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  1. Article ; Online: Sandwich-like CuNPs@AgNPs@PSB SERS substrates for sensitive detection of R6G and Forchlorfenuron.

    Han, Shibin / Chen, Cheng / Chen, Chen / Wang, Jiajia / Zhao, Xin / Wang, Xuehua / Lv, Xiaoyi / Jia, Zhenhong / Hou, Junwei

    Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

    2024  Volume 314, Page(s) 124178

    Abstract: The development of a highly sensitive, synthetically simple and economical SERS substrate is technically very important. A fast, economical, sensitive and reproducible CuNPs@AgNPs@ Porous silicon Bragg reflector (PSB) SERS substrate was prepared by ... ...

    Abstract The development of a highly sensitive, synthetically simple and economical SERS substrate is technically very important. A fast, economical, sensitive and reproducible CuNPs@AgNPs@ Porous silicon Bragg reflector (PSB) SERS substrate was prepared by electrochemical etching and in situ reduction method. The developed CuNPs@AgNPs@PSB has a large specific surface area and abundant "hot spot" region, which makes the SERS performance excellent. Meanwhile, the successful synthesis of CuNPs@AgNPs can not only modulate the plasmon resonance properties of nanoparticles, but also effectively prolong the time stability of Cu nanoparticles. The basic performance of the substrate was evaluated using rhodamine 6G (R6G). (Detection limit reached 10
    MeSH term(s) Metal Nanoparticles/chemistry ; Spectrum Analysis, Raman/methods ; Silver/chemistry ; Phenylurea Compounds ; Pyridines ; Rhodamines
    Chemical Substances rhodamine 6G (037VRW83CF) ; N-(2-chloro-4-pyridyl)-N'-phenylurea (K62IP7463J) ; Silver (3M4G523W1G) ; Phenylurea Compounds ; Pyridines ; Rhodamines
    Language English
    Publishing date 2024-03-27
    Publishing country England
    Document type Journal Article
    ZDB-ID 210413-1
    ISSN 1873-3557 ; 0370-8322 ; 0584-8539 ; 1386-1425
    ISSN (online) 1873-3557
    ISSN 0370-8322 ; 0584-8539 ; 1386-1425
    DOI 10.1016/j.saa.2024.124178
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  2. Article ; Online: Application of serum SERS technology combined with deep learning algorithm in the rapid diagnosis of immune diseases and chronic kidney disease.

    Yang, Jie / Chen, Xiaomei / Luo, Cainan / Li, Zhengfang / Chen, Chen / Han, Shibin / Lv, Xiaoyi / Wu, Lijun / Chen, Cheng

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 15719

    Abstract: Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic detection technique, has promising applications in disease screening and diagnosis. In this paper, an annealed silver nanoparticles/porous silicon Bragg ... ...

    Abstract Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic detection technique, has promising applications in disease screening and diagnosis. In this paper, an annealed silver nanoparticles/porous silicon Bragg reflector (AgNPs/PSB) composite SERS substrate with high sensitivity and strong stability was prepared by immersion plating and heat treatment using porous silicon Bragg reflector (PSB) as the substrate. The substrate combines the five deep learning algorithms of the improved AlexNet, ResNet, SqueezeNet, temporal convolutional network (TCN) and multiscale fusion convolutional neural network (MCNN). We constructed rapid screening models for patients with primary Sjögren's syndrome (pSS) and healthy controls (HC), diabetic nephropathy patients (DN) and healthy controls (HC), respectively. The results showed that the annealed AgNPs/PSB composite SERS substrates performed well in diagnosing. Among them, the MCNN model had the best classification effect in the two groups of experiments, with an accuracy rate of 94.7% and 92.0%, respectively. Previous studies have indicated that the AgNPs/PSB composite SERS substrate, combined with machine learning algorithms, has achieved promising classification results in disease diagnosis. This study shows that SERS technology based on annealed AgNPs/PSB composite substrate combined with deep learning algorithm has a greater developmental prospect and research value in the early identification and screening of immune diseases and chronic kidney disease, providing reference ideas for non-invasive and rapid clinical medical diagnosis of patients.
    MeSH term(s) Humans ; Deep Learning ; Metal Nanoparticles ; Silicon ; Silver ; Algorithms ; Spectrum Analysis, Raman ; Immune System Diseases ; Renal Insufficiency, Chronic/diagnosis
    Chemical Substances Silicon (Z4152N8IUI) ; Silver (3M4G523W1G)
    Language English
    Publishing date 2023-09-21
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-42719-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Novel SERS biosensor for rapid detection of breast cancer based on Ag

    Wang, Xuehua / Chen, Cheng / Chen, Chen / Zuo, Enguang / Han, Shibin / Yang, Jie / Yan, Ziwei / Lv, Xiaoyi / Hou, Junwei / Jia, Zhenhong

    Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

    2023  Volume 303, Page(s) 123226

    Abstract: ... ...

    Abstract Ag
    MeSH term(s) Humans ; Female ; Breast Neoplasms/diagnosis ; Metal Nanoparticles ; Silicon ; Silver ; Spectrum Analysis, Raman/methods ; Biosensing Techniques
    Chemical Substances Silicon (Z4152N8IUI) ; Silver (3M4G523W1G)
    Language English
    Publishing date 2023-08-02
    Publishing country England
    Document type Journal Article
    ZDB-ID 210413-1
    ISSN 1873-3557 ; 0370-8322 ; 0584-8539 ; 1386-1425
    ISSN (online) 1873-3557
    ISSN 0370-8322 ; 0584-8539 ; 1386-1425
    DOI 10.1016/j.saa.2023.123226
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Bonn / Germany

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  4. Article ; Online: Coupling annealed silver nanoparticles with a porous silicon Bragg mirror SERS substrate and machine learning for rapid non-invasive disease diagnosis.

    Han, Shibin / Chen, Cheng / Chen, Chen / Wu, Lijun / Wu, Xue / Lu, Chen / Zhang, Xueqin / Chao, Peng / Lv, Xiaoyi / Jia, Zhenhong / Hou, Junwei

    Analytica chimica acta

    2023  Volume 1254, Page(s) 341116

    Abstract: ... ...

    Abstract Ag
    MeSH term(s) Humans ; Silicon ; Spectrum Analysis, Raman/methods ; Metal Nanoparticles ; Silver ; Porosity
    Chemical Substances Silicon (Z4152N8IUI) ; Silver (3M4G523W1G)
    Language English
    Publishing date 2023-03-17
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1483436-4
    ISSN 1873-4324 ; 0003-2670
    ISSN (online) 1873-4324
    ISSN 0003-2670
    DOI 10.1016/j.aca.2023.341116
    Database MEDical Literature Analysis and Retrieval System OnLINE

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