Impact of statistical variability and 3D electrostatics on post-cycling anomalous charge loss in nanoscale Flash memories

This paper presents a detailed simulation investigation of the impact of statistical variability and 3D electrostatics on SILC distribution in nanoscale Flash memories. Considering a 1-TAT model we study the SILC statistics under stationary and dynamic retention conditions. Our results show that SILC is dispersed over the channel area due to non-uniform electrostatics in nanoscale devices. Further, the floating gate poly-silicon granularity plays a major role in determining the SILC distribution, depending on the gate polarity. Dynamic charge loss simulations highlight that the impact of 3D electrostatics is dominant over the cell-to-cell variability. Finally, we analyze the electron emission statistics on a single cell, showing that this gives rise to a lower SILC dispersion than an analytical Poisson charge loss statistics. Our results are fundamental to determine the degree of accuracy of 1D models for the post-cycling charge loss statistics simulation in nanoscale Flash memories.

[1]  A. Asenov,et al.  Impact of random dopant fluctuations on trap-assisted tunnelling in nanoscale MOSFETs , 2012, Microelectron. Reliab..

[2]  R. Degraeve,et al.  Analytical percolation model for predicting anomalous charge loss in flash memories , 2004, IEEE Transactions on Electron Devices.

[3]  Paolo Fantini,et al.  Impact of Neutral Threshold-Voltage Spread and Electron-Emission Statistics on Data Retention of Nanoscale nand Flash , 2010, IEEE Electron Device Letters.

[4]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[5]  Melvin Lax,et al.  Cascade Capture of Electrons in Solids , 1960 .

[6]  L. Larcher,et al.  Statistical simulations to inspect and predict data retention and program disturbs in flash memories , 2003, IEEE International Electron Devices Meeting 2003.

[7]  A. Brand,et al.  Novel read disturb failure mechanism induced by FLASH cycling , 1993, 31st Annual Proceedings Reliability Physics 1993.

[8]  S. Sugawa,et al.  Statistical evaluation for anomalous SILC of tunnel oxide using integrated array TEG , 2008, 2008 IEEE International Reliability Physics Symposium.

[9]  G. Molas,et al.  Investigation of the role of H-related defects in Al2O3 blocking layer on charge-trap memory retention by atomistic simulations and device physical modelling , 2010, 2010 International Electron Devices Meeting.

[10]  Amy Hsiu-Fen Chou,et al.  Flash Memories , 2000, The VLSI Handbook.

[11]  P.K. Ko,et al.  Random telegraph noise of deep-submicrometer MOSFETs , 1990, IEEE Electron Device Letters.

[12]  L. Larcher,et al.  Monte-Carlo Simulations of Flash Memory Array Retention , 2007, 2007 International Symposium on VLSI Technology, Systems and Applications (VLSI-TSA).

[13]  D. Ielmini Reliability issues and modeling of Flash and post-Flash memory (Invited Paper) , 2009 .

[14]  D. Baglee,et al.  The effects of write/erase cycling on data loss in EEPROMs , 1985, 1985 International Electron Devices Meeting.

[15]  A. Ghetti,et al.  Impact of atomistic doping and 3D electrostatics on the variability of RTN time constants in flash memories , 2011, 2011 International Electron Devices Meeting.

[16]  A. De Keersgieter,et al.  Highly Scaled Vertical Cylindrical SONOS Cell With Bilayer Polysilicon Channel for 3-D nand Flash Memory , 2011, IEEE Electron Device Letters.

[17]  M. Nelhiebel,et al.  Switching oxide traps as the missing link between negative bias temperature instability and random telegraph noise , 2009, 2009 IEEE International Electron Devices Meeting (IEDM).

[18]  J. A. López-Villanueva,et al.  Quantum two-dimensional calculation of time constants of random telegraph signals in metal-oxide-semiconductor structures , 1997 .

[19]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[20]  A. Asenov,et al.  Comparative Simulation Study of the Different Sources of Statistical Variability in Contemporary Floating-Gate Nonvolatile Memory , 2011, IEEE Transactions on Electron Devices.

[21]  A. Ghetti,et al.  3D Monte Carlo simulation of the programming dynamics and their statistical variability in nanoscale charge-trap memories , 2010, 2010 International Electron Devices Meeting.

[22]  Luca Larcher,et al.  High-kappa related reliability issues in advanced non-volatile memories , 2010, Microelectron. Reliab..

[24]  Christian Monzio Compagnoni,et al.  Three-Dimensional Simulation of Charge-Trap Memory Programming—Part I: Average Behavior , 2011, IEEE Transactions on Electron Devices.

[25]  Daniele Ielmini,et al.  A new conduction mechanism for the anomalous cells in thin oxide flash EEPROMs , 2001, 2001 IEEE International Reliability Physics Symposium Proceedings. 39th Annual (Cat. No.00CH37167).

[26]  P.P. Ankolekar,et al.  Multibit Error-Correction Methods for Latency-Constrained Flash Memory Systems , 2008, IEEE Transactions on Device and Materials Reliability.

[27]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[28]  Andrea L. Lacaita,et al.  Reliability constraints for TANOS memories due to alumina trapping and leakage , 2010, 2010 IEEE International Reliability Physics Symposium.

[29]  M.J. van Duuren,et al.  A new statistical model to extract the stress induced oxide trap number and the probability density distribution of the gate current produced by a single trap , 2003, IEEE International Electron Devices Meeting 2003.

[30]  R. E. Shiner,et al.  A new reliability model for post-cycling charge retention of flash memories , 2002, 2002 IEEE International Reliability Physics Symposium. Proceedings. 40th Annual (Cat. No.02CH37320).

[31]  Andrea L. Lacaita,et al.  A statistical model for SILC in flash memories , 2002 .