SENSORS AND ACTUATORS B-CHEMICAL
·
2024
·
IF 8
Linge Nian,Wenhua Li,Minhui Dai,Chunxia Zhang,Lu Li,Guangrui Zhang,Jianxi Xiao
The precise detection of pathological type I collagen is critical for diagnosing and prognosticating various diseases such as fibrosis and tumors. Surface-enhanced Raman scattering (SERS) is emerging as a promising high-resolution imaging technique, yet the intricate process of covalently modifying antibodies often results in SERS probes with diminished selectivity. We herein for the first time report the development of dual SERS peptide probes, Ag@R1@PCTP (S-P) and Ag@R2@ICTP (S-I), which integrate collagen targeting peptides (CTPs), Raman reporters, and silver nanoparticles (Ag NPs) for specific imaging of pathological type I collagen in connective tissues. The S-P/S-I dual SERS peptide probes displayed distinct peaks at 2154 cm −1 and 2227 cm −1 in the Raman silent region with no overlap, showcasing their capability for multiplex imaging free from cross-interference. The SERS peptide probe S-P is specifically tuned to target pathological collagen, excluding intact collagen, while S-I effectively recognizes type I collagen in both its pathological and healthy states. The S-P/S-I probes have exhibited outstanding effectiveness in identifying pathological type I collagen across various connective tissues and have been successfully applied for imaging this collagen in a variety of cancer tissues. The innovative dual SERS peptide probes offer a highly specific and robust tool for imaging pathological type I collagen in tissues, presenting significant potential for the accurate diagnosis and treatment of a range of collagen-related diseases.
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高影响因子
SENSORS AND ACTUATORS B-CHEMICAL
·
2024
·
IF 8
Haoyu Dong,Shuang Lin,Guoqiang Fang,Yiran Liu,Huachuang Li,Li Wang
Metal film over nanosphere (MFON) as a classical SERS-active substrate has attracted numerous attention and applications due to its excellent sensitivity and signal uniformity. However, such MFON substrates prepared by metal deposition require strictly controlled experimental conditions with high cost to obtain high batch reproducibility. In addition, the precise adjustment of the metal particle fineness and crystal facet is hard to conduct, limiting the SERS signal for further improvement. In this work, we propose multifaceted Au nanocrystal over nanosphere (AuNCFON) structures based on a facile and robust interfacial assembly technique. Notably, the preparation method could reduce significant loss of metallic materials without the requirement of large-scale instrumentation, and allows precise control of the metal film thickness and the nanocrystal facet. Specifically, the size and facet of nanocrystals on PS spheres are systematically regulated and the Au dodecahedral films with {110} facet on PS arrays exhibit optimal SERS activity. The SERS intensity is amplified by an enhancement factor of 0.13 × 10 7 with excellent signal homogeneity and batch reproducibility. Finally, the sensitive and accurate distinction of similarly structured molecules including crystal violet and malachite green (fungicides) is demonstrated assisted by principal component analysis-partial least squares (PCA-PLS) algorithm. The AuNCFON SERS substrate combined with deep learning analysis has a broad application prospect in reliable identification of chemical pollutants.
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MICROCHEMICAL JOURNAL
·
2025
·
IF 5.1
Tao Wang,Shuang Zhang,Dongling Wu,Maohua Li,Yalan He,Yunpeng Shen
The polyol reduction method has performed well in Ag nanocube (AgNC) synthesis but is hindered by high-temperature requirements, impacting environmental sustainability and economy. Using polyethylene glycol (PEG)/deionized water as a solvent mitigates these issues, by leveraging PEG’s high solubility, bio-compatibility, low cost, and redox properties. The synthesis conditions were optimized, resulting in relatively uniform AgNC. The synthetic AgNC were loaded on porous, cheap, flexible and biocompatible filter paper (FP) by a simple self-assembly, and the formed flexible substrate (AgNC@FP) was used for surface-enhanced Raman scattering (SERS) detection. The AgNC@FP substrate had a high enhancement factor (EF) of 9.8 × 10 7 , with a detection limit of Rhodamine 6G (R6G) of 5.2 × 10 -12 M. Meanwhile, the substrate showed good reproducibility and stability, with a relative standard deviation (RSD) of 5.9 % and a decrease in Raman signal strength of only 25 % after 30 days. Furthermore, the direct sampling of apples and pears from their surface thereby enables the rapid identification of ultra-low thiram residue concentrations, with a sensitivity of 8.3 × 10 -7 M. The high SERS enhancement factor and sensitivity were attributed to the result of the high hot spot density generated by the FP surface, excellent uniformity and superior sample collection efficiency. It can therefore be concluded that this flexible AgNC@FP substrate, which is manufactured at a low cost and allows for label-free SERS detection, represents a promising SERS platform for analytical and biosensing applications.
