticides efficiently within 80 min. Additionally, its reusability was demonstrated by sustaining strong SERS activity over five continuous detection cycles. These results emphasize the capability of Ag NS/ZIF-8/Ag composites for sensitive pesticide detection via SERS.
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JOURNAL OF RAMAN SPECTROSCOPY
·
2025
·
IF 1.9
Yiruo Zhang,Changguo Xue,Mengyu Xu,Ziyu Zhou,Congyu Zuo,Sheng Zhang
A stainless steel mesh loaded with silver nanoparticles (SSM/Ag) was developed as a low-cost and high-performance flexible surface-enhanced Raman spectroscopy (SERS) substrate for residual detection of methylene blue (MB) on curved samples. The sensor's performance was systematically investigated using rhodamine 6G (R6G) as a target molecule. The SSM/Ag substrate showed a limit of detection (LOD) of 10 −8 M and an enhancement factor (EF) of 1.4 × 10 6 . The experiment also utilized the SSM/Ag substrate to detect MB residues by wiping Alternanthera philoxeroides leaves, immersing river water samples, and performing in situ detection of the delivery label on the cup body. The results showed that the limits of detection (LODs) for these three cases were 10 −6 , 10 −7 , and 10 −7 M, respectively, exhibiting a reproducibility relative standard deviation (RSD) below 12%. This provides strong evidence for the validity and feasibility of the SSM/Ag substrate for in situ detection of MB residues on curved samples.
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SENSORS AND ACTUATORS B-CHEMICAL
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2025
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IF 7.7
Yi Yuan,Junlin Chen,Limin Cao,Jianxin Sui,Xiudan Wang,Hong Lin,Kaiqiang Wang
Surface-enhanced Raman scattering (SERS) substrates hold great potential for rapid food monitoring, but the inability to reconcile high enhancement, uniformity, and stability presents a critical trilemma for substrate design and practical applications. Here, inspired by the hierarchical structure of lychee, we developed an innovative "integrated balanced enhancement-protection" strategy, fabricating a lychee-like Au@Ag/Au nanoarray chip via a simple, uniform oil/water/oil (O/W/O) self-assembly technique. This design mimics the architecture of lychee: the outer Au layer, modeled after lychee’s peel, provides chemical protection; the inner Au@Ag layer, mirroring lychee’s seed and flesh, delivers strong plasmonic enhancement. The unique bilayer nanoarchitecture, featuring dense and vertically coupled plasmonic hotspots, ensures highly efficient electromagnetic (EM) field by Au-Ag synergistic effects. It demonstrates an analytical enhancement factor (AEF) of 2.30 × 10 6 , uniformity with a relative standard deviation (RSD) of 6.55 %, and stability with 93.26 % signal retention over 60 days. When coupled with a universal pretreatment protocol to minimize matrix interference, the platform enables sensitive and reliable quantitative detection of three representative food additives, including potassium sorbate (PS), sodium benzoate (SB), and sodium saccharin (SS) in complex fruit matrices. The limit of detection (LOD) for all analytes was below 75 mg/kg, substantially surpassing the national regulatory standards of China. Importantly, the chip demonstrated high recoveries (86.62–102.49 %) and low RSD (< 9 %) across multiple fruit types. Beyond food safety, this scalable, low-cost approach not only overcomes SERS substrate bottlenecks but also provides a viable field-deployable tool with broader implications for SERS-based analysis.
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MICROCHEMICAL JOURNAL
·
2025
·
IF 5.1
Weifan Pan,Peng Zhang,Qi Wang,Liangguang Du,Xue Yang,Xiaowei Guo,Jiamin Yu
Surface-enhanced Raman spectroscopy (SERS) is a promising technique for the rapid detection of trace pesticide residues in agricultural produce. Currently, research is predominantly centered on utilizing SERS to discern residues characterized by non-overlapping spectral peaks. Yet, the technology encounters challenges in accurately identifying substances when their Raman spectral peaks overlap. In this paper, a silver nanoparticles (Ag Nps) modified SiO 2 nanoparticles (SiO 2 Nps) arrays composite SERS substrate (SiO 2 @Ag Nps-SERS substrate) was prepared for detecting lambda-cyhalothrin (LCT) and iprodione (IPR) residues in tobacco leaves, with detection limits of 0.1 ppm and 1 ppm respectively. And then, supervised machine learning models were used to identify and classify LCT and IPR residues with overlapped Raman characteristic peaks at 1000 cm −1 . Support Vector Machine (SVM), Partial Least Squares Discriminant Analysis (PLS-DA) and Decision Tree (DT) models could all accurately classify the spectral data of LCT and IPR residues, and the classification accuracy of SVM model was the highest, reaching 99.74 %. This capability is a testament to the innovative strength of our approach, highlighting its potential for universal applicability in spectral data analysis.
