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High-Responsivity Multilayer MoSe2 Phototransistors with Fast Response Time.
Lee, Hyejoo; Ahn, Jongtae; Im, Seongil; Kim, Jiyoung; Choi, Woong.
  • Lee H; School of Materials Science & Engineering, Kookmin University, Seoul, 02707, South Korea.
  • Ahn J; Institute of Physics and Applied Physics, Yonsei University, Seoul, 03722, South Korea.
  • Im S; Institute of Physics and Applied Physics, Yonsei University, Seoul, 03722, South Korea.
  • Kim J; Department of Materials Science & Engineering, University of Texas at Dallas, Richardson, Texas, 75080, USA.
  • Choi W; School of Materials Science & Engineering, Kookmin University, Seoul, 02707, South Korea. woongchoi@kookmin.ac.kr.
Sci Rep ; 8(1): 11545, 2018 Aug 01.
Article en En | MEDLINE | ID: mdl-30069033
ABSTRACT
There is a great interest in phototransistors based on transition metal dichalcogenides because of their interesting optoelectronic properties. However, most emphasis has been put on MoS2 and little attention has been given to MoSe2, which has higher optical absorbance. Here, we present a compelling case for multilayer MoSe2 phototransistors fabricated in a bottom-gate thin-film transistor configuration on SiO2/Si substrates. Under 650-nm-laser, our MoSe2 phototransistor exhibited the best performance among MoSe2 phototransistors in literature, including the highest responsivity (1.4 × 105 AW-1), the highest specific detectivity (5.5 × 1013 jones), and the fastest response time (1.7 ms). We also present a qualitative model to describe the device operation based on the combination of photoconductive and photogating effects. These results demonstrate the feasibility of achieving high performance in multilayer MoSe2 phototransistors, suggesting the possibility of further enhancement in the performance of MoSe2 phototransistors with proper device engineering.

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Qualitative_research Idioma: En Año: 2018 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Qualitative_research Idioma: En Año: 2018 Tipo del documento: Article