Materials
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2025
·Vol. 19
·期 1
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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
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纳米材料
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分析化学
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光谱学
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深度学习
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污染监测
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JOURNAL OF COLLOID AND INTERFACE SCIENCE
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2026
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IF 9.6
Zhiming Chen,Jiabin Chen,Haoming Bao,Kaitao Liu,Pan Zeng,Fan Yang,Wei Cao,Dongqi Yang,An Cao,Tao Zhang,Yue Li
Surface-enhanced Raman scattering (SERS) has been one of the efficient strategies for trace molecular analysis, but the traditional substrates with sharp tips cannot effectively detecting the molecular isomers. Here, we develop a facile way to fabricate large-area, reproducible Ag/Au nanocavity arrays by the combination of microsphere-templated soft lithography and self-assembly. Compared to the flat and convex substrate, the Ag/Au units arranged on the concave surface exhibit a high-density of hotspots via spatial light confinement and multi-reflection-enhanced electromagnetic coupling, which enables highly sensitive detection of probe molecules down to10 −12 M. Moreover, by integrating machine learning algorithms, the test set shows a coefficient of determination (R 2 ) of 0.9896, achieving advanced training performance for classifying four structurally analogous quinolone antibiotics (ciprofloxacin, enrofloxacin, danofloxacin, and enoxacin) with a quantitative prediction of 10 −10 M. This work demonstrates a robust pathway for the controllable fabrication of high-performance SERS substrates for the development of intelligent, quantitative, and on-site sensing platforms in complex practical scenarios. Download: Download high-res image (179KB) Download: Download full-size image
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TALANTA
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2026
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IF 6.7
Wangyu Nan,Qingdan Ye,Jie huang,Pei Liang,Qianmin Dong,Kun Pang,Zihong Ye,Kai Sun,Yufeng Wang
In this study, we developed an aptamer-mediated surface-enhanced Raman scattering (SERS)-coupled immunochromatographic assay (ICA) for the quantitative detection of pyrethroids. For this approach, core-shell gold nanoparticles (Au@Au NPs) were used as SERS probes by conjugating with aptamers, and fluorescent Raman reporter molecules (MPBN) were incorporated to yield stable, reproducible spectral signals. Leveraging the aptamers' specific recognition of the target analyte, Raman-labeled Au@Au NPs could be effectively captured by the test line of the immunochromatographic strip, thereby enabling the quantitative analysis of fenvalerate-with a limit of detection (LOD) as low as 0.4 ppb. Comparative experiments revealed that the detection sensitivity of this SERS-ICA method was 476 times higher than that of conventional lateral flow assays (LFA), showcasing a remarkable sensitivity advantage. To validate its practicality, spiked recovery experiments were conducted on three real samples, namely welsh onions, cowpeas, and kidney beans. The results showed that the spiked recoveries ranged from 78.3% to 112.5%, with relative standard deviations (RSD) between 1.7% and 20.1%. This fully confirms that the method possesses favorable specificity and accuracy, making it suitable for real-sample detection. This detection platform offers a new technical route for the rapid on-site monitoring of trace contaminants in food safety and environmental surveillance, holding broad application prospects.
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Advanced Science
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2026
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IF 14.1
Hanbin Deng,Rui Wang,Dianqi Zhang,Wei Zhang,Jaebum Choo,Fabiao Yu,Shaowen Cheng
Bacterial wound infections, particularly those caused by Escherichia coli and Pseudomonas aeruginosa , are difficult to treat due to biofilm formation, multidrug resistance, and chronic inflammation. Here, we report a multifunctional nanoplatform based on a surface‐enhanced Raman scattering (SERS) probe that enables simultaneous photodynamic therapy, antibiotic delivery, and real‐time infection monitoring. The probe comprises gold nanoparticles coated with Prussian blue, which acts both as a near‐infrared photosensitizer and a Raman reporter in the spectroscopically silent region, further loaded with colistin sulfate and stabilized with bovine serum albumin. Upon irradiation with a 650 nm laser, the probe produces reactive oxygen species, and, in combination with antibiotic release, achieves enhanced eradication of Gram‐negative bacteria (>90% reduction) using a significantly reduced antibiotic dose. The SERS signal in the silent region enables background‐free, in situ discrimination and quantification of bacterial load during treatment. In both normal and diabetic mouse wound models, the probe accelerates bacterial clearance, facilitates M2 macrophage polarization, and promotes angiogenesis and collagen deposition, thereby resulting in improved wound healing. Analysis of 36 clinical wound samples demonstrates sensitive and specific Gram‐positive and negative bacterial identification. This approach establishes a clinically translatable strategy for precise infection management, real‐time monitoring, and enhanced wound repair.