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高影响因子
MICROCHEMICAL JOURNAL
·
2024
·
IF 4.9
Zelong Li,Xue Han,Lan Fu,Guochao Shi,Shiqi Xu,Mingli Wang,Wenzhi Yuan,Wenying Zhou,Jiahao Cui
The combination of surface-enhanced Raman scattering (SERS) and machine learning algorithm provides an effective means for the identification of pharmacodynamic substances. This paper reported a biomimetic synthesis route of Ag-30/SiO 2 -4/Cu-20/rice leaf (Ag-30/SiO 2 -4/Cu-20/RL) SERS platform with multiple synergistic electromagnetic enhanced performance. The localized surface plasmon resonance (LSPR) effect was strengthened as the SiO 2 nanolayer generated between Ag and Cu. This SERS platform demonstrated high sensitivity, with a low limit of detection (LOD) of 1 × 10 −10 M for 4-Aminophenylthiophenol (4-ATP) and an enhancement factor (EF) of 3.86 × 10 6 . More importantly, the principal component analysis (PCA) was adopted to analyze the SERS data of three different Traditional Chinese medicine (TCM) pharmacodynamic substances (Orientin, Atractylenolide III and Prim-o-glucosylcimifugin). The K-nearest neighbor (KNN) and Naïve Bayes (NB) achieved classification accuracy of 0.9474 and 0.9649, respectively. The platform provides guidance for the accurate identification of TCM pharmacodynamic substances.
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SENSORS AND ACTUATORS B-CHEMICAL
·
2024
·
IF 8
Yipeng Zhang,Zhangze Yang,Yucheng Zou,Shahzad Farooq,Zeyu Qin,Hui Zhang
Aiming to meet the demand for rapid detection of chlorpyrifos (CPS), a surface-enhanced Raman scattering (SERS) sensor based on a gluten/zein electrospun film (GZEF) was fabricated via electrospraying. The SERS performance was namely improved through metal nanoparticles selection and optimization of loading amounts. Further construction of the AANS@ZIF-8@GZEF sensor was achieved through in-situ growth. Owning to the porous structure of ZIF-8, the trapping ability and enrichment effect of the SERS sensor were enhanced, resulting in a superior SERS enhancement effect of 1.58 times. Moreover, the CPS detection under various concentrations was carried out using the AANS@ZIF-8@GZEF sensor. The concentration-logarithm peak intensity equations were fitted, and the limit of detection (LOD) of CPS was calculated to be 0.981 μg/L. Finally, the detection of CPS residues on the peel of apples was performed using the AANS@ZIF-8@GZEF sensor, and the results showed that the overall recovery rate ranged between 91.18% and 96.83%, with all relative standard deviations being less than 5%. Great potential applications in the rapid and sensitive detection of chlorpyrifos in food are expected for the AANS@ZIF-8@GZEF sensor constructed in this study.
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SENSORS AND ACTUATORS B-CHEMICAL
·
2024
·
IF 8
Morui Wang,Haoxuan Diao,Cheng Dou,Zhenye Wu,Liguang Ruan,Zhixin Wang,Zhong Wang,Weichun Ye,Jiangong Duan,Yuee Li
This work aims to face the challenge of label-free and quantitative detection for pathogenic microorganisms concerning on food safety and medical diagnosis. Ag NPs@PDMS sponge SERS substrates were developed through the "mold transfer-surface embedding" method for pathogenic microbial detection. The pore structure provided large specific surface area and critical contact sites, which endowed the detection limit of only 1 CFU/mL for E.coli . Importantly, six different microorganisms could be identified using this SERS substrate. The classification models combining three types of data dimension reductions and five types of machine learning algorithms were constructed to achieve the automatic classification of microorganisms. Among these algorithms, the PCA-SVC model held the highest accuracy of 92.17%. Different from labeled SERS, label-free SERS technique is conducive to the discovery of unknown microorganisms in water-environment. Therefore, this SERS substrate is expected for microbial system assessment and microbial safety monitoring, combined with handheld Raman spectrometer and artificial intelligence.
