FOOD CONTROL
·
2025
·
IF 6.3
Shanshan Xue,Limei Yin,Lixin Ma,Heera Jayan,Usman Majeed,Hesham R. El-Seedi,Xiaobo Zou,Zhiming Guo
As a major contaminant in apples, patulin (PAT) poses a significant threat to human health and the economy. Establishing highly sensitive and accurate quantitative detection methods for PAT is crucial for ensuring food safety and protecting consumer health. Herein, a competitive ratiometric surface-enhanced Raman spectroscopy (SERS) aptasensor was fabricated. 4-Mercaptobenzoic acid (4-MBA) was embedded as an internal standard (IS) within a gold-silver core-shell structure, later assembled onto Fe 3 O 4 nanoparticles and coupled with complementary aptamer strands to form magnetic probes. Additionally, an aptamer targeting PAT and the Raman reporter molecule 5,5′-Dithiobis-(2-nitrobenzoic acid) (DTNB) were anchored onto gold bipyramids (AuBPs), creating reporter probes. The recognition and binding of the target PAT to the aptamer led to the detachment of the reporter probe after magnetic separation, reducing the DTNB signal. Thus, the ratio of SERS peak intensities (I DTNB /I 4-MBA ) quantified PAT demonstrated a linear range of 0.1–200 ng/mL and a limit of detection (LOD) of 0.070 ng/mL. The implementation of magnetic separation significantly streamlined the sensor fabrication process, whereas the ratiometric strategy substantially enhanced the reproducibility and stability of PAT detection. Furthermore, this method was successfully applied to the determination of PAT in apples and their products, showing potential for practical applications in food safety.
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ANALYST
·
2026
·
IF 3.3
Rui Zhao,Qishuo Wang,Yunqing Wang,Rongchao Mei,Xiaoyan Wang,Lingxin Chen
Rapid detection of bacteria in complex matrices remains challenging due to substantial interference in signal readout. This study developed a novel near-infrared (NIR) surface-enhanced Raman scattering (SERS) sensor featuring exceptional anti-interference capability, achieved by encapsulating SERS tags with a carboxylated polystyrene shell and integrating them with a specific aptamer. The functional PS shell provides reliable physical protection and enables stable covalent bioconjugation, effectively overcoming the limitations of traditional thiol chemistry. Leveraging NIR excitation for minimal background interference, the sensor operates through a target-induced strand displacement mechanism that releases SERS tags upon bacterial binding. After magnetic separation, quantitative analysis is accomplished by directly measuring the SERS signal in the supernatant. Using Staphylococcus aureus as the model bacterium, the method demonstrated outstanding performance in diverse complex matrices including seawater, serum, milk, and traditional Chinese medicine preparations, with a detection limit of 10 CFU/mL and recoveries ranging from 89.96% to 110.6%. This work presents a robust and matrix-adaptive sensing strategy for rapid bacterial detection in complex environments.
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SENSORS AND ACTUATORS B-CHEMICAL
·
2023
·
IF 8.4
Ying Xu,Yang Zhang,Zhiyu Li,Yuanrong Liao,Rongjian Sa,Hualiang Yu,Yizhi Wang,Jing Peng,Yan Lin,Jun Wang
Electrospinning is a prominent technique for fabricating polymer-stabilized composite nanofibers for surface-enhanced Raman scattering (SERS). However, further exploration of the surface chemistry of these electrospun composite substrates is crucial to manipulate the charge transfer (CT) effect and achieve synergistic effects between CT and localized surface plasmon resonance (LSPR) for enhanced bio-labeling and pesticide detection. Here, we present the development of a flexible and self-supporting SERS substrate using electrospinning, consisting of polymer-coated silver nanowires (AgNWs). By employing different polymer shells and probe molecules, we strategically adjusted the energy levels of the frontier orbitals , enabling effective control over the CT effect. The resulting nanofibers exhibited optimized selectivity and sensitivity through multiple CT routes, enabling the detection of thiram in apple skin using a convenient wiping sampling method with a low limit of detection (LOD) of 5 ng/cm². We also investigated other pesticides without viable CT routes to demonstrate the versatility of the composite substrates, although they exhibited relatively lower selectivity and sensitivity due to the absence of synergistic effects. This study highlights the potential of CT manipulation in harnessing synergistic effects in electrospun 2D composite nanofibers , thereby advancing the practical applications of SERS technology.
