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Optical and Material Characteristics of MoS(2)/Cu(2)O Sensor for Detection of Lung Cancer Cell Types in Hydroplegia
In this study, n-type MoS(2) monolayer flakes are grown through chemical vapor deposition (CVD), and a p-type Cu(2)O thin film is grown via electrochemical deposition. The crystal structure of the grown MoS(2) flakes is analyzed through transmission electron microscopy. The monolayer structure of th...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101548/ https://www.ncbi.nlm.nih.gov/pubmed/35563136 http://dx.doi.org/10.3390/ijms23094745 |
Sumario: | In this study, n-type MoS(2) monolayer flakes are grown through chemical vapor deposition (CVD), and a p-type Cu(2)O thin film is grown via electrochemical deposition. The crystal structure of the grown MoS(2) flakes is analyzed through transmission electron microscopy. The monolayer structure of the MoS(2) flakes is verified with Raman spectroscopy, multiphoton excitation microscopy, atomic force microscopy, and photoluminescence (PL) measurements. After the preliminary processing of the grown MoS(2) flakes, the sample is then transferred onto a Cu(2)O thin film to complete a p-n heterogeneous structure. Data are confirmed via scanning electron microscopy, SHG, and Raman mapping measurements. The luminous energy gap between the two materials is examined through PL measurements. Results reveal that the thickness of the single-layer MoS(2) film is 0.7 nm. PL mapping shows a micro signal generated at the 627 nm wavelength, which belongs to the B2 excitons of MoS(2) and tends to increase gradually when it approaches 670 nm. Finally, the biosensor is used to detect lung cancer cell types in hydroplegia significantly reducing the current busy procedures and longer waiting time for detection. The results suggest that the fabricated sensor is highly sensitive to the change in the photocurrent with the number of each cell, the linear regression of the three cell types is as high as 99%. By measuring the slope of the photocurrent, we can identify the type of cells and the number of cells. |
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