SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
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2026
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IF 4.8
Huifang Yao,Xiaolan Liu,Lu Xue,Yaxue Han,Yong Ye,Ji Zhou
Cellulose-based surface-enhanced Raman spectroscopy (SERS) substrates have emerged as a prominent research focus for advancing the practical application of SERS technology. Herein, a three-phase interfacial self-assembly strategy was developed to deposit nanoparticle layers onto the surface of cellulose nanofibril (CNF) nanopapers. This approach enables the fabrication of large-area monolayer or multilayer metallic nanoparticles (NPs) with diverse morphologies on the CNF surface, thereby constructing versatile SERS nanopapers with tunable surface plasmonic properties. The double-layered Au NPs@CNF nanopaper showed excellent SERS performance, achieving a minimum detectable concentration (MDC) of 10 −13 M (4-aminothiophenol, 4-ATP) and 0.1 ppm (methamphetamine, MAMP) with a wide linear range. Featuring excellent optical transparency and a well-defined porous structure, the substrate facilitates efficient extraction and enrichment of target analytes. By attaching its non-metallic side to sample surfaces, it enables SERS detection as well as food-safe, nondestructive trace analysis. As a proof of concept, these SERS nanopapers were applied to rapidly detect thiram on apple peels, with an MDC of 0.1 ng/cm 2 , and to extract and identify dyes from textiles with minimal damage. These approaches prevent nanoparticle contamination on food surfaces and eliminate destructive sampling, providing a reliable and biosafe strategy for nondestructive in-situ SERS monitoring.
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MICROCHEMICAL JOURNAL
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2026
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IF 5.2
Liman Fang,Xuanzhu Chen,Jiaxu Shao,Wenlong Xiang,Sinan Feng,Qianmin Tu,Ruiyun You,Chenjun Fang,Xiaowei Yu,Yongbiao Zheng
Nylon shrinkage effect generates dense SERS hotspots. • Ultrahigh sensitivity, achieving a detection limit of 10 −9 M for the probe molecule R6G. • Excellent uniformity and reproducibility, with a relative standard deviation (RSD) of 5.14% across 50 random spots. • Superior long-term stability, retaining 89.23% of the initial SERS signal after 30 days of storage. • Paste-and-peel method for in-situ CBZ detection on fruit. To address the widespread issue of carbendazim (CBZ), a common pesticide residue, on the surfaces of fruits and vegetables, our research team prepared silver nanoparticles using the sodium citrate reduction method and successfully loaded them onto a nylon membrane substrate via vacuum-assisted filtration. Subsequently, the substrate was modified with 4-mercaptobenzoic acid (4-MBA) as an internal standard signaling molecule, yielding a Nylon-Ag@4MBA flexible surface-enhanced Raman spectroscopy (SERS) substrate. The as-prepared Nylon-Ag@4MBA substrate exhibited excellent uniformity (RSD = 5.14%), a detection limit as low as 10 −9 M for the R6G probe molecule, and a signal retention rate of 89.23% after 30 days of storage. In the detection of actual samples such as apples, the recovery rates of CBZ ranged from 95.05% to 96.90% with relative standard deviations (RSDs) below 4.07%, demonstrating reliable quantitative capability. No interference was observed from common substances on the fruit peel. This study confirms the potential application of the Nylon-Ag@4MBA substrate for the on-site rapid detection of pesticide residues. Download: Download high-res image (81KB) Download: Download full-size image
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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
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2026
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IF 4.8
Jia Bin Zhang,Wan Hui Guo,Hao Zhang,Wen Pan,Ye Min Guo,Fan-Li Zhang,Cheng Wang,Sheng Hong Liu
5-Hydroxymethylfurfural (5-HMF) is a toxic compound formed during the improper processing or storage of honey, endangering human health. Thus, rapid and accurate detection of 5-HMF is essential. In this study, we fabricated uniform gold nanorod (AuNR) array surface-enhanced Raman spectroscopy (SERS) substrates with high-density plasmonic hot spots by optimizing the AuNR aspect ratio and employing a novel three-phase self-assembly technique, significantly enhancing detection sensitivity and reproducibility. The AuNR array (aspect ratio of 3.5) showed the strongest signals due to the close match between its 781 nm longitudinal LSPR wavelength and the 785 nm excitation laser wavelength, enabling efficient resonant coupling. Leveraging the dual-resonance of the AuNR arrays, tip-induced field focusing and nanogap-mediated plasmon coupling synergistically produced ultrahigh electromagnetic enhancement for SERS detection. Using AuNR array-3.5 as the SERS substrate, the signal intensity demonstrated a positive correlation with a concentration of 5-HMF in the range of 1–50 mg/L, with a limit of detection (LOD) as low as 0.093 mg/L. The substrate revealed excellent uniformity (relative standard deviation, RSD = 3.86%), reproducibility (inter-batch RSD = 2.51%), reusability (RSD = 13.2%) and stability (stored at 4 °C for 30 days). In spiked honey samples, this method achieved an LOD of 35.4 mg/kg, well below the international maximum residue limit (40 mg/kg), and recovery values ranging from 73.32% to 95.92%, confirming its high sensitivity and accuracy. This work provided a rapid, efficient approach for detection of 5-HMF in honey and highlights its application potential in SERS-based food safety monitoring technologies.
