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Ye Q, Wu M, Xu Q, Zeng S, Jiang T, Xiong W, Fu S, Birowosuto MD, Gu C. Porous carbon film/WO 3-x nanosheets based SERS substrate combined with deep learning technique for molecule detection. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 310:123962. [PMID: 38309005 DOI: 10.1016/j.saa.2024.123962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/21/2024] [Accepted: 01/22/2024] [Indexed: 02/05/2024]
Abstract
The Surface-enhanced Raman scattering (SERS) is an attractive optical detecting method with high sensitivity and detectivity, however challenges on large-area signal uniformity and complex spectra analysis methods always retards its wide application. Herein, a highly sensitive and uniform SERS detection strategy supported by porous carbon film/WO3-x nanosheets (PorC/WO3-x) based noble-metal-free SERS substrate and deep learning algorithm are reported. Experimentally, the PorC/WO3-x substrate was prepared by high-temperature annealing the PorC/WO3 films under the argon atmosphere. The defect density of the WO3 was controlled by tuning the reducing reaction time during the annealing process. The SERS performance was evaluated by using R6G as the Raman reporter, it showed that the SERS intensity obtained on the substrate with the optimal annealing time of 3 h was about 8 times as high as that obtained on the PorC/WO3 substrate without annealing treatment. And detection limit of 10-7 M and Raman enhancement factor of 106 could be achieved. Moreover, the above optimal SERS substrate was utilized to detect flavonoids of quercetin, 3-hydroxyflavone and flavone, and a deep learning algorithms was incorporated to identify the quercetin. It revealed that quercetin can be accurately detected within the above flavonoids, and lowest detectable concentration of 10-5 M can be achieved.
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Affiliation(s)
- Qinli Ye
- The Research Institute of Advanced Technology, Ningbo University, Ningbo 315211, Zhejiang, China
| | - Miaomiao Wu
- The Research Institute of Advanced Technology, Ningbo University, Ningbo 315211, Zhejiang, China; Ningbo Institute of Oceanography, Ningbo 315800, China
| | - Qian Xu
- Department of Nursing, The First Hospital of Ningbo University, Ningbo 315010, Zhejiang, China
| | - Shuwen Zeng
- Light, Nanomaterials & Nanotechnologies (L2n), CNRS-UMR 7004, Université de Technologie de Troyes, 10000 Troyes, France
| | - Tao Jiang
- The Research Institute of Advanced Technology, Ningbo University, Ningbo 315211, Zhejiang, China
| | - Wei Xiong
- The Research Institute of Advanced Technology, Ningbo University, Ningbo 315211, Zhejiang, China
| | - Songyin Fu
- The Research Institute of Advanced Technology, Ningbo University, Ningbo 315211, Zhejiang, China.
| | - Muhammad Danang Birowosuto
- Łukasiewicz Research Network-PORT Polish Center for Technology Development, Stabłowicka 147, 54-066 Wrocław, Poland
| | - Chenjie Gu
- The Research Institute of Advanced Technology, Ningbo University, Ningbo 315211, Zhejiang, China; Ningbo Institute of Oceanography, Ningbo 315800, China; Department of Nursing, The First Hospital of Ningbo University, Ningbo 315010, Zhejiang, China.
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Li P, Gao J, Shi J, Wang H, Xing X, Ren J, Meng Y, Wang L, Lv B. Insights into the effect of oxygen vacancies on the epoxidation of 1-hexene with hydrogen peroxide over WO 3−x/SBA-15. Catal Sci Technol 2022. [DOI: 10.1039/d2cy01123a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The introduction of oxygen vacancies improved 1-hexene epoxidation performance over WO3−x/SBA-15 catalysts, which is attributed to the enhanced Lewis acidity of the active centers and the reduced energy barrier of the rate-determining step.
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Affiliation(s)
- Penghui Li
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Junhua Gao
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
| | - Jing Shi
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huixiang Wang
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- School of Chemistry and Materials Science, Shanxi Normal University, Taiyuan 030031, China
| | - Xiangying Xing
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingzhao Ren
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yu Meng
- Shaanxi Key Laboratory of Low Metamorphic Coal Clean Utilization, School of Chemistry and Chemical Engineering, Yulin University, Yulin 719000, China
| | - Liancheng Wang
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
| | - Baoliang Lv
- State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
- School of Chemistry and Materials Science, Shanxi Normal University, Taiyuan 030031, China
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