Showing posts with label parameter extraction. Show all posts
Showing posts with label parameter extraction. Show all posts

May 24, 2024

[paper] Rapid MOSFET Threshold Voltage Testing

Michael H. Herman; Trenton T. Nguyen; Ken Wong; Jeff Johnson; Ben Morris
Rapid MOSFET Threshold Voltage Testing
for High Throughput Semiconductor Process Monitoring
2024 IEEE 36th International Conference on Microelectronic Test Structures (ICMTS)
Edinburgh, United Kingdom, 2024, pp. 1-6
doi : 10.1109/ICMTS59902.2024.10520252

* Parametric Test Group, Advantest America, San Jose, CA 95134 United States

Abstract : We describe a method for rapid MOSFET threshold voltage (Vt) measurement. Multiple spot Ids measurements are compared to stored reference data. Each spot measurement yields an independent Vt estimate, and these enable quality metric calculation. A Vt and quality metric can be measured within 7 msec, using two spot measurements. The method permits parallel MOS testing.

FIG : Reference Ids-Vgs Curve with Gm curveB2Q8 device 2N7002 NMOS Transistor
at Vds = 0.05 Gm(max) 0.02272 at Vgs 2.25V; Extrap tangent line at 1.8665V




Oct 25, 2023

[paper] Sub-THz HICUM for SiGe HBTs

Soumya Ranjan Panda, Thomas Zimmer, Anjan Chakravorty, Nicolas Derrier
and Sebastien Fregonese
Exploring Compact Modeling of SiGe HBTs in Sub-THz Range With HICUM
in IEEE TED, DOI: 10.1109/TED.2023.3321017.

IMS laboratory, CNRS, University of Bordeaux (F)
Department of Electrical Engineering, IIT Madras (IN)
STMicroelectronics, 38920 Crolles (F)


Abstract : This study delves deeper into the high frequency (HF) behavior of state-of-the-art sub-THz silicon germanium heterojunction bipolar transistors (SiGe HBTs) fabricated with 55 nm BiCMOS process technology from STM. Using measurement data, calibrated TCAD simulations, and compact model simulations, we present a comprehensive methodology for extracting several HF parameters (related to parasitic capacitance partitioning and nonquasi-static effects) of the industry standard model, HICUM. The parameter extraction strategies involve thorough physics-based investigation and sensitivity analysis. The latter allowed us to precisely evaluate the effects of parameter variations on frequency dependent characteristics. The accuracy of the finally deployed model is tested by comparing the model simulation with measured small-signal two-port parameters of SiGe HBTs up to 330 GHz.
FIG: a.)  TEM image of the SiGe HBT device; b.) 2D TCAD structure simulation; c.) Large signal equivalent circuit of HICUM L2 compact model; d.) and e.) adjunct networks for vertical NQS effects

Acknowledgment: The authors would like to acknowledge Dider Celi, STM, for valuable discussion about the compact modeling of heterojunction bipolar transistors (HBTs), and they also like to thank STM for providing the silicon wafers. This work was supported by NANO2022 Important Project of Common European Interest Project (IPCEI), and SHIFT Grant ID 101096256.


Jan 27, 2022

[paper] Automatic Parameter Extraction of MOSFET Compact Models

Gazmend Alia1,2, Andi Buzo1, Hannes Maier-Flaig1, Klaus-Willi Pieper1
Linus Maurer and Georg Pelz1
Automatic Parameter Extraction of MOSFET Compact Models using Differential Evolution with Population Prediction (DEpred)
6th EDTM; March 6 to 9, 2022 
   
1 Infineon Technologies AG, Munich (D)
2 Bundeswehr University Munich (D)


Abstract: Parameter extraction of MOSFET compact models with hundreds of parameters is not a trivial task. Differential evolution (DE) has proven to be very effective in such highly dimensional parameter spaces. However, DE needs a large number of iterations to converge. This paper proposes a novel method to accelerate the convergence of DE by predicting tens of iterations ahead where the population will be, based on the knowledge from the already finished iterations. The method is validated with BSIM4 and HiSIM-HV compact models, where up to 50% of the iterations are saved.

