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Qin Y, Zhong X, Liang C, Liang Z, Nong Y, Deng L, Guo Y, Li J, Zhang M, Tang S, Wei L, Yang Y, Liang Y, Wu J, Lam YM, Su Z. Nanozyme-based colorimetric sensor arrays coupling with smartphone for discrimination and "segmentation-extraction-regression" deep learning assisted quantification of flavonoids. Biosens Bioelectron 2024; 263:116604. [PMID: 39094293 DOI: 10.1016/j.bios.2024.116604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Revised: 06/26/2024] [Accepted: 07/23/2024] [Indexed: 08/04/2024]
Abstract
Achieving rapid, cost effective, and intelligent identification and quantification of flavonoids is challenging. For fast and uncomplicated flavonoid determination, a sensing platform of smartphone-coupled colorimetric sensor arrays (electronic noses) was developed, relying on the differential competitive inhibition of hesperidin, nobiletin, and tangeretin on the oxidation reactions of nanozymes with a 3,3',5,5'-tetramethylbenzidine substrate. First, density functional theory calculations predicted the enhanced peroxidase-like activities of CeO2 nanozymes after doping with Mn, Co, and Fe, which was then confirmed by experiments. The self-designed mobile application, Quick Viewer, enabled a rapid evaluation of the red, green, and blue values of colorimetric images using a multi-hole parallel acquisition strategy. The sensor array based on three channels of CeMn, CeFe, and CeCo was able to discriminate between different flavonoids from various categories, concentrations, mixtures, and the various storage durations of flavonoid-rich Citri Reticulatae Pericarpium through a linear discriminant analysis. Furthermore, the integration of a "segmentation-extraction-regression" deep learning algorithm enabled single-hole images to be obtained by segmenting from a 3 × 4 sensing array to augment the featured information of array images. The MobileNetV3-small neural network was trained on 37,488 single-well images and achieved an excellent predictive capability for flavonoid concentrations (R2 = 0.97). Finally, MobileNetV3-small was integrated into a smartphone as an application (Intelligent Analysis Master), to achieve the one-click output of three concentrations. This study developed an innovative approach for the qualitative and simultaneous multi-ingredient quantitative analysis of flavonoids.
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Affiliation(s)
- Yuelian Qin
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Xinyu Zhong
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Caihong Liang
- School of Materials Science and Engineering, Nanyang Technological University, 639798, Singapore
| | - Zhenwu Liang
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Yunyuan Nong
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Lijun Deng
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Yue Guo
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Jinfeng Li
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Meiling Zhang
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Siqi Tang
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Liuyan Wei
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Ying Yang
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Yonghong Liang
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China
| | - Jinxia Wu
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China.
| | - Yeng Ming Lam
- School of Materials Science and Engineering, Nanyang Technological University, 639798, Singapore; Facility for Analysis, Characterisation, Testing and Simulation (FACTS), Nanyang Technological University, 639798, Singapore.
| | - Zhiheng Su
- Pharmaceutical College, Guangxi Medical University, Nanning, 530021, China; Guangxi Key Laboratory of Bioactive Molecules Research and Evaluation, Nanning, 530021, China; Guangxi Beibu Gulf Marine Biomedicine Precision Development and High-value Utilization Engineering Research Center, Nanning, 530021, China; Guangxi Health Commission Key Laboratory of Basic Research on Antigeriatric Drugs, Nanning, 530021, China.
