ACS Applied Materials & Interfaces
·
2025
·
IF 8.2
Minghui Niu,Chengwei Shan,Chenlong Xue,Xiaowei Xu,Aoyan Zhang,Yihong Xiao,Junyu Wei,Defeng Zou,Gina Jinna Chen,Aung Ko Ko Kyaw,Perry Ping Shum
The excellent photoelectric conversion efficiency and tunable bandgap of metal halide perovskites make them highly suitable for SERS applications. However, the low stability of perovskites in water and oxygen greatly hinders their use in SERS detection, particularly in biomolecule detection applications, which often require water-based test solutions. Herein, we report a gold (Au)/perovskite-polyvinylidene difluoride (PVDF) nanocomposite/ZnO nanoflower (GPPZ) SERS substrate capable of functioning in aqueous solutions. Its enhancement ability is attributed to plasmon-induced resonance energy transfer (PIRET) and an electromagnetic mechanism. The surface plasmon resonance created by ultrathin Au and ZnO nanoflowers induces resonance energy transfers to the perovskite via PIRET, facilitating a quasi-matched charge transfer between the perovskite and the probe molecule. The PVDF coating protects the perovskite from water and oxygen without affecting the resonance energy-transfer process. As a result, an enhancement factor (EF) approaching 1 × 106 was achieved for the crystal violet molecule. Additionally, we fabricated a flexible GPPZ substrate using silk screen printing, enabling mass production of an SERS array substrate. The printed flexible GPPZ substrates demonstrated micromole-level cysteine detection with an EF of 6.8 × 105, showing potential for application in hyperhomocysteinemia diagnosis.
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Biosensors-Basel
·
2025
·Vol. 15
·期 8
·477
·
IF 5.6
Jiahui Tian,Xianhe Jiao,Jiaqi Guo,Qian Yu,Shuqin Zhang,Guizhou Gu,Kundan Sivashanmugan,Xianming Kong
The presence of polycyclic aromatic hydrocarbons (PAHs) in edible oil has a serious effect on human health and may potentially induce cancer. This study combined thin-layer chromatography and surface-enhanced Raman spectroscopy (TLC-SERS) to rapidly and quantitatively detect PAHs in culinary oil. Machine learning using the principle component analysis-back propagation neural network (PCA-BP) was integrated with TLC-SERS for the detection of PAHs. Ag nanoparticles on diatomite (diatomite/Ag) TLC-SERS substrate were prepared via an in situ growth process and employed as a stationary phase in the TLC channel. The analyte sample was dropped onto the TLC channel for separation and detection. The diatomite/Ag TLC channel demonstrated excellent separation capability and superior SERS performance and successfully detected PAHs from edible oil at a sensitivity of 0.1 ppm. The PCA-BP quantitative analysis model demonstrated outstanding prediction performance. This work demonstrates that the combination of TLC-SERS technology with PCA-BP is an efficient and accurate method for quantitatively detecting PAHs in edible oil, which can effectively improve the quality of food.
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Analytical Methods
·
2025
·Vol. 17
·期 24
·5034-5044
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IF 2.6
Xinzheng Zhu,Ruimei Wu,Xu Wang,Xin Fu,Zhongshou Liu,Xiang Geng,Jie Teng
In this study, ultra-thin metal–organic framework nanosheets (MOFNs) were used for preparing an enhanced substrate to rapidly detect imidacloprid residues in citrus based on surface-enhanced Raman scattering (SERS) technology. The ultrasonic stripping method was used to prepare Co-MOFNs. Subsequently, a CoAg-MOFN-enhanced substrate was prepared by loading AgNPs onto the Co-MOFNs to enhance the SERS signal. The effects of the concentration of AgNPs, the ratio of Co-MOFNs to AgNPs, and the mixing time between the as-prepared enhanced base and imidacloprid standard solution on the SERS peak intensity were investigated, which showed that when the concentrated volume of AgNPs was 20 times and the mixed volume ratio of Co-MOFNs and AgNPs was 1 : 1, the prepared CoAg-MOFNs exhibited a good SERS enhanced effect. Notably, SERS response was the best when the CoAg-MOFN nanocomposite was mixed with an imidacloprid pesticide for 1 min. Utilizing density functional theory (DFT), four Raman characteristic peaks, specifically at 764, 784, 942 and 1035 cm−1, were identified for the qualitative and quantitative assessment of imidacloprid pesticide residues in citrus fruits. A quantitative analysis curve representing imidacloprid residues was developed, correlating the intensity at 1035 cm−1 over a range of 0.5–50 mg kg−1 (y = 2.7964x + 26.211, R2 = 0.9923), which demonstrated a strong linear relationship. The limit of detection (LOD) was 0.5 mg kg−1 and the limit of quantitation (LOQ) was 0.5 mg kg−1, which could meet the maximum residue limit (MRL) of 1 mg kg−1 stipulated by the Codex Alimentarius Commission (CAC) and European Union (EU). The recovery rates were 93.02–101.07%, and the RSD was 2.57–7.71%, indicating that the prepared CoAg-MOFN nanocomposite combined with the SERS method is suitable for the analysis of imidacloprid pesticide residues in citrus.
