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An Ultrafast Multibit Memory Based on the ReS2/h-BN/Graphene Heterostructure.
Lu, Haoyue; Wang, Yan; Han, Xuchen; Liu, Jing.
Afiliación
  • Lu H; State Key Laboratory of Precision Measurement Technology and Instrument, School of Precision Instruments and Optoelectronics Engineering, Tianjin University, No. 92 Weijin Road, Tianjin 300072, China.
  • Wang Y; State Key Laboratory of Precision Measurement Technology and Instrument, School of Precision Instruments and Optoelectronics Engineering, Tianjin University, No. 92 Weijin Road, Tianjin 300072, China.
  • Han X; State Key Laboratory of Precision Measurement Technology and Instrument, School of Precision Instruments and Optoelectronics Engineering, Tianjin University, No. 92 Weijin Road, Tianjin 300072, China.
  • Liu J; State Key Laboratory of Precision Measurement Technology and Instrument, School of Precision Instruments and Optoelectronics Engineering, Tianjin University, No. 92 Weijin Road, Tianjin 300072, China.
ACS Nano ; 18(34): 23403-23411, 2024 Aug 27.
Article en En | MEDLINE | ID: mdl-39088760
ABSTRACT
The exponential growth of data in the big data era has made it imperative to improve the data storage density and calculation speed. Therefore, the development of a multibit memory with an ultrafast operational speed is of great significance. In this work, a floating-gate (FG) memory based on the ReS2/h-BN/graphene van der Waals heterostructure is reported. The device exhibits ultrafast and multilevel nonvolatile memory characteristics, notably featuring an exceptionally large memory window of 113.36 V, a substantial erasing/programming current ratio of 107, an ultrafast operational speed of 30 ns, outstanding endurance exceeding 1000 cycles, and retention performance exceeding 1100 s. Furthermore, the device exhibits both electrically and optically tunable multilevel nonvolatile memory behavior. By controlling the voltage and light pulse parameters, the device achieves an electrical memory state of 130 levels (>7 bits) and an optical memory state of 45 levels (>5 bits).
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: ACS Nano Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: ACS Nano Año: 2024 Tipo del documento: Article