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高影响因子
ACS Sensors
·
2024
·
IF 8.2
Chunning Chen,Jiaqi Liu,Jiaxin Lu,Yalei Wang,Jingtong Zhai,Hongkun Zhao,Nan Lu
As one of the common carriers of biological information, along with human urine specimens and blood, exhaled breath condensate (EBC) carries reliable and rich information about the body’s metabolism to track human physiological normal/abnormal states and environmental exposures. What is more, EBC has gained extensive attention because of the convenient and nondestructive sampling. Facemasks, which act as a physical filter barrier between human exhaled breath and inhaled substances from the external environment, are safe, noninvasive, and economic devices for direct sampling of human exhaled breath and inhaled substances. Inspired by the ability of fog collection of Namib desert beetle, a strategy for in situ collecting and detecting EBC with surface-enhanced Raman scattering is illustrated. Based on the intrinsic and unique wettability differences between the squares and the surrounding area of the pattern on facemasks, the hydrophilic squares can capture exhaled droplets and spontaneously enrich the analytes and silver nanocubes (AgNCs), resulting in good repeatability in situ detection. Using R6G as the probe molecule, the minimal detectable concentration can reach as low as 10–16 M, and the relative standard deviation is less than 7%. This proves that this strategy can achieve high detection sensitivity and high detection repeatability. Meanwhile, this strategy is applicable for portable nitrite analysis in EBC and may provide an inspiration for monitoring other biomarkers in EBC.
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高影响因子
MICROCHIMICA ACTA
·
2025
·Vol. 192
·期 2
·1-8
·
IF 5.3
Zhang Luyang,Chen Huan,Ma Shanshan,Fan Wu,Chen Sheng,Yu Ajuan,Yuan Hang,Ouyang Gangfeng,Zhang Yanhao,Zhao Wuduo
A novel microfluidic approach is presented for the one-step synthesis of gold nanoparticle-doped microspherical photonic crystal (AuNP–MPC) for ultrasensitive surface-enhanced Raman spectroscopy (SERS) detection of methylene blue (MB), a common environmental pollutant. The AuNP–MPC microspheres exhibited excellent SERS activity due to the surface plasmon resonance of Au nanoparticles. And the SERS signal was significantly enhanced by strategically manipulating the photonic band gap (PBG) of the AuNP–MPC microspheres to achieve optimal overlap with the excitation laser wavelength. The SERS signal of MB was significantly enhanced by this, reaching an EF as high as 3.03 × 10 6 . The AuNP–MPC microspheres demonstrated rapid adsorption of MB within just 5 min, making them suitable for rapid detection applications. Notably, the limit of quantification was as low as 1 × 10 −8 mol/L, highlighting the exceptional sensitivity of this approach. Furthermore, the AuNP–MPC microspheres exhibited excellent homogeneity, reproducibility, and stability of SERS signals, which are crucial qualities for practical SERS applications. This work presents a promising avenue for developing SERS-active microfluidic platforms for the rapid detection of trace organic pollutants in environmental monitoring. Graphical
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高影响因子
MICROCHIMICA ACTA
·
2024
·Vol. 191
·期 4
·1-9
·
IF 5.3
Zheng Wenhan,Li Min,Zhang Zhengping,Lou Zhixuan,Liu Yanbin,Yao Yuanyuan,Chen Lifen,Lin Bingyong,Wang Yueliang,Guo Longhua
A sandwich plasmonic coupled surface enhanced Raman spectroscopy (SERS) tape is proposed prepared by peeling the chemical printed silver nanocorals (AgNCs) from Cu sheet with adhesive tape, which can sample targets from food surface and sandwich them between substrates and Cu sheet for SERS detection. The solid-to-solid transformation method for fabricating SERS tapes can effectively avoid the weakening of tape stickiness during the preparation process. The sandwich plasmonic coupled structure of AgNC substrate, targets, and Cu sheet display excellent SERS activity (EF = 1.62 × 10 7 ) for sensitive determination of analytes. In addition, due to the high heat conductivity of Cu sheet, the thermal effect of laser irradiation during SERS detection cannot damage the AgNC tapes, which ensures the reproducibility of subsequent quantification. The sandwich plasmonic coupled SERS tape is demonstrated to quantify malachite green (MG) and methyl parathion (MP) with good linear coefficients (> 0.98) by two typical calibration plots under different concentration ranges. The limit of detection (LOD) of the method is 0.17 ng/cm 2 and 0.48 μg/cm 2 (S/N = 3) for MG and MP. This method can realize the quantitative determination of MP and MG on the surface of fruits and fish scale with recoveries of 93–113%. The satisfactory detection results demonstrate the proposed sandwich plasmonic coupled AgNC tape can be successfully applied to SERS-based point-of-care testing (POCT) for pesticide residue determination, which will provide a new path for designing and constructing SERS tapes. Graphical Abstract