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FOOD CHEMISTRY
·
2025
·
IF 9.8
Ying Yang,Wenqi Zhang,Lu Zhang,Ziyan Shi,Dexiang Wei,Weiwei Xia,Xiaoguang Xu
Ochratoxin A (OTA) is a highly toxic and bioaccumulative mycotoxin found in grains, threatening food safety. Surface-enhanced Raman spectroscopy (SERS) combined with immunochromatography enables rapid and sensitive detection of OTA. This study aimed to develop a novel core-shell-satellite SERS probe (Au@Ag@(Cu-ZIF-8)-AuNPs) for OTA detection. The structure comprised an Au@Ag nanoparticle core, coated with Cu-doped ZIF-8 and gold nanosatellites. This design generated dense electromagnetic “hot spots” through plasmonic coupling between the core and satellites. Simultaneously, Cu doping reduced the bandgap of ZIF-8, thus enhancing charge transfer efficiency for chemical signal amplification. The dual electromagnetic-chemical enhancement achieved a detection range of 0.1 fg/mL–1.0 μg/mL and an ultralow detection limit of 0.057 fg/mL, thereby surpassing the detection limits of conventional methods. This innovative probe, with its high sensitivity and wide dynamic range, offers a powerful platform for mycotoxin monitoring, hence advancing SERS-based rapid detection technologies crucial for food safety.
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Polymers
·
2025
·Vol. 17
·期 12
·1716
·
IF 4.9
Lili Kong,Xinna Yu,Qifang Sun,Meizhen Huang,Tianyuan Liu,Jie Chen
Polycyclic aromatic hydrocarbons (PAHs) have attracted significant attention due to their severe threats to both ecological systems and human health. In this paper, a high-performance surface-enhanced Raman spectroscopy (SERS) substrate based on NCF/GO/Au@Ag nanocomposites was developed, which enabled sensitive and stable detection of PAHs. The NCF/GO/Au@Ag substrate synergistic utilizes the localized surface plasmon resonance (LSPR) effect of Au@Ag core–shell nanorods and the additional interfacial charge transfer provided by graphene oxide (GO) to exhibit extremely high sensitivity. And the three-dimensional fibrous network of nanocellulose (NCF) improved nanoparticle dispersion uniformity. Combined finite element simulations and experimental studies verified that the dual plasmonic resonances (512 nm and 772 nm) of Au@Ag nanorods optimally match 785 nm excitation, yielding an enhancement factor of 5.21 × 10 5 . GO integration enhanced Raman signals by 1.68-fold through interfacial charge transfer, while the introduction of NCF reduced the signal relative standard deviation (RSD) from 36.88% to 4.29%. The NCF/GO/Au@Ag substrate achieved a detection limit of 10 μg/L for PAHs, demonstrating exceptional sensitivity and reproducibility.
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JOURNAL OF ALLOYS AND COMPOUNDS
·
2025
·
IF 6.3
Caizhen Zu,Xishun Peng,Yi Long,Man Peng,Cunwei Wang,Haili Zhang,Zhangwei Tan,Yuxue He,Zhongchen Bai
Detecting antibiotic residues in food is a critical challenge for food safety assurance. This study developed a surface-enhanced Raman scattering (SERS) sensor based on two-dimensional graphitic carbon nitride (g-C 3 N 4 ) loaded with Au@Ag core-shell nanostructures (g-C 3 N 4 /Au@Ag) for detecting nitrofurantoin (NFT) residues in honey. The g-C 3 N 4 /Au@Ag thin film was fabricated by sequentially depositing g-C 3 N 4 nanosheets, Au nanoparticles, and Ag nanoparticles onto a stainless steel substrate via an electrochemical deposition method. This SERS sensor could synergistically amplify SERS signals by combining the localized surface plasmon resonance (LSPR) from the Au@Ag nanostructures with the charge transfer between the g-C 3 N 4 semiconductor and Au@Ag nanostructures. The optimized SERS sensor achieved an exceptional SERS enhancement factor of 3.8 × 10 6 for NFT in aqueous solutions, with a limit of detection (LOD) of 0.72 nM. Moreover, this SERS sensor could also recognize NFT residues in honey matrices at an LOD of 5 nM. These results provide a novel strategy for the highly sensitive detection of antibiotic residues in food safety monitoring, highlighting its potential for rapid screening of NFT residues in food.