Fig: DE vs DEpred cost function for BSIM4 and HiSIM-HV models.
DEpred reaches the target 50% faster.








Dec 8, 2021

[paper] Automated Compact Model Parameter Extraction

Marc Huppmann∗, Klaus-Willi Pieper†, Andi Buzo†, Linus Maurer∗ and Georg Pelz†
Utilizing Differential Evolution for an Automated Compact Model Parameter Extraction
In 2021 International Semiconductor Conference (CAS), pp. 231-234. IEEE, 2021.
   
∗ Universitat der Bundeswehr Munchen, Neubiberg, Germany
† Infineon Technologies AG, Neubiberg, Germany

Abstract: Parameter extraction is a challenging task, as it searches for a solution inside a high dimensional plus non- convex space. To be able to apply well known gradient based optimizers, the problem is dissected into multiple simpler yet intertwined tasks, which yields a complex and manual labour intensive procedure. On the contrary to gradient based methods, genetic algorithms perform excellent on global search problems, which eliminates the need for such a sophisticated workflow. In this paper, a highly automated methodology is presented that is capable of replacing the standard manual extraction sequence for the BSIM MOSFET compact model. Due to its superior extreme finding behaviour, the Differential Evolution algorithm is applied in combination with a special error metric to ensure a high fitting quality, in all regions of the output and transfer curves. Repeatably good results for 20k measurement points are obtained, with a reduction of factor 10 in total fitting duration, while coincidentally consuming mostly computation instead of manual labour time.
Fig: With every iteration, the errors approach each other till
they meet in roughly one point and σi terminates the fitting.





Oct 20, 2021

[paper] Parameter Extraction Approaches for Memristor Models

Dmitry Alexeevich Zhevnenko1,2, Fedor Pavlovich Meshchaninov1,2, Vladislav Sergeevich Kozhevnikov1,2, Evgeniy Sergeevich Shamin1,2, Oleg Alexandrovich Telminov1,2, and Evgeniy Sergeevich Gornev1,2
Research and Development of Parameter Extraction Approaches for Memristor Models
Micromachines 2021, 12, 1220. 
DOI: 10.3390/mi12101220
   
1 Moscow Institute of Physics and Technology, Moscow, Russia;
2 JSС MERI, Zelenograd, Russia

Abstract: Memristors are among the most promising devices for building neural processors and non-volatile memory. One circuit design stage involves modeling, which includes the option of memristor models. The most common approach is the use of compact models, the accuracy of which is often determined by the accuracy of their parameter extraction from experiment results. In this paper, a review of existing extraction methods was performed and new parameter extraction algorithms for an adaptive compact model were proposed. The effectiveness of the developed methods was confirmed for the volt-ampere characteristic of a memristor with a vertical structure: TiN/HfxAl1-xOy/HfO2/TiN.

Fig: Model VACs with different numbers of inhomogeneities: 
(a) four inhomogeneities; (b) no inhomogeneities.

Acknowledgments: This research was funded by the Ministry of Science and Higher Education of the Russian  Federation, grant number 075-15-2020-791. Authors thank the Institute of Microelectronics Technology and High-Purity Materials RAS for access to experimental data on the study of graphene oxide memristor switching cycles.


Oct 13, 2021

[paper] Parameter Extraction of Power MOSFET Models

Michihiro Shintani, Aoi Ueda and Takashi Sato
Accelerating Parameter Extraction of Power MOSFET Models Using Automatic Differentiation
IEEE Transactions on Power Electronics (2021)
DOI:  10.1109/TPEL.2021.3118057
 
Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma (J)
Graduate School of Informatics, Kyoto University (J)
 

Abstract: The extraction of the model parameters is as im- portant as the development of compact model itself because simulation accuracy is fully determined by the accuracy of the pa- rameters used. This study proposes an efficient model-parameter extraction method for compact models of power MOSFETs. The proposed method employs automatic differentiation (AD), which is extensively used for training artificial neural networks. In the proposed AD-based parameter extraction, gradient of all the model parameters is analytically calculated by forming a graph that facilitates the backward propagation of errors. Based on the calculated gradient, computationally intensive numerical differentiation is eliminated and the model parameters are efficiently optimized. Experiments are conducted to fit current and capacitance characteristics of commercially available silicon carbide MOSFET using power MOSFET models having 13 model parameters. Results demonstrated that the proposed method could successfully derive the model parameters 3.50× faster than a conventional numerical-differentiation method while achieving the equal accuracy.
Fig: Backward propagation mode. The dashed arrows indicate the path from E to SCALE.
The propagated values on the path in the backward propagation are highlighted

