SENSORS AND ACTUATORS B-CHEMICAL
·
2025
·
IF 7.7
Chenggang Zhang,Meng Wang,Yi Li,Miao Yu,Jie Zhang,Ye Sun
Rapid pathogen typing is essential for precise antimicrobial therapy; however, conventional methods are time-consuming. Although surface-enhanced Raman spectroscopy (SERS) provides quick detection, current methods rely on expensive recognition molecules or suffer from weak signals due to electrostatic repulsion-induced inefficient SERS-active nanoparticle adsorption with bacterial surfaces. Herein, we present a bioreceptor-free AI-powered SERS biosensing strategy for rapid and accurate pathogen typing. Through protonation under acidic conditions, the method regulates bacterial surface charge to overcome electrostatic repulsion between bacteria and SERS nanoparticles. It maintains bacterial viability and allows rapid in situ assembly of the SERS-active platform directly on bacterial surfaces, thereby preserving pathogen integrity, improving detection reliability, and significantly enhancing Raman signals. Integrated with machine learning, it delivers 99 % accuracy in typing three common bacterial meningitis pathogens, accompanied by a perfect AUC–ROC value of 1.0. The entire process, including sample pretreatment, surface charge modulation plus nanoparticle adsorption, SERS acquisition, and machine-learning typing, is completed in as little as 15 min. Cost-effective and user-friendly, this method eliminates the need for bioreceptors and complex processing, demonstrates robust performance in clinical samples, and shows broad applicability in public health, food safety, environmental monitoring, and emergency diagnostics.
研究领域:
生物医学工程
·
分析化学
·
微生物学
·
即时检测
·
医疗人工智能
·
纳米生物技术
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产品关联
DOI
高影响因子
LANGMUIR
·
2025
·
IF 3.9
Yuxin You,Abdur Rahim,Mingyue Li,Xiaoyu Zhang,Min Li,Chengju Guo,Muhammad Saleem,Muhammad Zahid,Xueyou Xu,Mei Liu
As human society continues to develop and progress, the hazards posed to human health by emerging pollutants are becoming increasingly serious due to their unique characteristics such as specific toxicity, persistence, and bioaccumulation. It is critical to develop highly sensitive, renewable nonmetallic surface-enhanced Raman scattering (SERS) platforms for environmental monitoring, particularly for the trace detection of mercury ions in water. Here, we utilized a band-tunable F4TCNQ/MoS2 heterojunction achieving an ultrasensitive limit of detection (LOD) of 2.77 × 10–11 M for Hg2+ in pure water. The enhancement factor (EF) for the 989 cm–1 peak was found to be approximately 4.2 × 105, while that for the 722 cm–1 peak was 2.8 × 105. Such sensitivity arises due to the interfacial charge transfer (CT) and the weak electromagnetic interaction between the heterojunction and Hg2+ with the Raman reporter molecule 4-methylpyridine (4-MPy). The substrate exhibits remarkable selectivity against interfering ions (Ca2+, Mg2+, Pb2+, etc.,), along with high reproducibility (RSD < 9.33%), and stability up to one month under environmental conditions. The results indicate that the detection sensitivity is comparable to or even better than that achieved with the conventional SERS substrate to enable specific detection of Hg2+. Moreover, the substrate can be reused through photocatalytic degradation showing a 30 min duration for complete removal of Hg2+, enabled by the F4TCNQ/MoS2 heterostructure. This offers significant advantages for detecting Hg2+ in complex environmental samples, such as seawater and soil leachate, while also proving valuable for environmental monitoring and food safety applications.