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CHEMICAL ENGINEERING JOURNAL
·
2025
·
IF 13.2
Meng Jin,Hui Pan,Ge Gao,Mengping Zhang,Haiyan Wei,Xiao Meng,Wenwen Chen,Xinya Zhang,Ming Shang,Cuijuan Wang
Public concern regarding mixed pesticide poisoning involving chlorfenapyr has highlighted the urgent need for effective point-of-care diagnostics (POCD) to facilitate timely clinical rescue. This study presents a novel surface-enhanced Raman scattering (SERS)-based microdevice for the rapid identification and quantification of chlorfenapyr, lufenuron, and emamectin benzoate in human serum and urine for first aid scenarios. We developed a multifunctional sensor utilizing a porous cellulose ester (MCE) membrane modified with zeolitic imidazole framework-67 (ZIF-67) and gold concave rhombic dodecahedra (Au CRDs), creating an Au CRDs@ZIF-67/MCE composite that serves as both a SERS-active substrate and a sorbent. Assembled in a 24-well plate, this microdevice enhances enrichment selectivity and efficiency through a “1+1 dual-mode separation” effect, while the concave sharp tips of Au CRDs significantly boost SERS sensitivity. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.911 and 0.986, with detection limits from 0.16 ppb to 2.71 ppb, demonstrating clinical applicability. This microdevice analyzed patient bio-samples in 5 min, demonstrating both practicality and accuracy, as results closely aligned with those obtained from routine chromatography. Importantly, the detection process requires no sample preparation, underscoring its potential as a high-efficiency, user-friendly POCD assay for multi-pesticide poisoning in first aid scenarios.
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LAB ON A CHIP
·
2021
·Vol. 21
·期 20
·3888-3898
·
IF 6.799
Rongke Gao,Changbiao Zhan,Chunyu Wu,Yang Lu,Baoqiang Cao,Jing Huang,Feng Wang,Liandong Yu
Hepatocellular carcinoma (HCC) is a harmful malady that truly debilitates human health, and hence it is of significance to isolate and on-line profile the phenotype of HCC cells for further diagnosis and therapy. We developed a novel strategy for efficient capture and in situ heterogeneous phenotype analysis of circulating tumor cells (CTCs) at the single-cell level based on surface-enhanced Raman scattering (SERS) fingerprint characteristics. Herein, a new microfluidic chip with lantern-like bypass structure was designed to capture CTCs by their large size from whole blood. Furthermore, two types of SERS-aptamer nanotags were fabricated, realizing spectral recognition of single CTCs in accordance with the surface membrane protein expression. Up to 84% of CTCs with a purity of 95% were captured from whole blood samples using the present SERS-aptamer based microfluidic chip at 20 μL min−1. The results showed that the proposed strategy can successfully identify HCC cell subtypes by SERS measurements, which was related to the clinical surface biomarkers. This may open a new avenue for serving as a powerful tool of cancer diagnosis and prognosis evaluation.
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Small
·
2025
·
IF 12.1
Shuoyang Yan,Zhiyang Zhang,Jiadong Chen,Qiaoning Wang,Yanzhou Wu,Yifan Sui,Shiyu Wang,Quande Che,Na Zhou,Ling Chen,Lingxin Chen
Process analytical technology (PAT) is a key tool in the chemical and biological production industry. However, it is still desirable to develop online PAT enabling rapid and sensitive detection of various reaction intermediates, to meet the requirements of precise and green chemistry. Here these challenges are addressed by developing a cavity-like silver aggregate (Ag cavity)-based colloidal surface-enhanced Raman scattering (SERS) microfluidic platform, which exhibits a reproducible flow detection window, enabling sensitive online monitoring and identification of the organic reaction intermediates of the model flow photochemical reactions. The key element of the platform is the colloidal Ag cavity prepared through a template-mediated method. Finite difference time domain (FDTD) simulation and molecular adsorption measurements indicate the increased electromagnetic field and the high surface area contribute to the high SERS sensitivity of the cavity-like silver aggregates. Moreover, the Ag cavity shows a long-term flow detection window in the microfluidic channel with high reproducibility (RSD = 3.72%). This platform is successfully used to monitor and analyze the photodegradation intermediates of the model antibiotics, indicating the promising practical applications. This study contributes to the advancement of online chemistry studies and provides an effective tool for online reaction monitoring across diverse organic production fields.
