Aug 30, 2017

[paper] Surface Potential Equation for Low Effective Mass Channel Common Double-Gate MOSFET

Ananda Sankar Chakraborty and Santanu Mahapatra, Senior Member, IEEE
in IEEE Transactions on Electron Devices
vol. 64, no. 4, pp. 1519-1527, April 2017
doi: 10.1109/TED.2017.2661798

Abstract: Formulation of accurate yet computationally efficient surface potential equation (SPE) is the fundamental step toward developing compact models for low effective mass channel quantum well MOSFETs. In this paper, we propose a new SPE for such devices considering multisubband electron occupancy and oxide thickness asymmetry. Unlike the previous attempts, here, we adopt purely physical modeling approaches (such as without mixing the solutions from finite and infinite potential wells or using any empirical model parameter), while preserving the mathematical complexity almost at the same level. Gate capacitances calculated from the proposed SPE are shown to be in good agreement with numerical device simulation for wide range of channel thickness, effective mass, oxide thickness asymmetry, and bias voltages [read more...]
FIG: Total gate capacitance per unit width Cgg (Vg) for 7-nm-thick device with 100% asymmetry in front and back oxide thicknesses. nmax = 2. Line = model. Symbol = TCAD

Aug 29, 2017

levmar : Levenberg-Marquardt nonlinear least squares algorithms in C/C++


The site provides GPL native ANSI C implementations of the Levenberg-Marquardt optimization algorithm, usable also from C++, Matlab, Perl, Python, Haskell and Tcl and explains their use. Both unconstrained and constrained (under linear equations, inequality and box constraints) Levenberg-Marquardt variants are included. The Levenberg-Marquardt (LM) algorithm is an iterative technique that finds a local minimum of a function that is expressed as the sum of squares of nonlinear functions. It has become a standard technique for nonlinear least-squares problems and can be thought of as a combination of steepest descent and the Gauss-Newton method. When the current solution is far from the correct one, the algorithm behaves like a steepest descent method: slow, but guaranteed to converge. When the current solution is close to the correct solution, it becomes a Gauss-Newton method.

Interfaces for using levmar from high-level programming environments & languages such as Matlab, Perl Python, Haskell and Tcl are also available; please refer to the FAQ for more details.

VALint: the NEEDS Verilog-A Checker

By Xufeng Wang1, Geoffrey Coram2, Colin McAndrew3
1. Purdue University 2. Analog Devices, Inc. 3. Freescale Semiconductor
Version 1.0.0 - published on 31 Mar 2017
doi:10.4231/D3HX15S0V

Abstract: VALint is the NEEDS created, automatic Verilog-A code checker. Its purpose is to check the quality of the Verilog-A code and provide the author feedback if bad practices, common mistakes, pitfalls, or inefficiencies are found. This VALint is published as a standalone tool for the compact model community. It is also built-in as an integrated part of the NEEDS publishing platform [read more...]


Aug 28, 2017

[paper] Nanoscale MOSFET Modeling

 Nanoscale MOSFET Modeling: 
Part 1: The Simplified EKV Model for the Design of Low-Power Analog Circuits
C. Enz, F. Chicco and A. Pezzotta
in IEEE Solid-State Circuits Magazine, vol. 9, no. 3, pp. 26-35, Summer 2017
doi: 10.1109/MSSC.2017.2712318

Abstract: This article presents the simplified charge-based Enz-Krummenacher-Vittoz (EKV) [11] metal-oxide-semiconductor field-effect transistor (MOSFET) model and shows that it can be used for advanced complementary metal-oxide-semiconductor (CMOS) processes despite its very few parameters. The concept of an inversion coefficient (IC) is first introduced as an essential design parameter that replaces the overdrive voltage VG-VT0 and spans the entire range of operating points from weak via moderate to strong inversion (SI), including the effect of velocity saturation (VS). The simplified model in saturation is then presented and validated for different 40- and 28-nm bulk CMOS processes. A very simple expression of the normalized transconductance in saturation, valid from weak to SI and requiring only the VS parameter mc, is described. The normalized transconductance efficiency Gm/ID, which is a key figure-of-merit (FoM) for the design of low-power analog circuits, is then derived as a function of IC including the effect of VS. It is then successfully validated from weak to SI with data measured on a 40-nm and two 28-nm bulk CMOS processes. It is then shown that the normalized output conductance Gds/ID follows a similar dependence with IC than the normalized Gm/ID characteristic but with different parameters accounting for drain induced barrier lowering (DIBL). The methodology for extracting the few parameters from the measured ID-VG and ID-VD characteristics is then detailed. Finally, it is shown that the simplified EKV model can also be used for a fully depleted silicon on insulator (FDSOI) and Fin-FET 28-nm processes [read more...]