Acknowledgment: This work was partially supported by JST-OPERA Program Grant Number JPMJOP1841, Japan. The part of this work is also supported by JSPS KAKENHI Grant 20H04156 and 20K21793.







Apr 19, 2021

[Photos] MOS-AK LADEC Mexico April 18, 2021

Arbeitskreis Modellierung von Systemen und Parameterextraktion
Modeling of Systems and Parameter Extraction Working Group
MOS-AK LAEDC Workshop
(virtual/online) April 18, 2021

Together with local Host and LAEDC Organizers as well as all the Extended MOS-AK TPC Committee, we have organized the 3rd subsequent MOS-AK/LAEDC workshop which was the Virtual/Online event. There are a couple of the event photos:

MOS-AK Session 1 (APR.18) begun: 8:00am Mexico time zone (GMT-5)

T_1 FOSSEE eSIM: An open source CAD software for circuit simulation
Kannan Moudgalya
IIT Bombay (IN)

T_2 Memristor modeling
Arturo Sarmiento
INAOE (MX)

T_3 Modeling Issues for CMOS RF ICs
Roberto Murphy, Jose Valdes and Reydezel Torres
INAOE (MX)

T_4 Improving Time-Dependent Gate Breakdown of GaN HEMTs with p-type Gate
E. Sangiorgi, A. Tallarico, N. Posthuma, S. Decoutere, C. Fiegna
Universita di Bologna

MOS-AK Session 2 (APR.18) begun: 1:00pm Mexico time zone (GMT-5)

T_5 Compact Models of SiC and GaN Power Devices
Alan Mantooth, Arman Ur Rashid, Md Maksudul Hossain
University of Arkansas (US)

T_6 New analytical model for AOSTFTs
Antonio Cerdeira
CINVESTAV-IPN, Mexico City (MX)

T_7 On the Parameter Extraction of Thin-Film Transistors in Weak-Conduction
Adelmo Ortiz-Conde
Solid State Electronics Laboratory, Simon Bolivar University, Caracas (VE)

End of MOS-AK Workshop
Group Photo






Jan 12, 2021

[paper] Modeling Power GaN-HEMTs in SPICE

Utkarsh Jadli, Faisal Mohd-Yasin, Hamid Amini Moghadam, Peyush Pande*, Mayank Chaturvedi and Sima Dimitrijev
Modeling Power GaN-HEMTs Using Standard MOSFET Equations and Parameters in SPICE
Electronics 2021, 10, 130
DOI: 10.3390/electronics10020130

Queensland Micro- and Nanotechnology Centre, Griffith University, Brisbane, QLD 4111, Australia;
*Electronics Department, Graphic Era (Deemed to Be University), Dehradun, Uttarakhand 248002, India;

Abstract: The device library in the standard circuit simulator (SPICE) lacks a gallium nitride based high-electron-mobility-transistor (GaN-HEMT) model, required for the design and verification of power-electronic circuits. This paper shows that GaN-HEMTs can be modeled by selected equations from the standard MOSFET LEVEL3 model in SPICE. A method is proposed for the extraction of SPICE parameters in these equations. The selected equations and the proposed parameter-extraction method are verified with measured static and dynamic characteristics of commercial GaN-HEMTs. Furthermore, a double pulse test is performed in LTSpice and compared to its manufacturer model to demonstrate the effectiveness of the MOSFET LEVEL3 model. The advantage of the proposed approach to use the MOSFET LEVEL3 model, in comparison to the alternative behavioral-based model provided by some manufacturers, is that users can apply the proposed method to adjust the parameters of the MOSFET LEVEL3 model for the case of manufacturers who do not provide SPICE models for their HEMTs.