研究领域:
环境科学
·
分析化学
·
纳米材料学
·
光催化
·
污染物检测
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产品关联
DOI
PubMed
高影响因子
SENSORS
·
2025
·Vol. 25
·期 7
·2316
·
IF 3.5
Jianjun Ding,Niansong Liu,Ganglin Wang,Naiyu Guo,Chao Sun
In response to the shortcomings of traditional surface-enhanced Raman spectroscopy (SERS) substrates, such as short shelf life, poor uniformity, and low selectivity, this study innovatively proposed a three-dimensional composite substrate of CNTs/Ag/AgNWs/SiO 2 . This substrate demonstrates excellent SERS enhancement effects, with a detection limit of 10 −12 mol/L for the probe molecule Rhodamine 6G (R6G) and an enhancement factor (EF) of 8.947 × 10 8 . Further experiments confirmed the substrate’s superior uniformity and stability. The enhancement mechanism was investigated using both experimental methods and the Finite Difference Time Domain (FDTD) approach. When commonly used pesticide thiram was used as the target analyte, the detection limit of the substrate reached 0.1 mg/L, which is significantly lower than the pesticide residue standards of China and the European Union. Additionally, the genetic algorithm (GA)-optimized Back Propagation (BP) neural network was introduced for the quantitative analysis of thiram concentrations. The experimental results indicated that the GA-BP algorithm achieved the training prediction accuracy of 92.5% for thiram, demonstrating good network performance. This method shows good selectivity and has broad application prospects in the detection of toxic chemicals, environmental pollutants, and food additives.
研究领域:
分析化学
·
纳米材料
·
环境监测
·
食品安全
·
传感器与生物传感器
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产品关联
DOI
PubMed
高影响因子
Materials
·
2025
·Vol. 19
·期 1
·
IF 3.2
Chenlong Zhao,Yaoyang Wang,Shuo Cheng,Yuhang You,Yi Li,Xianwu Xiu
Herein, a high-performance Ta2O5/AgNPs composite Surface-Enhanced Raman Scattering (SERS) substrate is engineered for highly sensitive detection of microplastics. Through morphology modulation and band-gap engineering, the semiconductor Ta2O5is structured into spheres and composited with silver nanoparticles (AgNPs), facilitating efficient charge transfer and localized surface plasmon resonance (LSPR). This architecture integrates electromagnetic (EM) and chemical (CM) enhancement mechanisms, achieving an ultra-low detection limit of 10−13M for rhodamine 6G (R6G) with excellent linearity. Furthermore, the three-dimensional “pseudo-Neuston” network structure exhibits superior capture capability for microplastics (PS, PET, PMMA). To address spectral interference in simulated complex environments, a multi-scale deep-learning model combining wavelet transform, Convolutional Neural Networks (CNN), and Transformers is proposed. This model achieves a classification accuracy of 98.7% under high-noise conditions, significantly outperforming traditional machine learning methods. This work presents a robust strategy for environmental monitoring, offering a novel solution for precise risk assessment of microplastic pollution.
研究领域:
环境科学
·
纳米材料
·
分析化学
·
光谱学
·
深度学习
·
污染监测
✓ 已验证
产品关联
DOI
PubMed
高影响因子
JOURNAL OF HAZARDOUS MATERIALS
·
2025
·
IF 11.3
Zhenyong Dong,Feixiang Zheng,Hao Wang,Yukai Liu,Xiao Ren,Feng Lin,Song Zhou,Li Chen,Yan-qing Lu,Guanghui Wang
The use of multiple pesticides in agriculture has caused mixed residues, complicating food safety testing. Surface-enhanced Raman scattering (SERS) offers high sensitivity and fingerprinting capabilities for pesticide detection; however,its application is limited by spot size, uneven sample distribution, spectral analysis challenges in mixed samples, and the lack of integrated automated systems for sample preparation, detection, and analysis. Hence, we developed a SERS microfluidic chip integrated with plasmonic microsphere lens arrays, which integrates optical field-modulated microspheres and plasmonic nanostructures to realise the transition of SERS detection from point-hotspots to uniform area-hotspots, achieving high-sensitivity, high-stability Raman detection under wide-field laser excitation. Moreover, a comprehensive a sample-to-answer total analysis system was established with this chip as the core, incorporating the micro-QuEChERS pretreatment module for efficient extraction of pesticides in complex matrices and the random forest-dual annealing spectral parsing algorithm for mixed spectral analysis. The results indicate that the limits of detection for 2,4-dichlorophenoxyacetic acid, acetamiprid, and thiabendazole were 1.15 nM, 0.63 nM, and 0.69 nM, respectively. The linear ranges were 10⁻⁴–10⁻⁹ M, with R² values of 0.9982, 0.9989, and 0.9996, respectively. Average recoveries ranged from 90.8 % -104.66 %, 89.1 %-107.89 %, and 89.73 %-108.4 %, respectively, with relative standard deviations below 8 %. The algorithm quantified mixed pesticides with mean absolute percentage errors of 4.96 %, 5.35 %, and 7.72 %, respectively. The system showed 3 s detection response and 15-minute analysis time. Thus, the method provides a rapid, on-site solution for detecting mixed pesticides in complex matrices by exceptional optical performance and automated processing functionality.
