TCAD modeling and characterization of short-range variations in multiple-gate devices and circuit blocks

Short-range process variations such as line-edge roughness (LER) and random dopant fluctuations (RD) are extremely critical in aggressively scaled devices. In this work, techniques to incorporate such variations into Technology Computer-Aided Design (TCAD) simulations are discussed. Different statistical approaches are considered, including Monte Carlo and propagation of variance techniques, which allow predicting the impact of process variations on both device and circuit performance through physical, mixed-mode and SPICE simulations. Statistical dependencies and correlations among fluctuations of several parameters are investigated to provide a link between physical-, device- and circuit-level modeling. The described techniques are exploited to investigate feasibility of mainstream applications of FinFET devices at the LSTP-32nm node. The performance of single devices and SRAM cells are characterized, comparing different contributions to line-edge roughness, assessing relative importance of LER and RD issues and providing design guidelines for minimizing the impact of short-range variations.

[1]  A. Asenov,et al.  Intrinsic parameter fluctuations in decananometer MOSFETs introduced by gate line edge roughness , 2003 .

[2]  M. Ieong,et al.  Modeling line edge roughness effects in sub 100 nanometer gate length devices , 2000, 2000 International Conference on Simulation Semiconductor Processes and Devices (Cat. No.00TH8502).

[3]  Colin C. McAndrew,et al.  Statistical modeling for circuit simulation , 2003, Fourth International Symposium on Quality Electronic Design, 2003. Proceedings..

[4]  Alan Mathewson,et al.  Relating statistical MOSFET model parameter variabilities to IC manufacturing process fluctuations enabling realistic worst case design , 1994 .

[5]  D.B.M. Klaassen,et al.  Device modeling of statistical dopant fluctuations in MOS transistors , 1997, SISPAD '97. 1997 International Conference on Simulation of Semiconductor Processes and Devices. Technical Digest.

[6]  A. Asenov Random dopant induced threshold voltage lowering and fluctuations in sub-0.1 /spl mu/m MOSFET's: A 3-D "atomistic" simulation study , 1998 .

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

[8]  E.. Baravelli,et al.  Impact of Line-Edge Roughness on FinFET Matching Performance , 2007, IEEE Transactions on Electron Devices.

[9]  Asen Asenov,et al.  Impact of intrinsic parameter fluctuations in decanano MOSFETs on yield and functionality of SRAM cells , 2005 .

[10]  W. Fichtner,et al.  Random dopant fluctuation modelling with the impedance field method , 2003, International Conference on Simulation of Semiconductor Processes and Devices, 2003. SISPAD 2003..

[11]  M. Jurczak,et al.  Impact of LER and Random Dopant Fluctuations on FinFET Matching Performance , 2008, IEEE Transactions on Nanotechnology.