研究领域:
材料科学
·
纳米技术
·
分析化学
·
环境监测
·
生物传感
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FOOD CHEMISTRY
·
2026
·
IF 9.8
Qian Ye,Xianjin Zhang,Yuanyuan Yao,Yueliang Wang,Lifen Chen,Bingyong Lin,Hong Huang,Jianguo Xu,Xin Peng,Longhua Guo
Traditional sensory evaluation methods for tea—relying on empirical experience, visual colorimetry, and subjective taste perception—suffer from irreproducible inter-rater variability and inability to quantify bioactive markers, thus failing to establish scientifically verifiable quality standards. To address this, we developed an intelligent platform integrating surface-enhanced Raman scattering with machine learning for rapid and quantitative white tea analysis, enabling detection within just 20 min. Utilizing silver nano-coral substrates for signal enhancement and a 785 nm portable Raman spectrometer for full-spectrum data acquisition, we constructed a hybrid machine learning architecture featuring Random Forest for vintage classification (96% accuracy) and Gradient Boosting Regressor for epigallocatechin gallate (EGCG) quantification (R 2 = 0.98, the values of Root Mean Square Error, Mean Absolute Error, and Mean Square Error all approach zero). This approach established a definitive EGCG-content grading hierarchy: Yinzhen > Mudan > Gongmei > Shoumei, which is highly consistent with traditional sensory evaluation methods, while provides additional quantitative ability.
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CHEMICAL ENGINEERING JOURNAL
·
2026
·
IF 13.2
Chan Huang,Xiuying Li,Xuan Zeng,Lingzhi Chen,Huabin Zhang,Xinjie Guo,Yiqun Chang,Wenshi Huang,Yichu Nie,Tianen Zhou,Jiaqi Yu,Jun Xu,Huaihong Cai,Yanguang Cong,Jiang Pi,Pinghua Sun,Haibo Zhou,Jun Jiang,Xueqin Huang,Yunxiang Ji
Rapid and sensitive detection of pathogenic lipopolysaccharide (LPS) is of the utmost importance in pharmaceutical products and food safety. Herein, we presented catalyzed hairpin assembly (CHA)-mediated magnetic/plasmonic satellite nanoassemblies, made of ternary metallic Au@AgPt-coated metal-organic framework (MOF) nanohybrids (Au@AgPt@MOF) with dual-enhancement SERS output and Au magnetic nanoparticles (AuMNPs) with magnetic enrichment and SERS amplification, for ultrasensitive sensing LPS in pharmaceutical injections. Target LPS initiated aptamer (Apt)-based chain replacement reaction, thereby activating downstream CHA for inducing the aggregation of large satellite nanoassemblies and the amplification of catalytic/SERS signals. Under the optimal condition, this method exhibited good linear response in the range of 10 −5 -10 3 ng/mL, with an ultralow limit of detection (LOD) in SERS model (8 fg/mL) and catalytic colorimetric model (56 fg/mL). The selectivity and sensitivity of oligonucleotide-driven signal amplification was validated by in vitro experiments and trials of glucose, troxerutin, lidocaine hydrochloride injection samples. The assay results were closely aligning with those of the standard endotoxin quantitative kit, demonstrating the reliability and availability of this assay. Overall, by incorporating the merits of dual-SERS enhancement of Au@AgPt@MOF substrate, magnetic-meditated satellite strategy, and CHA-cascade amplification response, this platform opened up new opportunities for inspecting LPS in drug injection samples.
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ANALYTICAL CHEMISTRY
·
2026
·
IF 7.3
Chang-Yi Wu,Ze-Gang Wu,Jia-Cheng Chen,Sai-Shang Zhong,Bai-Chuan Zhao,Wen-Tao Yang,Xue-Chun Li,Wan-lin Yin,Jia-Le Huang,Jun Cao,Cheng-Liang Zhu,Ai-Guo Shen
Serum metabolic analysis based on label-free SERS fingerprints represents a highly promising technique for the detection of tumors. However, the insufficient hotspot density of SERS substrates often results in incomplete molecular Raman bands, hindering the accurate discrimination of tumors. Herein, we propose a clean, hydrophobic monolayer gold nanofilm/potassium iodide-encapsulated silver-coupled (Ag@KI/HMGF) SERS substrate. This triple-coupled SERS substrate achieves exceptional signal amplification and enables the acquisition of abundant SERS bands for multicomponent systems. Robust machine learning classifiers were employed to identify and analyze the Raman spectral features of serum metabolites, and this method exhibited high clinical accuracy, sensitivity, and specificity in distinguishing samples from patients with different types of gastrointestinal malignancies and healthy individuals. The serum metabolic analysis based on the coupled SERS substrate constructed in this study provides a highly promising solution to address the clinical challenge of gastrointestinal malignant tumor discrimination and can be further extended to clinical cancer detection based on other biological fluids.