✓ 已验证
产品关联
DOI
PubMed
高影响因子
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
·
2022
·
IF 4.831
Xiaoqian Qiu,Jiao Gu,Taiqun Yang,Chaoqun Ma,Lei Li,Yamin Wu,Chun Zhu,Hui Gao,Zichen Yang,Zirui Wang,Xiaolin Li,Anqi Hu,Jinzeng Xu,Lvyuan Zhong,Jialu Shen,Anlan Huang,Guoqing Chen
The norfloxacin (NFX) residue in milk will increase human resistance to drugs and pose a threat to public health. In this work, a highly sensitive method for detection of NFX was developed based on surface enhanced Raman spectroscopy (SERS) using β-cyclodextrin functionalized silver nanoparticles (β-CD-AgNPs) as substrate. The unique spatial size and hydrophilicity of β-CD on the surface of AgNPs could selectively capture the target molecule (NFX) through some weak interactions, including hydrogen-bond interaction, electrostatic interaction, etc. The interactions were characterized by the UV–Vis absorption spectroscopy, fluorescence spectroscopy, Zeta potential and DLS. The Raman signal of NFX is largely enhanced when anchored by β-CD on the surface of AgNPs due to SERS effect. Through a series of experiments and analysis, the limit of detection (LOD) in standard solution and spiked milk were calculated to be 3.214 pmol/L and 5.327 nmol/L. The correlation coefficients (R 2 ) were 0.986 and 0.984, respectively. For milk sample determination of NFX, the recovery was 101.29% to 104.00% with the relative standard deviation (RSD) from 2.986% to 9.136%. To sum up, this developed SERS strategy is sensitive and specific to detect NFX in milk, it has practical application value and prospects.
研究领域:
食品安全
·
分析化学
·
生物医学
✓ 已验证
DOI
高影响因子
Food Analytical Methods
·
2017
·Vol. 11
·期 1
·69-76
·
IF 2.038
Li Pan,Teng Yuanjie,Nie Yonghui,Liu Wenhan
A simple, rapid, and environmentally friendly surface-enhanced Raman scattering (SERS) method was developed for the determination of trace amitraz in milk with the use of silver-coated gold nanoparticles (Au@Ag NPs) as enhancing reagent. The normal Raman and SERS spectra of amitraz were analyzed, and the peaks were assigned by density functional theory. The morphology of Au@Ag NPs was characterized and confirmed by transmission electron microscopy, scanning electron microscopy, and ultraviolet-visible spectroscopy. The SERS effects of Au@Ag NPs were investigated, including the types of solvents for dissolving amitraz, the volume ratio of the Au@Ag NPs and amitraz, and the concentration of aggregating agent (NaCl) for aggregate Au@Ag NPs. Results show that ethanol exerts the least interference on the SERS spectrum of amitraz and is more environmentally sound than methanol. The strongest SERS signal appeared when the volume ratio of Au@Ag NPs and amitraz was 2:1. Moreover, the strongest SERS signals appeared when the concentration of NaCl was 0.025 mol L −1 because of appropriate aggregation. Under the optimum conditions, the concentration of amitraz presents a good linear relationship with Raman intensity (723 cm −1 ) with a linear range of 9.77 × 10 −4 ~2.93 × 10 −2 g L −1 . The detected recoveries of amitraz in milk were between 81.7 and 100.5% with a relative standard deviation (RSD) of 2.61~5.51%.