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MICROCHEMICAL JOURNAL
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2026
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IF 5.2
Tianxin Zuo,Hengchang Zhang,Kaidi Sun,Hairong Chen,Caiqin Han
AuNPs@BN@AgNR SERS sensor for ultrasensitive salivary BR/BV detection. • Ultra-low LODs of 5 × 10 −8 M for BR and 1 × 10 −7 M for BV in spiked saliva. • FDTD simulations confirm 5.54-fold electric field enhancement via LSPR coupling. • BN layer enables target enrichment and suppressed non-specific adsorption. Bilirubin (BR) and biliverdin (BV) are non-invasive biomarkers for hepatic function assessment. Their detection in saliva is limited by sub-micromolar concentrations and matrix interference. Conventional methods exhibit limits of detection (LODs) ≥ 10 −6 M. Herein, an AuNPs@BN@AgNR SERS sensor is fabricated via oblique angle deposition, wet chemical etching, and chemical reduction. FDTD simulations demonstrate a 5.54-fold local electric field enhancement in the x–z plane relative to the BN@AgNR bilayer, resulting from LSPR coupling between AuNPs and AgNRs. Experimentally, the substrate achieves enhancement factors up to 4.06 × 10 9 with a spatial relative standard deviation (RSD) of ≤7.00%. The sensor yields LODs of 1 × 10 −12 M (BPE), 2.5 × 10 −8 M (R6G), and 1 × 10 −6 M (CV). In spiked saliva, the sensor exhibits quantifiable concentration ranges of 5 × 10 −8 M to 1 × 10 −4 M for BR and 1 × 10 −7 M to 1 × 10 −4 M for BV, with corresponding LODs of 5 × 10 −8 M and 1 × 10 −7 M. This performance is attributed to BN-mediated electrostatic target enrichment and the suppression of non-specific protein adsorption. This study provides an analytical platform for the non-invasive trace analysis of hepatic biomarkers. Download: Download high-res image (112KB) Download: Download full-size image
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Science Advances
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2026
·Vol. 12
·期 27
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IF 13.9
Wenrou Yu,Zhaoxian Chen,Yao Liu,Yan Du,Hui Wang,Fengjie Tang,Xin Xie,Yingzhou Huang
Achieving noninvasive high-frequency monitoring of ischemic stroke (IS) remains a major clinical challenge for timely intervention and precise secondary prevention. Establishing precise correlations between patients’ systemic microscopic molecular fingerprints and localized macroscopic organ pathological events is essential to overcome the limitations of single-modal detection and enhance the efficacy of clinical risk assessment. However, because of the complexity of heterogeneous data, effectively integrating the cross-dimensional “molecular imaging” data remains a critical bottleneck in achieving this goal. Here, we present a proof-of-concept method to distinguish patients with confirmed IS from healthy controls (HCs) that used machine learning (ML)–based methods to surface-enhanced Raman spectroscopy (SERS) of urine (one-dimensional) and carotid artery B-ultrasound imaging (CBI) (two-dimensional). In an exploratory cohort of 101 participants, this approach analyzed 10,100 SERS spectra and 481 CBI images, achieving 92% classification accuracy and an area under the curve (AUC) of 0.95. Furthermore, by combined SERS spectra and liquid chromatography–mass spectrometry technology, this study preliminarily explored the urinary biomarker differences between HC/IS groups. The multidimensional data fusion strategy proposed in this study effectively bridges the information gap between traditional molecular detection and clinical phenotypes by systematically correlating microfluidic biomarkers with macro-organ imaging features. This approach provides a previously unexplored, noninvasive, and highly accurate tool for risk stratification and clinical decision-making in classifying HC/IS groups.