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TALANTA
·
2026
·
IF 6.7
Qian Xie,Jinxin Chi,Zhixin Li,Limei Xu,Yujuan Xiao,Xucong Lin,Guihua Huang
The environmental risks of microplastics are exacerbated by the leaching of endocrine-disrupting additives such as bisphenol A (BPA). Effective monitoring requires analytical methods that are ultrasensitive, specific, and suitable for on-site application, requirements that remain challenging for conventional techniques. Herein, we develop an integrated capillary-based SERS aptasensor for the rapid and specific detection of BPA leached from microplastics. The sensor core is a three-dimensional hierarchical porous silica monolith (3D-PSM) anchored inside a quartz capillary. A DNA-programmed nanogap SERS hotspot matrix is constructed on the 3D-PSM by immobilizing cDNA-modified Au nanoparticles, followed by hybridization with aptamer-conjugated Au@4-MBN@Ag nanotags. This design utilizes the cDNA-aptamer duplex as a programmable molecular spacer to create a uniform sub-10-nm gap, generating an intense initial SERS signal (“signal-on”). Competitive binding of BPA triggers nanotag release and quantifiable signal attenuation (“signal-off”). Benefiting from convective mass transport within the 3D architecture, the platform achieves a limit of detection (LOD) of 1.24 pM for BPA, exhibiting a linear range spanning five orders of magnitude (1.0 pM to 0.1 μM), with a recognition time of 10 min. Practical utility was demonstrated by analyzing BPA thermally liberated (70 °C) from polycarbonate microplastics (PC-MPs, 100 and 1000 mesh) in environmental water matrices. The method exhibited high specificity and satisfactory recoveries (93.7 ± 3.6% to 102.0 ± 7.6%) in spiked river water samples, demonstrating a positive correlation between leached BPA amounts and MP contamination levels. This work provides a reliable tool for the direct assessment of hazardous chemical leaching from microplastics.
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ANALYTICAL CHEMISTRY
·
2026
·
IF 7.3
Zhenli Sun,Yiyan Zhang,Jingjing Du,Qian Liu
The pervasive occurrence of microplastics (MPs) in aquatic environments presents growing challenges for environmental monitoring. Conventional MP detection methods often require extensive pretreatment and struggle to differentiate mixed polymer compositions in complex matrices. Here, we present a pretreatment-free analytical method that integrates an electrostatically functionalized surface-enhanced Raman scattering (SERS) substrate with an interpretable deep learning framework. A hierarchically porous gold sponge modified with poly(diallyldimethylammonium chloride) facilitates efficient electrostatic enrichment and size-selective capture of negatively charged MPs, while embedded gold nanoparticles generate plasmonic hotspots for enhanced Raman signal amplification. A modular binary convolutional neural network framework (CNN) employing a one-vs-rest architecture enables accurate and interpretable classification of five representative MPs, i.e., polytetrafluoroethylene, polypropylene, polystyrene, polyvinyl chloride, and polyethylene terephthalate, achieving a precision of 0.9896 within the evaluated Raman data set. Gradient-weighted class activation mapping (Grad-CAM) analysis highlights key Raman bands characteristic of each polymer type, e.g., the C–C vibrations in the benzene ring of PET, supporting the chemical interpretability of the CNN model. The system was validated in urban tap water and natural surface waters, which represent both low-interference and heavy-metal-impacted complex matrices. This integrated platform provides a sensitive and adaptable approach for pretreatment-free identification of MPs in complex water matrices, demonstrating its potential for practical environmental analysis.
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ChemistrySelect
·
2026
·Vol. 11
·期 35
·e74422
·
IF 2.3
Wei Lai
Conventional two-dimensional SERS substrates are often limited by low hot-spot density and poor reproducibility. In this work, a novel three-dimensional (3D) SERS substrate was developed by in situ growing fractal gold nanostructures on a Ti 3 C 2 T x MXene network incorporated into a hydrogel. The coexistence of Au and MXene, confirmed by EDS analysis, provides a composite platform that combines the electromagnetic enhancement of Au nanostructures with the potential chemical-enhancement contribution of MXene. An ethanol-induced hydrogel shrinkage strategy was further introduced to simultaneously concentrate analytes and compress the 3D framework, thereby increasing the local density of active sites and enhancing the SERS response. The substrate exhibited a linear detection range of 10 −8 -10 −4 M for crystal violet (CV) and was successfully applied to the quantitative analysis of ginsenoside Rg3 in ginseng. A detection limit of approximately 0.23 µg mL −1 and an estimated sample content of approximately 1.31 µg g −1 were obtained. This work demonstrates a contraction-assisted Au/MXene 3D SERS platform for sensitive molecular detection. Graphical Synergistic enhancement of SERS signals from Raman reporter molecules (ginsenoside Rg3 in ginseng) arises from the electromagnetic enhancement of gold nanoflowers and the synergistic contribution of MXene.
