Three-Dimensional Simulation of Charge-Trap Memory Programming—Part I: Average Behavior

This paper presents a detailed investigation of charge-trap memory programming by means of 3-D TCAD simulations accounting both for the discrete and localized nature of traps and for the statistical process ruling granular electron injection from the substrate into the storage layer. In addition, for a correct evaluation of the threshold-voltage dynamics, cell electrostatics and drain current are calculated in presence of atomistic doping, largely contributing to percolative substrate conduction. Results show that the low average programming efficiency commonly encountered in nanoscaled charge-trap memory devices mainly results from the low impact of locally stored electrons on cell threshold voltage in presence of fringing fields at the cell edges. Programming variability arising from the discreteness of charge and matter will be addressed in Part II of this paper.

[1]  Chih-Yuan Lu,et al.  study of incremental step pulse programming (ISPP) and STI edge effect of BE-SONOS NAND Flash , 2008, 2008 IEEE International Reliability Physics Symposium.

[2]  Nobuyuki Sano,et al.  On discrete random dopant modeling in drift-diffusion simulations: physical meaning of 'atomistic' dopants , 2002, Microelectron. Reliab..

[3]  Kyoung-Hwan Park,et al.  Modeling and Characterization of Program / Erasure Speed and Retention of TiN-gate MANOS (Si-Oxide-SiNx-Al2O3-Metal Gate) Cells for NAND Flash Memory , 2007, 2007 22nd IEEE Non-Volatile Semiconductor Memory Workshop.

[4]  A. Asenov,et al.  Simulation Study of Individual and Combined Sources of Intrinsic Parameter Fluctuations in Conventional Nano-MOSFETs , 2006, IEEE Transactions on Electron Devices.

[5]  A Maconi,et al.  Comprehensive Investigation of Statistical Effects in Nitride Memories—Part II: Scaling Analysis and Impact on Device Performance , 2010, IEEE Transactions on Electron Devices.

[6]  H. Wong,et al.  Three-dimensional "atomistic" simulation of discrete random dopant distribution effects in sub-0.1 /spl mu/m MOSFET's , 1993, Proceedings of IEEE International Electron Devices Meeting.

[7]  A. Lacaita,et al.  First evidence for injection statistics accuracy limitations in NAND Flash constant-current Fowler-Nordheim programming , 2007, 2007 IEEE International Electron Devices Meeting.

[8]  P. Arnett,et al.  Transient conduction in insulators at high fields , 1975 .

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

[10]  Subhash Saini,et al.  Hierarchical approach to "atomistic" 3-D MOSFET simulation , 1999, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[11]  L. Larcher,et al.  Investigation of trapping/detrapping mechanisms in Al2O3 electron/hole traps and their influence on TANOS memory operations , 2010, Proceedings of 2010 International Symposium on VLSI Technology, System and Application.

[12]  Guido Torelli,et al.  Technological and design constraints for multilevel flash memories , 1996, Proceedings of Third International Conference on Electronics, Circuits, and Systems.

[13]  Andrea L. Lacaita,et al.  Investigation of the ISPP dynamics and of the programming efficiency of charge-trap memories , 2010, 2010 Proceedings of the European Solid State Device Research Conference.

[14]  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.

[15]  A. Mauri,et al.  Physical Modeling for Programming of TANOS Memories in the Fowler–Nordheim Regime , 2009, IEEE Transactions on Electron Devices.

[16]  S M Amoroso,et al.  Three-Dimensional Simulation of Charge-Trap Memory Programming—Part II: Variability , 2011, IEEE Transactions on Electron Devices.

[17]  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.

[18]  C.M. Compagnoni,et al.  Analytical Model for the Electron-Injection Statistics During Programming of Nanoscale nand Flash Memories , 2008, IEEE Transactions on Electron Devices.

[19]  Tahone Yang,et al.  Study of Local Trapping and STI Edge Effects on Charge-Trapping NAND Flash , 2007, 2007 IEEE International Electron Devices Meeting.

[20]  Tahone Yang,et al.  Understanding STI edge fringing field effect on the scaling of charge-trapping (CT) NAND Flash and modeling of incremental step pulse programming (ISPP) , 2009, 2009 IEEE International Electron Devices Meeting (IEDM).

[21]  A. Visconti,et al.  Comprehensive Analysis of Random Telegraph Noise Instability and Its Scaling in Deca–Nanometer Flash Memories , 2009, IEEE Transactions on Electron Devices.

[22]  Tetsuo Endoh,et al.  Fast and accurate programming method for multi-level NAND EEPROMs , 1995, 1995 Symposium on VLSI Technology. Digest of Technical Papers.

[23]  Andrew R. Brown,et al.  Simulation of intrinsic parameter fluctuations in decananometer and nanometer-scale MOSFETs , 2003 .

[24]  J. Paul,et al.  Analysis of TANOS Memory Cells With Sealing Oxide Containing Blocking Dielectric , 2010, IEEE Transactions on Electron Devices.

[25]  Christian Monzio Compagnoni,et al.  Comprehensive Investigation of Statistical Effects in Nitride Memories—Part I: Physics-Based Modeling , 2010, IEEE Transactions on Electron Devices.

[26]  A. Asenov,et al.  Statistical aspects of reliability in bulk MOSFETs with multiple defect states and random discrete dopants , 2008, Microelectron. Reliab..

[27]  A. Visconti,et al.  Ultimate Accuracy for the nand Flash Program Algorithm Due to the Electron Injection Statistics , 2008, IEEE Transactions on Electron Devices.