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Optical thickness identification of transition metal dichalcogenide nanosheets on transparent substrates.
Zhang, Hao; Ran, Feirong; Shi, Xiaotong; Fang, Xiangru; Wu, Shiyu; Liu, Yue; Zheng, Xianqiang; Yang, Peng; Liu, Yang; Wang, Lin; Huang, Xiao; Li, Hai; Huang, Wei.
Afiliación
  • Zhang H; Key Laboratory of Flexible Electronics (KLOFE) & Institute of Advanced Materials (IAM), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211816, People's Republic of China.
Nanotechnology ; 28(16): 164001, 2017 Apr 21.
Article en En | MEDLINE | ID: mdl-28327463
Transparent and flexible devices based on two-dimensional (2D) materials hold great potential for many electronic/optoelectronic applications. The direct and fast thickness identification of 2D materials on transparent substrates is therefore an essential step in such applications, but remains challenging. Here, we present a simple, rapid and reliable optical method to identify the thickness of 2D nanosheets on transparent substrates, such as polydimethylsiloxane, glass, and coverslip. Under reflection and transmission light, 1-20L MoS2 and 1-14L WSe2 nanosheets can be reliably identified by measuring the optical contrast difference between the 2D nanosheets and substrates in color, red, green or blue channels. Meanwhile, the values of all the measured contrast differences as a function of layer number can be well fitted with the Boltzmann function, indicating the generalizability and reliability of our optical method. Our method will not only facilitate the fundamental study of the thickness-dependent properties of 2D nanosheets, but will also expand their potential applications in the field of flexible/transparent electronics and optoelectronics.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Nanotechnology Año: 2017 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Nanotechnology Año: 2017 Tipo del documento: Article