Skip to main content
padlock icon - secure page this page is secure

Investigation on the Charge Loss Mechanisms of Nanoscale Charge Trap Non-Volatile Memory by Using Stretched Exponential Function

Buy Article:

$106.67 + tax (Refund Policy)

Charge loss mechanisms of nanoscale charge trap non-volatile memory devices are carefully examined and studied. Fowler-Nordheim tunnelling mechanism is used to perform rapid program/erase cycling. Based on the good fit of post cycled and baked threshold voltage data to Stretched Exponential function, the lowest point and the peak of Vt distribution were found to evolve in a similar manner that resulted to similar derived E a. The saturation behaviour of the threshold voltage decay can be predicted and validated through cells’ threshold voltage measurements that fit well to Stretched Exponential function. The power law relationship of program/erase cycle count and the saturation behaviour was found to be similar on the device under study and NROM devices that utilizes significant different charge injection mechanisms for program/erase operation. The experimental results also demonstrated that charge injection mechanism is one of the dominant factors in determining the underlying charge loss mechanism. Moreover, the determination of charge loss mechanism depends on the total charges injected through the tunnel oxide layer of ONO stack in NB-CTNVM cell. Physical interpretation of the experimental findings of the dominant charge loss mechanism is deliberated in detail.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Publication date: January 1, 2016

More about this publication?
  • Journal for Nanoscience and Nanotechnology (JNN) is an international and multidisciplinary peer-reviewed journal with a wide-ranging coverage, consolidating research activities in all areas of nanoscience and nanotechnology into a single and unique reference source. JNN is the first cross-disciplinary journal to publish original full research articles, rapid communications of important new scientific and technological findings, timely state-of-the-art reviews with author's photo and short biography, and current research news encompassing the fundamental and applied research in all disciplines of science, engineering and medicine.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more