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Wang H, Yao R, Zhang R, Ma H, Gao J, Liang M, Zhao Y, Miao Z. CeO 2-Supported TiO 2-Pt Nanorod Composites as Efficient Catalysts for CO Oxidation. Molecules 2023; 28:1867. [PMID: 36838854 PMCID: PMC9959209 DOI: 10.3390/molecules28041867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/04/2023] [Accepted: 02/09/2023] [Indexed: 02/18/2023] Open
Abstract
Supported Pt-based catalysts have been identified as highly selective catalysts for CO oxidation, but their potential for applications has been hampered by the high cost and scarcity of Pt metals as well as aggregation problems at relatively high temperatures. In this work, nanorod structured (TiO2-Pt)/CeO2 catalysts with the addition of 0.3 at% Pt and different atomic ratios of Ti were prepared through a combined dealloying and calcination method. XRD, XPS, SEM, TEM, and STEM measurements were used to confirm the phase composition, surface morphology, and structure of synthesized samples. After calcination treatment, Pt nanoparticles were semi-inlayed on the surface of the CeO2 nanorod, and TiO2 was highly dispersed into the catalyst system, resulting in the formation of (TiO2-Pt)/CeO2 with high specific surface area and large pore volume. The unique structure can provide more reaction path and active sites for catalytic CO oxidation, thus contributing to the generation of catalysts with high catalytic activity. The outstanding catalytic performance is ascribed to the stable structure and proper TiO2 doping as well as the combined effect of Pt, TiO2, and CeO2. The research results are of importance for further development of high catalytic performance nanoporous catalytic materials.
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Affiliation(s)
- Haiyang Wang
- Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi’an 710123, China
| | - Ruijuan Yao
- Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi’an 710123, China
| | - Ruiyin Zhang
- Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi’an 710123, China
| | - Hao Ma
- Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi’an 710123, China
| | - Jianjing Gao
- Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi’an 710123, China
| | - Miaomiao Liang
- School of Materials Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, China
| | - Yuzhen Zhao
- Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi’an 710123, China
| | - Zongcheng Miao
- Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi’an 710123, China
- School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an 710072, China
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Camposeco R, Hinojosa-Reyes M, Castillo S, Nava N, Zanella R. Synthesis and characterization of highly dispersed bimetallic Au-Rh nanoparticles supported on titanate nanotubes for CO oxidation reaction at low temperature. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:10734-10748. [PMID: 33099755 DOI: 10.1007/s11356-020-11341-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 10/20/2020] [Indexed: 06/11/2023]
Abstract
Low-temperature CO oxidation was carried out by using rhodium incorporated into titanate nanotubes (Rh/NTs) prepared by the sol-gel and hydrothermal methods; otherwise, gold nanoparticles were deposited homogeneously onto the Rh/NT surface through the deposition-precipitation with urea (DPU) method. The Au-Rh/NT sample exhibited high metal dispersion (55%), outstanding CO oxidation at low temperature, and better resistance to deactivation than the monometallic Rh/NT and Au/NT samples. The characterization of bimetallic samples, with particle sizes from 1 to 3 nm, revealed the remarkable presence of interacting Au and Rh species in metallic state. In this way, Au0 and Rh0 were answerable for the higher catalytic activity observed in the bimetallic samples. The interaction between Au and Rh in the nanoparticles of Au-Rh/NT promoted a synergistic effect on the CO oxidation reaction, explained by the creation of new CO adsorption sites.
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Affiliation(s)
- Roberto Camposeco
- Instituto de Ciencias Aplicadas y Tecnología, ICAT, Universidad Nacional Autónoma de México, UNAM, Circuito Exterior S/N, Ciudad Universitaria, 04510, Mexico City, Mexico
| | - Mariana Hinojosa-Reyes
- Faculty of Sciences, Autonomous University of San Luis Potosí, SLP, 78000, San Luis Potosí, Mexico
| | - Salvador Castillo
- Product Technology, Mexican Institute of Petroleum, 07730, Mexico City, Mexico
- Department of Chemical Engineering, ESIQIE-IPN, 75876, Mexico City, Mexico
| | - Noel Nava
- Product Technology, Mexican Institute of Petroleum, 07730, Mexico City, Mexico
| | - Rodolfo Zanella
- Instituto de Ciencias Aplicadas y Tecnología, ICAT, Universidad Nacional Autónoma de México, UNAM, Circuito Exterior S/N, Ciudad Universitaria, 04510, Mexico City, Mexico.
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