Fig: Internal cross-sectional structure of GaN-HEMT

Acknowledgments: The authors would like to acknowledge the Innovative Manufacturing Co- operative Research Centre (IMCRC) for providing a PhD scholarship to the first author. We also acknowledge the School of Engineering and Built Environments (EBE) of Griffith University for funding this project. This work was performed in part at the Queensland node of the Australian National Fabrication Facility, a company established under the National Collaborative Research Infrastructure Strategy to provide nano- and micro-fabrication facilities for Australia’s researchers.

Jan 4, 2021

[paper] Compact Modeling of Carbon Nanotube FETs

A Compact and Robust Technique for the Modeling and Parameter Extraction 
of Carbon Nanotube Field Effect Transistors
Laura Falaschetti1, Davide Mencarelli1, Nicola Pelagalli1, Paolo Crippa1, Giorgio Biagetti1,
Claudio Turchetti1,George Deligeorgis2, and Luca Pierantoni1
Electronics 2020, 9(12), 2199; 
DOI: 10.3390/electronics9122199

1 Department of Information Engineering, Marche Polytechnic University, 60131 Ancona, Italy
2 Microelectronics Research Group (MRG/IESL), FORTH, Greece


Abstract: Carbon nanotubes field-effect transistors (CNTFETs) have been recently studied with great interest due to the intriguing properties of the material that, in turn, lead to remarkable properties of the charge transport of the device channel. Downstream of the full-wave simulations, the construction of equivalent device models becomes the basic step for the advanced design of high-performance CNTFET-based nanoelectronics circuits and systems. In this contribution, we introduce a strategy for deriving a compact model for a CNTFET that is based on the full-wave simulation of the 3D geometry by using the finite element method, followed by the derivation of a compact circuit model and extraction of equivalent parameters. We show examples of CNTFET simulations and extract from them the fitting parameters of the model. The aim is to achieve a fully functional description in Verilog-A language and create a model library for the SPICE-like simulator environment, in order to be used by IC designers.
Figure 2. 3D structure of CNTFET. Reprinted, with permission, from [I and II]

Aknowlwgement: This research was supported by the European Project “NANO components for electronic SMART wireless circuits and systems (NANOSMART)”, H2020—ICT-07-2018-RIA, n. 825430.

References:
[I] Deng, J.; Wong, H.P. A Compact SPICE Model for Carbon-Nanotube Field-Effect Transistors Including non-idealities and Its Application—Part I: Model of the Intrinsic Channel Region. IEEE Trans. Electron Devices 2007, 54, 3186–3194
[II] Deng, J.; Wong, H.P. A Compact SPICE Model for Carbon-Nanotube Field-Effect Transistors Including non-idealities and Its Application—Part II: Full Device Model and Circuit Performance Benchmarking. IEEE Trans. Electron Devices 2007, 54, 3195–3205 




Nov 4, 2020

[paper] Local Variability Evaluation on Effective Channel Length

Juan Pablo Martinez Brito, Graduate Student Member, IEEE, 
and Sergio Bampi, Senior Member, IEEE
Local Variability Evaluation on Effective Channel Length
Extracted with Shift-and-Ratio Method
IEEE TED, vol. 67, no. 11, pp. 4662-4666, Nov. 2020
doi: 10.1109/TED.2020.3017178

Abstract: In this study, the local variation of the effective channel reduction parameter (ΔL=Lm−Leff) of a MOSFET is extracted by means of the traditional shift-and-ratio (SAR) method. ΔL is then correlated with the threshold voltage difference (ΔVTH) between the device under test (DUT) and the reference device. It is demonstrated that there exists an optimal VG range for extracting reliable values of L through the SAR method. Statistical data analysis shows that for R≈ (Llong/Lshort)≈25, better results are achieved since the value of σ(ΔL) varies typically as the reciprocal 1/√ W. The test structure used in this work is a Kelvin-based 2-D addressable MOSFET matrix implemented in 180-nm bulk CMOS technology. The sample space is of 2304 devices divided into nine subgroups of 256 same size closely placed nMOSFETs.
Fig: (a) Full circuit micrograph (b) MOSFET Matrix structure (c) Zoomed-in view at DUTs 

Acknowledgment: The authors would like to thank and acknowledge the Brazilian public company CEITEC S.A. Semiconductors for the measurement infrastructure, the CAD Support Center (NSCAD) at Federal University of Rio Grande do Sul (UFRGS) for electronic design automation (EDA) support, and Silterra Inc. for the silicon prototyping services.