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CHEMICAL ENGINEERING JOURNAL
·
2025
·
IF 13.2
Bohan Zhang,Jinglei Yang,Qiaojun Jiang,Ruping Zheng,Liting Qiu,Jingxin Chen,Ruiyun You,Zixing Yan,Yudong Lu
In clinical settings, there is a significant demand for the monitoring of therapeutic drugs. Surface-enhanced Raman spectroscopy (SERS) has shown considerable potential in the field of drug analysis. Designing SERS sensors with high sensitivity, strong stability, excellent reproducibility is a challenging and fascinating goal in the field of chemical measurement. In this study, a simple and portable AuNPs/C-CNF/PVA hydrogel SERS sensor was developed, composed of gold nanoparticles (AuNPs), carboxylated cellulose nanofibers (C-CNF) and polyvinyl alcohol (PVA). Due to the “screening” effect of the hydrogel network, it is capable of separating hydrophobic molecules from macromolecules and enabling the enrichment of hydrophilic small molecules. When used to analyze 6-thioguanine (6-TG) and methylene blue (MB) in plasma, the AuNPs/C-CNF/PVA hydrogel SERS sensor showed limit of detection (LOD) as low as 7.9 × 10 −8 M for 6-TG and 3.3 × 10 −9 M for MB. Based on this technology, in blood spiking experiments using clinical samples, the recovery rate for 6-TG ranged from 99.16 % to 103.51 %, while the recovery rate for MB ranged from 93.13 % to 101.70 %. Therefore, the AuNPs/C-CNF/PVA hydrogel SERS sensor enables ultra-sensitive, integrated detection of drugs in plasma through separation and enrichment, without the need for complex pretreatment steps. This approach holds great promise for application in clinical therapeutic drug monitoring.
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FOOD CHEMISTRY
·
2025
·
IF 9.8
Huiwen Liu,Limin Cao,Jianxin Sui,Hong Lin,Xiudan Wang,Kaiqiang Wang
Conventional anthocyanin-based colorimetric indicator labels can achieve qualitative differentiation of seafood freshness levels, but exhibit low responsiveness to early-stage freshness changes. Herein, a high-sensitive smart hydrogel patch with multiplexed colorimetric and surface-enhanced Raman spectroscopy (SERS) features was developed. The structural basis of anthocyanins served as a novel colorimetric and SERS dual-mode sensing unit for smart hydrogel patch was first uncovered. The colorimetric function of the patch can be used to qualitatively identify the freshness of seafoods, and the SERS function can be used to quantitatively detect the TVB-N content in seafoods. The results revealed that within a pH range of 2.0 to 12.0, the patch's color shifted from bright red to dark green, accompanied by alterations in anthocyanin's characteristic Raman peaks at 1287 cm −1 , 1320 cm −1 , and 1642 cm −1 due to structural transitions. This study provides a new method for sensitive detection of seafood freshness using a smart hydrogel patch.
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IEEE SENSORS JOURNAL
·
2025
·
IF 4.5
Zelong Li,Xuemei Lin,Zengshan Yu,Guochao Shi,Wenying Zhou,Jiahao Cui,Shan Guo,Mingli Wang
Accurate and sensitive detection of bilirubin, cholic acid, and Alanine aminotransferase (ALT) is essential for the early detection of hepatobiliary diseases in healthcare and the medical field. Integrating surface-enhanced Raman scattering (SERS) with deep learning algorithm has shown great application prospect in the early identification of markers of hepatobiliary diseases. Here, an regular Ag decorated Cu-Ag nanoisland-liked SERS biosensor (Ag@5/Ag-Cu@20/PSS) was constructed by using pattered sappire substrate as a template. An additional 5 mins of Ag nanofilm significantly improved the SERS signal intensity and homogeneity, and the sensitivity was enhanced by two orders of magnitude up to 10-10 M for 4-aminothiophenol (4-ATP). Importantly, deep learning algorithms included temporal convolutional networks (TCN), convolutional neural networks (CNN), recurrent neural network (RNN) and Transformer were used to deeply mine SERS spectral data of bilirubin, cholic acid and ALT, extract effective features, and establish an accurate classification and prediction model. Results indicating that the developed SERS biosensor combined with Transformer model demonstrated excellent accuracy (ACC) of 0.9816±0.0090 in qualitatively and quantitatively analyzing of bilirubin, cholic acid, and ALT. The successful application of the SERS biosensor will help improve the accuracy of early identification of bilirubin, cholic acid, and ALT disease markers and promote the early intervention and treatment of hepatobiliary diseases.
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