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Analytical Methods
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2026
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IF 3
Ze-Bo Zheng,Xiao-Hui Sun,Wan-Hui Guo,Wen Pan,Fan-Li Zhang,Sheng-Hong Liu
To enable rapid in situ detection of pesticide residues on foods with non-planar surfaces, a polymer-integrated flexible surface-enhanced Raman scattering (SERS) substrate was constructed and demonstrated using apples as a model. An ordered gold nanotriangle (AuNT) array was integrated onto a biaxially oriented polypropylene (BOPP) film to provide conformal interfacial adaptation, while a polyethylene terephthalate (PET) overlayer was introduced as a protective barrier to suppress environmental degradation and maintain hotspot integrity during storage and deformation. The densely packed AuNTs generated strong electromagnetic enhancement, yielding an analytical enhancement factor of 3.72 × 108 with good signal uniformity (RSD < 7%). More than 90% of the initial SERS activity was retained after 30 days, and over 80% was maintained under repeated mechanical deformation. The flexible substrate enabled direct and nondestructive detection of thiram on apple surfaces, achieving a limit of detection of 0.074 µg L−1 and a linear range spanning four orders of magnitude (R2 = 0.9865). Recoveries of 89.5–103.1% were obtained in spiked samples. These results indicate that the polymer-integrated flexible SERS platform provides a mechanically robust and storage-stable approach for practical analysis of contaminants on irregular food surfaces.
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MICROCHEMICAL JOURNAL
·
2026
·
IF 5.2
Qi Wang,Chi Zhang,Wenbin Jin,Yina Zhou,Xue Yang,Jimin Shao,Xiaowei Guo
DNPH-modified PS@Ag serves as a measurable pre-exposure reference state. • Paired ΔSNV resolves aldehyde-induced signed spectral redistribution. • Full-spectrum ΔSNV classifies four aldehydes with balanced accuracy 0.977. • Endpoint and ΔSNV provide complementary views of aldehyde identity. • Accuracy remained 0.90 in preparation holdout and 0.80 in concentration holdout. Reactive surface-enhanced Raman spectroscopy (SERS) interfaces are challenging to interpret because endpoint spectra combine reagent bands, analyte-induced changes, and hotspot-dependent variation. Here, a PS@Ag surface modified with 2,4-dinitrophenylhydrazine (DNPH) served as a structured pre-exposure reference, and aldehyde exposure was represented as a preparation-linked state transition derived from repeated spatial measurements on the same substrate. Four aldehydes were examined across broad nominal concentration ranges using independently executed preparations. Across three formaldehyde preparations, global transition descriptors showed more consistent concentration directionality than endpoint total intensity, whereas local coordinates were more preparation sensitive. At the matched 10 mg g −1 benchmark, endpoint spectra achieved a preparation-grouped balanced accuracy of 1.000. Full-spectrum standard-normal-variate difference spectra (ΔSNV) achieved balanced accuracy of 0.977 and macro-F1 of 0.971 while resolving signed redistribution from the DNPH prelayer to the endpoint. Preparation-replicate and leave-one-concentration-out validation yielded balanced accuracies of 0.90 ± 0.05 and 0.80 ± 0.05, respectively, for aldehyde-identity classification. A fixed full-spectrum ΔSNV model was subsequently evaluated on 12 newly fabricated substrate-preparation blocks comprising 96 endpoint-derived target observations, yielding balanced accuracy and macro-F1 of 0.979. Complementary XPS of a representative 10 mg g −1 formaldehyde endpoint supported DNPH deposition and aldehyde-exposure-associated surface-composition redistribution, while HPLC/PDA resolved DNPH derivatives of formaldehyde, acetaldehyde, and acrolein. The results establish a qualitative, state-resolved framework for aldehyde discrimination. Download: Download high-res image (190KB) Download: Download full-size image
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CHEMICAL ENGINEERING JOURNAL
