Literature DB >> 28156092

Highly Reproducible Au-Decorated ZnO Nanorod Array on a Graphite Sensor for Classification of Human Aqueous Humors.

Wansun Kim1, Soo Hyun Lee2, Sang Hun Kim2, Jae-Chul Lee3, Sang Woong Moon4, Jae Su Yu2, Samjin Choi1,3.   

Abstract

Gold-decorated, vertically grown ZnO nanorods (NRs) on a flexible graphite sheet (Au/ZnONRs/G) were developed for surface-enhanced Raman scattering (SERS)-based biosensing to identify trace amounts of human aqueous humors. This Au/ZnONRs/G SERS-functionalized sensor was fabricated via two steps: hydrothermal synthesis-induced growth of ZnO NRs on graphite sheets for nanostructure fabrication, followed by e-beam evaporator-induced gold metallization on ZnONRs/G for SERS functionalization. The thickness of the Au layer and the height of the ZnO NRs for enhancing SERS performance were adjusted to maximize Raman intensity, and the optimized Au/ZnONRs/G nanostructures were verified by the electric finite element computational models to maximize the electric fields. The proposed Au/ZnONRs/G SERS sensor showed an enhancement factor of 2.3 × 106 via rhodamine 6G Raman probe and excellent reproducibility (relative standard deviation of <10%) via Raman mapping of a SERS active area with a square of 100 × 100 μm2. To evaluate the actual bioapplicability of point-of-care-testing (POCT) analysis in clinics, SERS data acquisition was performed with an integration time of 1 s from a 1 μL analytic droplet of the sample. The performance of this Au/ZnONRs/G sensor was evaluated using human aqueous humors with cataract and two oxidative stress-induced eye diseases, age-related macular degeneration, and diabetic macular edema. These three eye diseases could be identified without any labeling or modification using the Au/ZnONRs/G SERS sensor and the computational algorithm incorporating a support vector machine and multivariate statistical prediction. Therefore, these findings indicate that our label-free, highly reproducible and flexible Au/ZnONRs/G SERS-functionalized sensor supported by a multivariate statistics-derived bioclassification method has great potential in POCT applications for identifying eye diseases.

Entities:  

Keywords:  ZnO nanorod; aqueous humor; finite element method (FEM) computation; graphite sheet; surface-enhanced Raman scattering (SERS)

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Year:  2017        PMID: 28156092     DOI: 10.1021/acsami.6b16130

Source DB:  PubMed          Journal:  ACS Appl Mater Interfaces        ISSN: 1944-8244            Impact factor:   9.229


  3 in total

1.  Diagnosis in a Preclinical Model of Bladder Pain Syndrome Using a Au/ZnO Nanorod-based SERS Substrate.

Authors:  Sanghwa Lee; Jung-Man Namgoong; Hwan Yeul Yu; Miyeon Jue; Gwanho Kim; Sangmin Jeon; Dong-Myung Shin; Myung-Soo Choo; Jinmyoung Joo; Chan-Gi Pack; Jun Ki Kim
Journal:  Nanomaterials (Basel)       Date:  2019-02-07       Impact factor: 5.076

2.  Fabrication and Characterization of High-Quality UV Photodetectors Based ZnO Nanorods Using Traditional and Modified Chemical Bath Deposition Methods.

Authors:  Ahmed Fattah Abdulrahman; Sabah Mohammed Ahmed; Azeez Abdullah Barzinjy; Samir Mustafa Hamad; Naser Mahmoud Ahmed; Munirah Abullah Almessiere
Journal:  Nanomaterials (Basel)       Date:  2021-03-09       Impact factor: 5.076

3.  Hydrogel-Assisted 3D Volumetric Hotspot for Sensitive Detection by Surface-Enhanced Raman Spectroscopy.

Authors:  Soo Hyun Lee; Sunho Kim; Jun-Yeong Yang; ChaeWon Mun; Seunghun Lee; Shin-Hyun Kim; Sung-Gyu Park
Journal:  Int J Mol Sci       Date:  2022-01-17       Impact factor: 5.923

  3 in total

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