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ANALYTICAL CHEMISTRY
·
2025
·
IF 6.7
Ao Wang,Qianqian Ding,Jiahao Mou,Hongbin Qi,Jiazhi Yang,Urol K. Makhmanov,A. V. Rogachev,Xiaohong Jiang
Plastic pollution has emerged as a critical global environmental challenge, posing substantial risks to ecosystems’ stability, biodiversity conservation, and public health protection. However, technique limitations persist in detecting and analyzing plastic particles within complex environmental matrices. This study introduces an ultrasensitive surface-enhanced Raman spectroscopy (SERS)-based method for detecting and precisely quantifying polystyrene (PS) plastic particles of various sizes in real-world aqueous samples. The developed SERS platform integrates urchin-like silver nanoparticles, generating high-density SERS hotspots, with a slippery polydimethylsiloxane (PDMS) brush surface for effective analyte enrichment. The synergistic combination achieves exceptional detection performance for dichloromethane (DCM)-dispersed polystyrene plastic particles across broad size ranges, demonstrating a remarkable detection limit of 2.57 × 10–5 mg/mL. The established quantitative relationship follows log I = 0.4501 log C + 4.1869 (R2 = 0.9899), confirming excellent analytical reliability. This advancement provides a robust analytical framework for environmental monitoring applications, particularly offering a novel approach for detecting microplastics (MPs) and nanoplastics (NPs) in real water samples.
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CRYSTENGCOMM
·
2025
·
IF 2.6
Lei Chen,Rui Xu,Zhi Yang,Fuyu Chang,Lu Yang,Yoonseop Byun,Eunsoo Song,Eungyeong Park,Lihui Liu,Young Mee Jung
The two-dimensional (2D) layered structure of MXene provides a large specific surface area, making it an ideal platform for optimizing geometric configurations in surface-enhanced Raman scattering (SERS) applications. In this study, we developed a novel ternary core-shell nanostructure, Ag@Cu2O-MXene, in which Ag@Cu2O core-shell nanoparticles (NPs) are uniformly anchored onto 2D Ti3C2Tx MXene nanosheets. The Ag NPs exhibit strong localized surface plasmon resonance, while the narrow bandgap and high electron mobility of Cu2O shell promote efficient charge transfer. Importantly, plasmonic coupling between the Ag core and the MXene substrate further enhances plasmon absorption, resulting in a substantial increase in SERS activity and enabling highly sensitive molecular detection. Using this composite, we achieved an ultra-low detection limit of 10–9 M for methylene blue. MXene substrate further facilitates rapid electron transfer from the Ag core to the the Cu2O shell, while its surface defects contribute additional charge carriers to Cu₂O, enhancing the utilization of photogenerated electron. Notably, the SERS enhancement was positively correlated with the thickness of Cu2O shell, highlighting the tunable nature of the Ag@Cu2O-MXene core-shell nanostructure.
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SENSORS AND ACTUATORS B-CHEMICAL
·
2023
·
IF 8.4
Weidan Na,Changjin Ou,Yijun Ming,Yuchong Gao,Lin Tian
Surface enhanced Raman spectroscopy (SERS) detection was not as accurate and reproducible as fluorometry due to some uncertainties such as operator's focus adjustment and difference between capillaries. Herein, the weak Raman signal (1640 cm −1 ) from water bending vibration is adopted as a benchmark to improve the practical applicability of Raman detection. Specifically, amygdalin and citrate sodium were applied as reducing and capping agent to synthesize dual-ligand gold nanoparticles (DL-AuNPs). Additionally, the cyano group of amygdalin can attach to the surface of DL-AuNPs and generate a primary SERS signal (2174 cm −1 ), which can be significantly enhanced by Cu(II) as DL-AuNPs aggregates. More importantly, the strong binding affinity between pyrophosphate ions (PPi) and Cu(II) redisperses DL-AuNPs and decreases the signal intensity, making the DL-AuNPs/Cu(II) SERS sensor promising for the detection of PPi. This proposed method presents a reliable SERS analysis with the stable water background calibration and broaden the application of SERS technique in aqueous solution target monitoring.
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