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2026
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IF 12.5
Bohan Zhang,Jinying Lin,Wenzheng Wu,Zhenglong Chen,Ruiyun You,Yudong Lu,Tao Zhang,Yong Fan
A hydrogel SERS platform requiring no pretreatment has been developed. • The LOD for DOX and MTO were as low as 3.4 × 10 −8 M and 3.6 × 10 −9 M. • Machine learning achieved a 100% identification for DOX and MTO plasma samples. Rapid quantitative detection and classification of trace drugs directly in complex biological fluids are crucial in modern analytical chemistry. This paper proposes a label-free, interference-resistant smart surface-enhanced Raman scattering (SERS) sensing strategy. A machine learning-assisted Au@Ag/C-CNF/PEGDA hydrogel SERS sensor is developed for monitoring and identifying anthracycline anticancer drugs in plasma. Addressing the susceptibility to contamination and oxidation inherent in conventional SERS sensors, this sensor leverages the pore-trapping effect and nanoparticle encapsulation properties of hydrogel. This approach not only eliminates macromolecular interference but also maintains a high signal output of 71.05% for the internal Au@Ag SERS probe after 50 days. Leveraging the electrostatic interactions of carboxylated cellulose (C-CNF), the sensor exhibits excellent signal reproducibility with detection limits as low as 3.4 × 10 −8 M for doxorubicin (DOX) and 3.6 × 10 −9 M for mitoxantrone (MTO). Furthermore, this study employed machine learning models for high-dimensional feature extraction of SERS data, achieving up to 100% classification accuracy for DOX and MTO in spiked plasma samples. This approach holds promise as a robust solution for clinical drug concentration monitoring and species identification, potentially advancing precision treatment strategies in clinical practice. Download: Download high-res image (183KB) Download: Download full-size image
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CHEMICAL ENGINEERING JOURNAL
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2026
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IF 12.5
Qi Liu,Wenrou Yu,Anping Liu,Lianjie Zhou,Wen Tang,Yingzhou Huang
Multiple Synergistic SERS Enhancement of 3D micro-nano Ni-foam@MoS₂ • Overcomes EBC matrix interference for ultrasensitive 2.95 nM lactate detection • AI algorithms decode complex SERS spectra for non-invasive health monitoring. To address the critical demand for highly sensitive sensing interfaces in non-invasive exhaled breath condensate (EBC) analysis, this study develops a high-performance SERS substrate featuring interlaced, needle-like MoS₂ nanoclusters grown in situ on a 3D nickel foam scaffold (Ni-foam@MoS₂). This architecture effectively overcomes the severe signal heterogeneity and poor wearable compatibility that typically plague traditional plasmonic metal substrates. The system synergizes multiple coupled SERS enhancement mechanisms: the 3D porous scaffold and interwoven needle-like arrays form abundant optical microcavities. These microcavities effectively confine incident light and significantly enhance light-matter interactions, thereby inducing electromagnetic enhancement. Concurrently, the interlaced MoS₂ arrays not only efficiently concentrate trace analytes but also induce substantial chemical mechanism via vigorous charge transfer. Consequently, the substrate achieves an outstanding average enhancement factor of 1.88 × 10 9 , alongside superb signal reproducibility and long-term environmental stability. By deploying this Ni-foam@MoS₂ substrate for the rapid off-line analysis of simulated exhaled breath condensate (EBC), we achieved the ultrasensitive detection of lactate (LA), a critical metabolic biomarker, with a limit of detection as low as 2.95 nM. Furthermore, coupling these complex spectral datasets with advanced artificial intelligence algorithms enabled the highly accurate classification of concentration-dependent LA spectral variations, demonstrating significant proof-of-concept potential for mask-integrated biomolecular sensing and non-invasive physiological monitoring.