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FOOD RESEARCH INTERNATIONAL
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2026
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IF 8.8
Zhenglong Chen,Zhile Zhao,Yuxin Bu,Xinyan Yang,Yulin Fang,Hui Lin,Yudong Lu
An HP-β-CD-functionalized hydrogel SERS strategy was developed for white tea storage-year analysis. • HP-β-CD-assisted capture and Ag-hotspot SERS sensing of tea polyphenols were mechanistically discussed. • Agarose improved nanoparticle dispersion and signal uniformity. • Sample-level machine learning enabled internal storage-year discrimination of the tested white tea samples. • External validation using multi-origin samples is still required to confirm practical robustness. Accurate discrimination of white tea storage years is important for quality evaluation, authenticity control, and market regulation. In this study, an HP-β-CD-functionalized hydrogel surface-enhanced Raman scattering (SERS) substrate was developed for rapid storage-year discrimination of white tea. Hydroxypropyl-β-cyclodextrin-functionalized silver nanoparticles (HP-β-CD/Ag NPs) were incorporated into an agarose hydrogel to construct an HP-β-CD/Ag NPs/AG substrate. HP-β-CD was designed to promote the local capture of aromatic and polyphenolic tea components near SERS-active Ag hotspots, while the agarose hydrogel improved nanoparticle dispersion and signal uniformity. The optimized substrate retained distinguishable SERS responses for epigallocatechin gallate and quercetin at 10 −7 mol L −1 and showed good signal uniformity, with a relative standard deviation of 6.96%. White tea samples from seven storage years between 2011 and 2023 were analyzed, including 10 independent samples per year and 10 spectra per sample. Principal component analysis showed that the first three principal components explained 98.94% of the spectral variance. Under 50 repeated tea-sample-level splits, machine-learning models achieved stable internal storage-year discrimination, with sample-level accuracies ranging from 97.62% to 100.00%. A sample-level permutation test further indicated that the classification performance was unlikely to result from random label association. These results suggest that the proposed hydrogel SERS strategy can provide a rapid and fingerprint-based approach for white tea storage-year discrimination, although further external validation using more diverse samples is still required. Download: Download high-res image (179KB) Download: Download full-size image
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TRANSITION METAL CHEMISTRY
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2026
·Vol. 51
·期 2
·30
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IF 2.8
Li Shijie,Zhao Chenchen,Wang Lingyu,Feng Xiaoqi,Hou Jiaqiang,Gao Tianyu,Yang Guoli,Yao Kaisheng
To address the limitations of traditional synthesis methods for gold nanostructures, which rely on high temperatures, toxic reagents, and harsh conditions, this study proposes an eco-friendly strategy for synthesizing gold spikelet nanoflowers using poly(ionic liquid) (PIL) as a structure-directing agent. By employing HAuCl 4 as the precursor and ascorbic acid (AA) as the reducing agent, hierarchical Au spikelet nanoflowers with tertiary structure were successfully prepared via a one-pot method in a 60 °C water bath. Systematic investigation of the influencing factors revealed that temperature, AA concentration, and PIL concentration collectively determine the product morphology, with PIL concentration exerting the most significant influence on both the morphology and hierarchical structure of the Au nanoflowers. Using Rhodamine 6G (R6G) as a molecular probe, the resulting substrate exhibited exceptional surface-enhanced Raman scattering (SERS) sensitivity, achieving a detection limit of 10 − 12 M for R6G, which surpasses the performance of most reported Au/Ag-based materials, and demonstrates high reproducibility (< 2% average relative deviation (RAD) from measurements at five randomly selected locations). This work provides a sustainable approach for fabricating high-performance SERS substrates, demonstrating promising potential for applications in biological sensing and diagnostics. Graphical
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ACS Sensors
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2026
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IF 9.1
Yang Cheng,Xinyuan Bi,Bo Liu,Zhou Chen,Linley Li Lin,Yuling Wang,Jiahua Pan,Jian Ye
Prostate cancer (PCa) remains a major global health burden, yet current screening tools often lead to overdiagnosis due to low specificity, highlighting the urgent need for more precise diagnostic approaches. Prostatic fluid (PSF) represents a promising but underexplored biofluid with exceptional diagnostic potential due to its direct contact with the PCa microenvironment. Here, we employed molecule-level interpretable surface-enhanced Raman spectroscopy (SERS) to comprehensively investigate PCa-associated alterations in two PSF components including metabolites and small extracellular vesicles (sEVs) and explored their potential interrelations via correlation analysis. Through molecule-resolvable SERS spectral set (MORE SERSome) technique, we identified ergothioneine and deoxyguanosine as differential metabolites between PCa and benign prostatic hyperplasia patients. We further constructed a fusion diagnostic model by integrating metabolites and sEVs information. The fusion model significantly outperformed the diagnostic accuracy by applying any single component, suggesting diagnostic complementarity between PSF metabolites and sEVs. Integration with clinical variables such as age and plasma prostate-specific antigen concentration further enhanced performance with the area under the curve as high as 0.93 for PCa diagnosis, substantially surpassing existing screening methods. These findings strengthen the importance of in-depth analysis of specific PSF components and further promise the potential of SERS-based PSF profiling as a noninvasive strategy for PCa diagnosis and biopsy guidance.