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ANALYST
·
2019
·Vol. 145
·期 2
·445-452
·
IF 4.019
Yanfang Cui,Haiwang Wang,Su Liu,Yu Wang,Jiadong Huang
The self-assembly of plasmonic nanoparticles provides a powerful approach to generate surface-enhanced Raman scattering (SERS), which promotes the actual applications in chemical and biomolecular analyses. Herein, we developed a facile SERS sensing strategy for an ATP assay with a 3-D DNA nanomachine that walks by the Exo III cleavage, leading to the formation of AuNP aggregates, which resulted in the enhancement of the electromagnetic field. Depending on the target-activated Exo III cleavage, the 3-D nanomachine can walk along the 3-D track on the surface of AuNPs and generate self-assembled hot-spots to enhance the SERS signal of a Raman dye, allowing a homogenous assay of the ATP concentration with high sensitivity and reproducibility. Under optimized experimental conditions, the biosensor detected ATP with a widened dynamic range from 1 pM to 1 × 105 pM with a limit of detection of up to 0.29 pM. Hence, the novel strategy provides a useful and practical platform for the SERS assay of ATP with high sensitivity and repeatability. Besides, this platform shows great potential for applications in high-throughput assays for drug screening and clinical diagnostics.
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JOURNAL OF FOOD COMPOSITION AND ANALYSIS
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2025
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IF 4.6
Dongjian Li,Mingxin Han,Liangzhuang Wang,Chengyun Si,Yingxiang Du,Xuefang Luo
Pesticide residues pose serious threats to food safety and human health, highlighting the need for rapid and sensitive detection methods. Traditional techniques are often time-consuming and complex, whereas Surface-Enhanced Raman Spectroscopy (SERS) offers a fast and highly sensitive alternative. In this study, silver nanoparticles (AgNPs) were synthesized via a one-pot hydrothermal method using trisodium citrate (TSC) as a reducing agent and polyvinylpyrrolidone (PVP) as a capping agent. By optimizing PVP and TSC concentrations, a novel AgNPs@capillary SERS substrate was fabricated through in situ assembly of AgNPs onto the inner walls of glass capillaries. The substrate enabled rapid, on-site detection of pesticide residues, specifically the neonicotinoid acetamiprid (ACE) and benzimidazole fungicide carbendazim (CBZ). SERS measurements showed strong linear correlations for ACE (R² = 0.9713, 0.01–0.5 μg/mL) and CBZ (R² = 0.9566, 0.005–0.5 μg/mL). Importantly, the detection limits reached 2.28 × 10⁻³ μg/mL for ACE and 6.25 × 10⁻³ μg/mL for CBZ, demonstrating excellent sensitivity. This study confirms the effectiveness of the one-pot synthesized AgNPs@capillary SERS platform as a practical tool for trace-level pesticide monitoring in environmental and food safety contexts.
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MICROCHEMICAL JOURNAL
·
2025
·
IF 5.1
Yue Wang,Quanying Qu,Xiao Xiao,Tianyu Wang,Han Yan,Wei Wu,Qinzhi Wang
In this work, a high-performance lychee-like plasmonic nanocomplex with programmable hierarchical structure (Ag@ZIF-8@Au) was successfully fabricated as surface enhanced Raman scattering (SERS) platform via layer-by-layer assembly for sensitive detection of diazepam (DZP). ZIF-8 has good pre-enrichment for DZP as well as works as a skeleton for preventing aggregation of plasmonic nanoparticles, dramatically boosting sensitivity, stability and reproducibility of the SERS substrate. Furthermore, lychee-like Ag@ZIF-8@Au nanostructures provided numerous SERS “hot spots” for generating the synergistic enhancement effects including lightning rod and resonance coupling effects. By leveraging Ag@ZIF-8@Au substrate, DZP can be exquisitely detected. The detection limit plummets to 0.126 ng mL −1 , while a broad linear detection span of 10 −9 –10 −2 g mL −1 is achieved. Additionally, Ag@ZIF-8@Au can be utilized to identify DZP in aquatic products with a satisfactory recovery rate of 85.3 % to 111.9 %, which indicates its good practical applicability and great potential for monitoring safety of aquatic products.