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ACS Sensors
·
2025
·
IF 9.1
Xing Wang,Shen Shen,Ning Sun,Yong Zhu,Jie Zhang
To enhance the sensitivity, integration, and practicality of the Raman detection system, a deep learning-based dual-functional subregional microfluidic integrated hydrogel surface-enhanced Raman scattering (SERS) platform is proposed in this paper. First, silver nanoparticles (Ag NPs) with a homogeneous morphology were synthesized using a one-step reduction method. Second, these Ag NPs were embedded in N-isopropylacrylamide/poly(vinyl alcohol) (Ag NPs-NIPAM/PVA) hydrogels. Finally, a dual-functional SERS platform featuring four channels, each equipped with a switch and a detection region, was developed in conjunction with microfluidics. This platform effectively allows the flow of the test material to be directed to a specific detection region by sequential activation of the hydrogel switches with an external heating element. It then utilizes the corresponding heating element in the detection region to adjust the gaps between Ag NPs, enabling the measurement of the Raman enhancement performance in the designated SERS detection area. The dual-functional microfluidic-integrated hydrogel SERS platform enables subregional sampling and simultaneous detection of multiple molecules. The platform demonstrated excellent detection performance for Rhodamine 6G (R6G), achieving a detection limit as low as 10–10 mol/L and an enhancement factor of 107, with relative standard deviations of the main characteristic peaks below 10%. Additionally, the platform is capable of simultaneous subarea detection of four real molecules─thiram, pyrene, anthracene, and dibutyl phthalate─combined with fully connected neural network technology, which offers improved predictability, practicality, and applicability for their classification and identification.
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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
·
2024
·
IF 4.3
Xuehua Wang,Junwei Hou,Chen Chen,Zhenhong Jia,Enguang Zuo,Chenjie Chang,Yuhao Huang,Cheng Chen,Xiaoyi Lv
Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple symptoms, and its rapid screening is the research focus of surface-enhanced Raman scattering (SERS) technology. In this study, gold@silver-porous silicon (Au@Ag-PSi) composite substrates were synthesized by electrochemical etching and in-situ reduction methods, which showed excellent sensitivity and accuracy in the detection of rhodamine 6G (R6G) and serum from SLE patients. SERS technology was combined with deep learning algorithms to model serum features using selected CNN, AlexNet, and RF models. 92 % accuracy was achieved in classifying SLE patients by CNN models, and the reliability of these models in accurately identifying sera was verified by ROC curve analysis. This study highlights the great potential of Au@Ag-PSi substrate in SERS detection and introduces a novel deep learning approach for SERS for accurate screening of SLE. The proposed method and composite substrate provide significant value for rapid, accurate, and noninvasive SLE screening and provide insights into SERS-based diagnostic techniques.
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高影响因子
Nanophotonics
·
2024
·Vol. 13
·期 3
·307-318
·
IF 6.5
Yang Jiao,Yuanyuan Pan,Moru Yang,Zhen Li,Jing Yu,Rong Fu,Baoyuan Man,Chao Zhang,Xiaofei Zhao
Hollow urchin-like substrates have been widely interested in the field of surface-enhanced Raman scattering (SERS) and photocatalysis. However, most reported studies are simple nanoscale urchin-like substrate with limited light trapping range and complicated preparation process. In this paper, a simple and effective controllable synthesis strategy based on micro-nano hierarchical urchin-like ZnO/Ag hollow spheres was prepared. Compared with the 2D structure and solid spheres, the 3D urchin-like ZnO/Ag hollow sphere has higher laser utilization and more exposed specific surface area due to its special hollow structure, which resulted in excellent SERS and photocatalytic performance, and successfully realize the detection and photodegradation of antibiotics. The limited of detection of metronidazole can reach as low as 10 −9 M, and degradation rate achieve 89 % within 120 min. The experimental and theoretical results confirm that the ZnO/Ag hollow spheres can be used in the development of ZnO heterostructure for the detection and degradation of antibiotics, which open new avenues for the development of novel ZnO-based substrate in SERS sensing and catalytic application to address environmental challenges.
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