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TALANTA
·
2026
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IF 6.7
Min Peng,Lei Shao,Jiangkun Zhai,Yudong Yao,Xi Mei,Shanshan Zhu
Alzheimer's disease (AD) is a progressive neurodegenerative disorder requiring early diagnosis for effective intervention. The combination of blood Aβ 42 /Aβ 40 ratio and p-tau-181 is recognized as a promising core biomarker panel for AD diagnosis. However, conventional detection methods suffer from limitations including time-consuming procedures, lack of multiplexing capability, and insufficient sensitivity. Herein, we developed a magnetic surface-enhanced Raman scattering (SERS)-encoded tags-based lateral flow immunoassay (LFIA) for simultaneous detection of Aβ 42 , Aβ 40 , and p-tau-181 on a single test line. Magnetic Fe 3 O 4 @Au nanoparticles were synthesized and modified with three distinct Raman reporters (DTNB for Aβ 42 , 4-MBA for Aβ 40 , and 2-MPY for p-tau-181) and corresponding detection antibodies. Under optimal conditions, the assay achieved rapid detection (∼28 min) and high sensitivity, with limits of detection of 93.33 fg/mL for Aβ 42 , 218.78 fg/mL for Aβ 40 , and 56.23 fg/mL for p-tau-181. The method exhibited excellent specificity against interfering substances (BSA, human IgG) and closely related species (Aβ 38 , p-tau-217), as well as good reproducibility (RSD <5%) and stability (≥4 weeks). In clinical plasma samples (n = 40), the combined score (p-tau-181/(Aβ 42 /Aβ 40 )) progressively increased with disease severity and correlated well with MMSE scores and MRI MTA grades, capturing both cognitive decline and hippocampal atrophy. This magnetic SERS-encoded LFIA platform offers a rapid, sensitive, user-friendly, and multiplex-capable approach for early AD diagnosis and progression monitoring, showing promise for future point-of-care applications.
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Inorganics
·
2026
·Vol. 14
·期 7
·188
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IF 3.4
Haocheng He,Boya Ma,Haozhe Sun,Zimeng Li,Huixu Liu,Wenshi Zhao,Naveen Reddy Kadasala,Bo Feng,Yang Liu
The persistent accumulation of tetracycline (TC) antibiotics in aquatic environments poses severe ecological and public health risks, necessitating the development of multifunctional platforms capable of simultaneous detection and degradation. Herein, we report magnetically recoverable plasmonic Fe3O4/Cu2O-Ag nanocomposites (NCs) that integrate visible-light-driven photocatalysis with ultrasensitive surface-enhanced Raman scattering (SERS) detection. Hierarchical flower-like Fe3O4nanocrystals were employed as magnetic supports, followed by in situ growth of Cu2O nanocrystals and controlled deposition of Ag nanocrystals. The optimized composite (FCA-2) exhibited enhanced visible-light absorption (Eg= 1.86 eV), suppressed electron–hole recombination, and improved photocurrent response, which were attributed to Schottky barrier formation at the Cu2O-Ag interface and localized surface plasmon resonance (LSPR) effects. Under simulated solar irradiation, FCA-2 NCs achieved 91.79% degradation of TC within 60 min, following pseudo-first-order kinetics (k = 20.37 × 10−3min−1). Finite-difference time-domain (FDTD) simulations revealed that optimal Ag loading maximized plasmonic “hot spot” density, thereby enhancing electromagnetic field intensity and SERS performance. The FCA-2 substrate enabled ultrasensitive TC detection with a limit of detection of as low as 10−10M. Moreover, the superparamagnetic Fe3O4core allowed for rapid magnetic separation and sustained performance over multiple SERS–photocatalysis cycles, with negligible signal attenuation after 30 days. This work presents a rational strategy for constructing plasmonic magnetic NCs that synergistically couple photocatalytic remediation, ultrasensitive sensing, and magnetic recyclability, offering significant potential for integrated environmental monitoring and sustainable water treatment applications.
