DocumentCode
1133709
Title
Statistical Metrology of Metal Nanocrystal Memories With 3-D Finite-Element Analysis
Author
Shaw, Jonathan ; Hou, Tuo-Hung ; Raza, Hassan ; Kan, Edwin Chihchuan
Author_Institution
Sch. of Electr. & Comput. Eng., Cornell Univ., Ithaca, NY, USA
Volume
56
Issue
8
fYear
2009
Firstpage
1729
Lastpage
1735
Abstract
We study the parametrical yield of memory windows for the metal nanocrystal (NC) Flash memories with consideration of the 3-D electrostatics and channel percolation effects. Monte Carlo parametrical variation that accounts for the number and size fluctuations in NCs as well as channel length is used to determine the threshold voltage distribution and bit error rate for gate length scaling to 20 nm. Devices with nanowire-based channels are compared with planar devices having the same gate stack structure. Scalability prediction by 1-D analysis is found to be very different from 3-D modeling due to underestimation of effective NC coverage and failure to consider the 3-D nature of the channel percolation effect.
Keywords
Monte Carlo methods; electrostatics; estimation theory; flash memories; nanostructured materials; nanowires; percolation; statistical analysis; 3-D electrostatics; 3-D finite-element analysis; Monte Carlo parametrical variation; bit error rate; channel length; channel percolation effects; gate length scaling; gate stack structure; memory windows; metal nanocrystal flash memories; nanowire-based channels; statistical metrology; threshold voltage distribution; Bit error rate; Electrostatics; Finite element methods; Flash memory; Fluctuations; Metrology; Monte Carlo methods; Nanocrystals; Nanoscale devices; Threshold voltage; 3-D electrostatics; Nanocrystal (NC); nonvolatile memories; programming window distribution;
fLanguage
English
Journal_Title
Electron Devices, IEEE Transactions on
Publisher
ieee
ISSN
0018-9383
Type
jour
DOI
10.1109/TED.2009.2024108
Filename
5164934
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