研究领域:
食品科学
·
分析化学
·
环境科学
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DOI
高影响因子
MICROCHEMICAL JOURNAL
·
2021
·
IF 4.821
Fengli Gao,Weiqian Kong,Guangli He,Yanzhen Guo,Huili Liu,Shouren Zhang,Baocheng Yang
As an emerging technique for rapid detection, Surface-enhanced Raman scattering (SERS) has received much practical attention. Here, we report a uniformly distributed silver nanoparticles on well-defined tungsten oxide nanoflakes hierarchical nanostructures (Ag/WO 3-x ) as flexible solid SERS substrate. The vertically aligned Ag/WO 3-x nanoflakes were prepared by in situ redox reaction without reductant additives, ensuring the clean surface and free of extra interferences with good signal-to-noise ratio. Using rhodamine 6G (R6G) as probe molecule, the enhancement factor of developed Ag/WO 3-x nanoflakes SERS substrate was found to be high as 2.41 × 10 7 with an ultrasensitive detection concentration of 10 -12 M. Additionally, Ag/WO 3-x nanoflakes SERS substrate exhibited good reproducibility and long-time stability. Meanwhile, the pesticide thiram with a 1.3 pM limit of detection (LOD) can be readily determined via developed SERS substrate. To illustrate the potential practical value of the prepared substrates, 2.4 ppb spiked thiram on apple peel surface were both successfully detected. Notably, the developed SERS substrates could be cut into small pieces for detecting trace chemical or biological molecules and the flexible utilization of substrates would be improved dramatically. As a result, vertically aligned Ag/WO 3-x nanoflakes with well-defined shape and hierarchical structure have great potential as solid SERS substrate in the field of fast detection and trace analysis.
研究领域:
分析化学
·
纳米技术
·
材料科学
✓ 已验证
DOI
高影响因子
OPTICS EXPRESS
·
2019
·Vol. 27
·期 3
·3000-3013
·
IF 3.561
Wen Yang,Zhen Li,Zhengyi Lu,Jing Yu,Yanyan Huo,Baoyuan Man,Jie Pan,Haipeng Si,Shouzhen Jiang,Chao Zhang
In recent years, biomaterials have increasingly attracted attention on surface-enhanced Raman spectroscopy (SERS) due to their well Raman performance while metal particles are combined with biological substrates. Therefore, we propose an environmentally friendly substrate based on silver-plated cicada wings with seamless graphene layer (Gr-AgNPs-C.w.), which can be prepared with a simple and inexpensive method. Compared with AgNPs-C.w., Gr-AgNPs-C.w. hybrids show better SERS performance with high sensitivity, good uniformity and good stability with R6G detection. The minimum detected concentration can reach 10−15 M, and the value of R2 can reach 0.996, respectively. Theoretical simulation demonstrates the situation of electromagnetic field through COMSOL software. In addition, due to the affinity of graphene for biomolecules, we can successfully detect the DNA biomolecules through a simple process. Therefore, this cheap and efficient natural SERS substrate has great potential for a considerable number of biochemical SERS applications and can broaden the way in which multiple SERS platforms derived from other natural materials are prepared.