FIG: The simplified EKV model applied to a 28-nm FDSOI CMOS process: 
Gm n UT / ID versus IC for three different transistor channel lengths

References
[1] A. Bahai, “Ultra-low energy systems: Analog to information,” in Proc. European Solid-State Circ. Conf., Sept. 2016, pp. 3–6.
[2] D. Binkley, Tradeoffs and Optimization in Analog CMOS Design. Hoboken, NJ: Wiley, 2008.
[3] W. Sansen, Analog Design Essentials. New York: Springer-Verlag, 2006.
[4] A. Mangla, M. A. Chalkiadaki, F. Fadhuile, T. Taris, Y. Deval, and C. C. Enz, “Design methodology for ultra low-power analog circuits using next generation BSIM6 MOSFET compact model,” Microelectr. J., vol. 44, no. 7, pp. 570–575, July 2013.
[5] Y. S. Chauhan, S. Venugopalan, M. A. Chalkiadaki, M. A. U. Karim, H. Agarwal, S. Khandelwal, N. Paydavosi, J. P. Duarte, C. C. Enz, A. M. Niknejad, and C. Hu, “BSIM6: Analog and RF compact model for bulk MOSFET,” IEEE Trans. Electron Dev., vol. 61, no. 2, pp. 234–244, Feb. 2014.
[6] C. Enz, M. A. Chalkiadaki, and A. Mangla, “Low-power analog/RF circuit design based on the inversion coefficient,” in Proc. European Solid-State Circ. Conf., Sept. 2015, pp. 202–208.
[7] C. Enz and A. Pezzotta, “Nanoscale MOSFET modeling for the design of low-power analog and RF circuits,” in Proc. Int. Conf. MIXDES, June 2016, pp. 21–26.
[8] W. Sansen, “Analog CMOS from 5 micrometer to 5 nanometer,” in Proc. IEEE Int. Solid State Circuits Conf. Dig. Tech. Papers, Feb. 2015, pp. 1–6.
[9] W. Sansen, “Analog design procedures for channel lengths down to 20 nm,” in Proc. IEEE 20th Int. Conf. Electronics, Circuits, and Systems, Dec. 2013, pp. 337–340.
[10] C. C. Enz and E. A. Vittoz, Charge-Based MOS Transistor Modeling - The EKV Model for Low-Power and RF IC Design. Hoboken, NJ: Wiley, 2006.
[11] C. C. Enz, F. Krummenacher, and E. A. Vittoz, “An analytical MOS transistor model valid in all regions of operation and dedicated to low-voltage and low-current applications,” Analog Integr. Circuits Signal Process. J., vol. 8, pp. 83–114, July 1995.
[12] P. Heim, S. R. Schultz, and M. A. Jabri, “Technology-independent biasing technique for CMOS analogue micropower implementations of neural networks,” in Proc. Sixth Australian Conf. Neural Networks, Sydney, Australia, 1995, pp. 9–12.
[13] C. C. Enz and E. A. Vittoz, “CMOS low-power analog circuit design,” in EmergingTechnologies: Designing Low Power Digital Systems, R. Cavin and W. Liu, Eds. Piscataway, NJ: IEEE, 1996, pp. 79–133.
[14] E. Vittoz and J. Fellrath, “CMOS analog integrated circuits based on weak inversion operations,” IEEE J. Solid-State Circuits, vol. 12, no. 3, pp. 224–231, June 1977.
[15] A. Mangla, C. C. Enz, and J. M. Sallese, “Figure-of-merit for optimizing the current efficiency of low-power RF circuits,” in Proc. Int. Conf. Mixed Design Integrated Circuits and Systems, June 2011, pp. 85–89.
[16] A. Mangla, “Modeling nanoscale quasi-ballistic MOS transistors,” Ph.D. dissertation, EPFL, Switzerland, Dissertation No. 6385, 2014.
[17] R. R. Troutman and A. G. Fortino, “Simple model for threshold voltage in a short- channel IGFET,” IEEE Trans. Electron. Dev., vol. 24, no. 10, pp. 1266–1268, Oct. 1977.
[18] N. Arora, MOSFET Models for VLSI Circuit Simulation. New York: Springer-Verlag, 1993.
[19] Z. H. Liu, C. Hu, J. H. Huang, T. Y. Chan, M. C. Jeng, P. K. Ko, and Y. C. Cheng, “Threshold voltage model for deep submicrometer MOSFETs,” IEEE Trans. Electron Dev., vol. 40, no. 1, pp. 86–95, Jan. 1993.
[20] M. A. Chalkiadaki, “Characterization and modeling of nanoscale MOSFET for ultra-low power RF IC design,” Ph.D. dissertation, EPFL, Switzerland, Dissertation No. 7030, 2016.

Aug 25, 2017

Physics-Based Multi-Bias RF Large-Signal GaN HEMT #Modeling and Parameter Extraction Flow - IEEE Xplore Document... https://t.co/tT8gOLBa9k


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August 25, 2017 at 11:37AM
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An Analytical #Model for the Gate C–V Characteristics of UTB III—V-on-Insulator MIS Structure - IEEE Xplore... https://t.co/Fe1Fqwu5BJ


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