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ANALYTICAL CHEMISTRY
·
2025
·
IF 6.7
Jinai Chen,Yujiao Wei,Liming Wang,Leyi Chen,Shengnan He,Honglin Liu
We present a digital surface-enhanced Raman spectroscopy (SERS) platform enabling enzyme- and amplification-free single-molecule DNA detection through Poisson distribution-driven quantification and geometrically optimized plasmonic nanostructures. Utilizing high-throughput UV lithography, we fabricated large-area nanopillar arrays (1.5 × 1.5 cm) with tunable heights (500–1300 nm) and periodicities (4–10 μm), addressing key limitations in conventional SERS methods via three innovations: (1) dynamic hotspot generation: Target DNA induces plasmonic dimerization between functionalized gold nanoprobes and Au-capped nanopillars, creating spatially resolved SERS enhancement (1326 cm–1 DTNB signal), (2) digital counting algorithms: Compensate Raman intensity variations by quantifying activated pillars as discrete molecular events, and (3) geometric confinement: Spatial confinement effects enabling statistically robust single-molecule occupancy. This platform achieved 10 fM sensitivity for Diaporthe spp. DNA detection, outperforming PCR-electrophoresis (1 pM) by 2 orders of magnitude. Applied to presymptomatic kiwifruit diagnosis, the system identified pathogen DNA in asymptomatic samples prior to visual symptom development, validated by characteristic DTNB peaks (1326 cm–1) absent in negative controls. The modular design permits multiplexed detection through probe diversification, while the absence of enzymatic steps enables field-deployable operation. By integrating single-molecule statistics with plasmonic signal amplification, this work establishes a robust framework for precision molecular diagnostics, demonstrating transformative potential for agricultural pathogen surveillance and low-abundance biomarker analysis. The technology’s batch-producible nanopillar architecture and digital quantification strategy overcome longstanding reproducibility challenges in SERS-based detection, positioning it as a versatile tool for next-generation biosensing applications.
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ANALYTICA CHIMICA ACTA
·
2025
·
IF 6
Huixia Di,Zhouhao Lei,Qianyu Li,Peize Xu,Yadi Wang
Background Sialic acid (SA) is a significant monosaccharide presented as the terminal moieties of glycoproteins or glycolipids on the cell membrane and closely correlates with various biological and pathological activities, especially in tumor growth and metastasis. It is well known that the overexpression of SA levels could facilitate tumor immune escape, cell proliferation, and angiogenesis. Thus, SA profiling is critical for the early identification and long-term monitoring of tumors. However, it remains limited by the sensitivity and accuracy of the currently available techniques. Results Herein, we proposed a three-dimensional (3D) surface-enhanced Raman scattering (SERS) imaging with a background-free pattern to determine the SA expression at the single-cell level based on a signal amplification strategy. In this study, the target cells were first captured by the phenylboronic acid (PBA) ligands-coated plasmonic gold (pAu) film and further conjugated with benzonitrile-encoded gold SERS nanotags (Au-MBN@Au@PBA) due to the borate bonds, resulting in an enhanced plasmonic structure to generate a wide variety of “hot spots” to improve the SERS signals at 2230 cm −1 channel in the cellular Raman-silent region (1800–2800 cm −1 ). In this study, the 3D SERS imaging enables a deep insight into SA levels, determination of the normal and cancer cell lines, and real-time monitoring of nanoparticle tracking in cancer cells. Significance In this work, the newly prepared PBA ligands possess various capabilities, including modification of SERS nanotags and pAu films, generating good affinity toward SA moieties, and increasing the hydrophilicity of pAu substrate for cell capture. With the assistance of PBA ligands, the pAu film-cell-SERS nanotags sandwich structure was yielded, and the enhanced plasmon coupling was produced, which allows noninvasive, high-precision, and sensitive SA profiling for early tumor diagnosis, glycosylation exploration, and tracking phagocytosis.
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Analytical Methods
·
2025
·
IF 2.6
Junaid Younus,Qi Wang,Weifan Pan,Jimin Shao,Xiaowei Guo,Xue Yang
Surface-enhanced Raman scattering (SERS) is a rapid, sensitive, and non-destructive technique for pesticide detection. However, most reported studies focus on single-analyte detection, and the simultaneous detection of multiple pesticide residues in complex matrices such as tobacco leaves remains challenging. In this study, we developed a portable SERS platform for the simultaneous detection of pendimethalin, propamocarb, and carbendazim using a polystyrene@silver (PS@Ag) core–shell substrate. The method enabled rapid detection (<15 min) with limits of detection (LODs) of 0.1 mg kg−1 for carbendazim, 5 mg kg−1 for pendimethalin, and 10 mg kg−1 for propamocarb in individual analyte detection, which meets the European Union's maximum residue limits (MRLs). In ternary mixtures, the LODs were 1 mg kg−1 for carbendazim, 5 mg kg−1 for pendimethalin and 10 mg kg−1 for propamocarb with strong linearity (R2 = 0.97–0.98). The substrate exhibited uniform enhancement with relative standard deviations (RSDs) of 3.53% for pendimethalin, 7.76% for propamocarb, and 4.70% for carbendazim, and high sensitivity, achieving enhancement factors for all target pesticides (3.4 × 101 for pendimethalin, 3.7 × 101 for propamocarb, and 6.0 × 103 for carbendazim). To the best of our knowledge, this is the first report to demonstrate that a PS@Ag SERS substrate combined with a portable Raman spectrometer serves as a highly reliable and promising tool for on-site monitoring of multiple pesticide residues in food safety and environmental applications.
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