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ACS Applied Nano Materials
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2026
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IF 5.8
Yang Yu,Min Zhong,Huabo Huang,Liang Li
Silver (Ag) nanosheets were successfully coated on the glass slides, filter paper, bottle cap-PP, and bottle body-PET substrates using Ag seed-induced aggregation. The Ag nanoparticles acting as the crystal nucleus were first grown on the supporting substrates, and then citric acid and ascorbic acid were introduced to act as morphology-controlling agents to enable the assembly of silver nanosheets on the supporting substrate. The as-prepared Ag substrates were used as effective surface-enhanced Raman scattering (SERS) substrates for the detection of trace amounts of small molecules. Using Rhodamine 6G (R6G) as probing molecules, it was found that the Raman signal of R6G could be still detected when the concentration of R6G was as low as 10–10 mol/L for the glass slides, filter paper, bottle cap-PP, and bottle body-PET SERS substrates, and the enhancement factor (EF) values of glass slide, filter paper, bottle cap-PP and bottle body-PET substrates were 1.21 × 107, 0.82 × 107, 1.93 × 107 and 2.07 × 107, respectively. In addition, the relative standard deviation (RSD) was also calculated, and the values for the four SERS substrates were 9.7, 21.6, 6.3, and 6.1%, respectively. This method has been proven to be suitable for the growth of Ag nanosheets on different substrates and has broad potential applications in the detection of trace small molecules.
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ANALYTICAL AND BIOANALYTICAL CHEMISTRY
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2026
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IF 4.1
Zhang Yanjiao,Guo Yanxian,Wang Wen,Fang Xianglin,Cong Yanguang,Li Shaoxin
Sweat is an ideal biofluid for noninvasive monitoring of athletes’ physiological status during exercise, as its rich chemical composition directly reflects health and metabolic state. Herein, we develop a wearable device based on segmented circular microfluidic paper–based surface-enhanced Raman scattering (SCMP-SERS) for real-time sweat analysis during physical activity. The core sensor incorporates gold@carbon dots–based plasmonic paper, which exhibits exceptional SERS performance with a maximum enhancement factor of up to 3.6 × 10 9 . Combined with a flow-regulating microfluidic network, the system allows controlled sweat collection and quantitative analysis. It can identify key sweat biomarkers, such as urea, uric acid, and lactic acid, and distinguish differences between individuals. Furthermore, the device’s multi-channel design facilitates continuous sweat sampling and longitudinal SERS quantitation throughout extended exercise sessions. Furthermore, by integrating machine learning, the SCMP-SERS device successfully identifies stimulants in artificial sweat with over 97.9% accuracy. This innovative approach demonstrates significant potential for real-time antidoping surveillance and personalized sports physiology monitoring. Graphical abstract
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Analytical Methods
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2026
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IF 3
Xinyu Wen,Ruixue Sun,Hui Si,Junting Li,Chao Zhang,Hailing Zheng,Yang Zhou,Bing Wang
Silk fibroin (SF) is a key biomarker for ancient silk artifacts. The rapid and sensitive detection of SF is therefore essential for their compositional analysis and preservation. In this research, an anti-SF monoclonal antibody (anti-SF mAb) was conjugated with an AuDTNB@Ag nanocore–shell structure to form a highly effective SERS immunoassay probe, and a surface-enhanced Raman scattering (SERS) assisted immunochromatographic assay (ICA) was developed for the detection of silk residues in artifacts. The visual limit of detection (vLOD) is 40 ng mL−1 while the instrumental limit of detection (iLOD) is 3.96 ng/mL−1 with a wide linear detection range (5–100 ng mL−1) as determined through Raman spectroscopy. The assay exhibited high specificity against interfering proteins and demonstrated consistent inter-batch reproducibility. When detecting real cultural relic samples, the immunochromatographic strip assay showed high accuracy and reliability, which was validated by indirect enzyme-linked immunosorbent assay (ELISA). Considering its high sensitivity, rapid analysis, and portability, the SERS ICA may provide a technologically advanced strategy for the on-site screening of silk residues in archaeological and museological contexts.
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