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Charge trapping devices using a bilayer oxide structure.

Moonkyung Kim1, Ravishankar Sundararaman, Sandip Tiwari

  • 1School of Electrical and Computer Engineering, Cornell University, New York 14850, USA.

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Summary

This study explores charge traps in SiO2/SiO2 structures for low-power memory. While Fowler-Nordheim tunneling shows promise, narrow memory windows and poor retention limit current applications.

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Area of Science:

  • Materials Science
  • Electrical Engineering
  • Semiconductor Device Physics

Background:

  • Exploring novel charge trapping materials for non-volatile memory is crucial for advancing low-power electronic devices.
  • Silicon dioxide (SiO2) based structures are investigated for their potential in next-generation memory technologies.

Purpose of the Study:

  • To investigate the operational characteristics of SiO2/SiO2 device structures utilizing charge traps in both the bulk and interface of deposited oxides.
  • To model the programming behavior of these charge trapping devices using Fowler-Nordheim tunneling simulations.

Main Methods:

  • Fabrication and characterization of SiO2/SiO2 device structures with 0.5 micrometer gate dimensions and 3 nm thermal oxide/7 nm deposited oxide gate stacks.
  • 1D Poisson equation solved to determine electric fields for programming voltage analysis.
  • Fowler-Nordheim tunneling simulations performed to model charge trapping and programming curves.

Main Results:

  • Achieved low power operation due to thin gate stacks.
  • Observed narrow memory windows compared to silicon-oxide-nitride-oxide-silicon (SONOS) cells, attributed to low interfacial trap density.
  • Fowler-Nordheim tunneling simulations accurately fitted programming curves.
  • Memory window stability demonstrated up to 100,000 cycles, but rapid deterioration in retention characteristics was noted.

Conclusions:

  • SiO2/SiO2 structures offer low-power operation but require optimization to enhance memory window size.
  • Interfacial engineering is critical to improve trap density and device performance.
  • While programming is well-modeled, retention limitations need further investigation for practical applications.