研究领域:
材料科学
·
分析化学
·
生物传感器
·
纳米技术
✓ 已验证
DOI
PubMed
高影响因子
Nanomaterials
·
2017
·Vol. 7
·期 3
·70
·
IF 3.553
Haixin Dong,Zhiming Liu,Huiqing Zhong,Hui Yang,Yan Zhou,Yuqing Hou,Jia Long,Jin Lin,Zhouyi Guo
Melanin plays an indispensable role in the human body. It serves as a biological reducer for the green synthesis of precious metal nanoparticles. Melanin–Ag nanocomposites were successfully produced which exhibited very strong surface-enhanced Raman scattering (SERS) effect because of the reducibility property of melanin. A melanin–Ag composite structure was synthesized in situ in melanin cells, and SERS technique was performed for the rapid imaging and quantitative assay of intracellular melanin. This imaging technique was also used to successfully trace the formation and secretion of intracellular melanin after stimulation with melanin-stimulating hormones. Based on the self-reducing property of melanin, the proposed SERS imaging method can provide potentially powerful analytical detection tools to study the biological functions of melanin and to prevent and cure melanin-related diseases.Keywords:surface-enhanced Raman scattering;melanin–Ag nanocomposites;bioimaging;melanogenesis
研究领域:
生物化学
·
纳米医学
·
分析化学
✓ 已验证
DOI
PubMed
高影响因子
APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING
·
2018
·Vol. 124
·期 12
·1-9
·
IF 1.604
Lin Shuang,Lin Xiang,Zhao Haiyan,Hasi Wuliji,Wang Li
Quantitative analysis always encounters difficulty in the field of surface-enhanced Raman spectroscopy (SERS) because of the lack of accurate and reliable analytical means. In this work, a new approach was demonstrated for the quantitative SERS measurement by self-assembled superlattice based on ultra-smooth Au nanospheres (NSs) embedded with 4-methylthiobenzoic acid (4-MBA) as the internal reference. Malachite green (MG) in water and chrysoidine in drinks with detection limit of 0.35 µM were successfully and quantitatively measured by employing Au@4-MBA@Au NSs superlattice as solid SERS substrate. Compared with conventional SERS methods, the fitting linearity of the relative SERS intensity vs. analyte concentrations has significantly improved by this new analysis means. As a result, our approach is a reliable analytical strategy to solve quantitative problems in SERS analysis, which can be easily applied for on-site detection and for preliminary monitoring of food samples.
研究领域:
分析化学
·
纳米科学与技术
·
食品安全检测
✓ 已验证
DOI
高影响因子
Journal of Materials Chemistry C
·
2018
·Vol. 6
·期 32
·8793-8803
·
IF 5.976
Wei Wei,Yixuan Du,Liangmiao Zhang,Yong Yang,Yanfeng Gao
Surface-enhanced Raman scattering (SERS) is a rapid and effective method for identifying fingerprint structures at low concentrations. However, the application of SERS for on-site detection with flexible and robust structures is challenging. In this work, we have developed a flexible, robust and reusable silver-functionalized SERS substrate for pesticide residue detection. This SERS substrate is composed of a silver nanoparticle@nanowire (AgNP@AgNW) network that is embedded into polydimethylsiloxane. The unique network structure provides rich SERS “hot spots”, where the electromagnetic field can be magnified through the excitation of localized surface plasmon resonances of AgNPs that surround AgNWs. The embedded structure improves the adsorption ability of the surface for target molecules, thereby reducing Raman fluorescence. In addition, this substrate retains 54.7% of the original Raman intensity after ten cycles; hence, this substrate shows satisfactory recyclability performance. Moreover, the SERS substrate exhibits acceptable detection reproducibility with 4.22% relative standard deviation and satisfactory tensile properties. These results demonstrate that our substrate has the potential for use in environmental supervision, food safety, explosive detection and security applications.
研究领域:
分析化学
·
环境科学
·
食品安全
✓ 已验证
DOI
高影响因子
危险品化学品经营许可证（带存储）