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SENSORS
·
2025
·Vol. 25
·期 13
·3920
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IF 3.5
Yan Wu,Junshi Huang,Ni Tong,Qi Chen,Fang Peng,Muhua Liu,Jinhui Zhao,Shuanggen Huang
In the process of chicken breeding, there has been a great deal of abuse of antibiotics. Antibiotics can enter the human body along with the chicken meat, comprising a possible risk to human health. In this paper, principal component analysis (PCA)–linear discriminant analysis (LDA) was chosen to classify neomycin (NEO) and chloramphenicol (CAP) residues in chicken meat. A total of 400 chicken meat samples were used for the classification, of which 268 samples and 132 samples were used as the training sets and the test sets, respectively. The experimental condition of SERS spectrum collection was optimized, including the use of a gold colloid and active agent, and an improvement in the adsorption time. The optimal measurement conditions for the SERS spectra were an adsorption time of 4 min and the use of a 14th-generation gold colloid as the enhanced substrate without a surfactant. For three groups of different spectral preprocessing methods, the classification accuracies of PCA-LDA models for test sets were 78.79% for baseline correction, 84.85% for the second derivative and 100% for the second derivative combined with baseline correction. LDA was used to establish a classification model to realize the quick determination of NEO and CAP residues in chicken meat by SERS. The results showed that the characteristic peaks at 546 and 666 cm−1could be used to distinguish NEO and CAP residues in chicken meat. The classification model based on PCA-LDA had higher classification accuracy, sensitivity and specificity using a second derivative combined with baseline correction as the spectral preprocessing method, which shows that the SERS method based on PCA-LDA could be used to perform the classification of NEO and CAP residues in chicken meat quickly and effectively. It also verified the feasibility of PCA-LDA to effectively classify chicken meat samples into four types. This research method could provide a reference for the measurement of such antibiotic residues in chicken meat in the future.
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ACS Applied Optical Materials
·
2025
·
IF 3.8
Xiaolong Yin,Tong Shi,Jiacheng Li,Yu Wang,Jizhe Song,Hongyan Zhao,Zhixiu Wang,Cuixia Bi
In this work, Au@Ag nanostars were successfully synthesized via a seed-mediated growth method, using presynthesized Au nanostars as structural templates. The structure of the Au@Ag nanostars can be precisely controlled by adjusting the concentration of AgNO3 and Au nanostar seeds. The structural configuration of the Au@Ag nanostars can be precisely tuned from partially encapsulated cores to fully encapsulated architectures. The Au@Ag nanostars display tunable localized surface plasmon resonance (LSPR) characteristics in response to changes in the Ag shell thickness. The Raman enhancement of 4-ATP indicates that surface-enhanced Raman spectroscopy (SERS) performs optimally when Ag fully encapsulate the Au nanostars, confirming the results from FDTD theoretical simulations. The remarkable sensitivity of SERS detection originates from the enhanced electromagnetic fields generated at both the nanogaps and branched ends of the Au@Ag nanostars, coupled with their optimized LSPR characteristics. The detection limit achieved an exceptionally low level of 10–15 M. Effective detection of pesticides such as thiram and carbaryl was also achieved. The structural configuration of the Au@Ag nanostars fully leverages the synergistic effects between Au and Ag, along with the nanogaps, to significantly enhance the sensitivity and stability of SERS detection. This study provides theoretical and experimental references for plasma metal nanostars with significantly enhanced electromagnetic fields and offers insights for future SERS studies.
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PHYSICA SCRIPTA
·
2025
·Vol. 100
·期 10
·105607
·
IF 2.6
Xiaolong Song,Yafang Pan,Shi Wang,Peng Wang,Mingli Wang
Compared with single-metal materials, bimetallic materials exhibit superior oxidation resistance and stability. The Surface-enhanced Raman Scattering (SERS) performance can be effectively modulated by adjusting the concentration of the precursors. Herein, Fe3O4@EDTA@Ag-Cu NPs were successfully synthesized, the SERS performance of the substrate was significantly enhanced by modulating the concentration of the silver and copper precursors. The results indicated that the SERS sample prepared by mixing the dispersion of Fe3O4@EDTA@Ag-Cu NPs with Rhodamine 6G(R6G) solution at a 1:2 volume ratio, achieved a detection concentration as low as (1.0 ± 0.2) × 10−10 M for R6G. Furthermore, the substrate demonstrated high sensitivity, uniformity, temporal stability, reproducibility, and the capability for the rapid detection of benzimidazole in strongly alkaline conditions.
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