Oct 19, 2020

[paper] Parameter Extraction Technique for IGBT Compact Model

N.V. Bharadwaj1, Dr. P. Chandrasekhar2 and Dr. M. Sivakumar3
A Consecutive Parameter Extraction Technique for IGBT Compact Model
ICMM-2019; AIP Conf. Proc. 2269, 030031-1–030031-5;
DOI: 10.1063/5.0019484

1Geethanjali College of Enegineering and Technology, Hyderabad, 501301, India 
2MGIT, Hyerabad, 500075, India 
3Gudlavalleru Engineering College, Gudlavalleru , 521356, India

Abstract: A consecutive parameter extraction technique describes the fitting target related parameters for Insulated-gate bipolar transistor (IGBT) model. The IGBT model has been represented by a couple of simplified equivalent circuits. Using simulated data for a trench-type IGBT as reference the performance of compact model IGBT is compared to an IGBT macro model. Due to physics based modeling, parameter extraction with the compact model is fast. With very less extraction effort, the compact model fits the dc current and capacitance characteristics accurately.

FIG: The IGBT cell structure with cell pitch = 4μm and trench gate depth = 3μm





Aug 5, 2020

[paper] GCC Method for Determining MOSFET VTH

Matthias Bucher1, Nikolaos Makris1, Loukas Chevas1
Generalized Constant Current Method for Determining MOSFET Threshold Voltage
arXiv:2008.00576v1 (2 Aug 202) 
has been submitted to the IEEE for possible publication

1 School of Electrical and Computer Engineering, Technical University of Crete

Abstract: A novel method for extracting threshold voltage (VTH) and substrate effect parameters of MOSFETs with constant current bias at all levels of inversion is presented. This generalized constant-current (GCC) method exploits the charge-based model of MOSFETs to extract threshold voltage and other substrate-effect related parameters. The method is applicable over a wide range of current throughout weak and moderate inversion and to some extent in strong inversion. This method is particularly useful when applied for MOSFETs presenting edge conduction effect (subthreshold hump) in CMOS processes using Shallow Trench Isolation (STI).
Fig:  Application of the GCC method in presence of edge conduction phenomenon in STI MOSFETs. A constant current is applied to determine pinchoff voltage for the center transistor in moderate inversion at IC=2. To characterize the edge transistor, imposing a current criterion IC=1E−4 corresponds to ICe≈0.02. Pinchoff voltage (VP) and slope factor n characteristics illustrate the determination of parameters for center and edge transistors.

Acknowledgment: This work was partly supported under Project INNOVATION-EL-Crete
(MIS 5002772).





May 11, 2020

Conference Paper Reached 500 Reads

Wladek 
Wladek Grabinski, Daniel Tomaszewski, Farzan Jazaeri, Anurag Mangla, Jean-Michel Sallese, Maria-Anna Chalkiadaki, Antonios Bazigos, and Matthias Bucher
FOSS EKV 2.6 Parameter Extractor
22nd International MIXDES Conference, pp. 181-186 (2015)

Abstract: The design of advanced integrated circuits (IC) in particular for low power analog and radio-frequency (RF) application becomes more complex as the device level modeling confronting challenges in micro- and nano-meter CMOS processes. As present CMOS technologies continue geometry scaling the designers can benefit using dedicated SPICE MOSFET models and apply specific analog design methodologies. The EKV was developed especially to meet altogether the analog/RF design requirements. This paper describes a basic set of the DC parameter extraction steps for the EKV 2.6 model. The free open source software (FOSS) Profile2D tool was used to illustrate an accurate EKV 2.6 DC extraction strategy. 


Apr 24, 2020

conference FOSS paper reached 300 reads


D. Tomaszewski, G. Głuszko, M. Brinson, V. Kuznetsov and W. Grabinski, "FOSS as an efficient tool for extraction of MOSFET compact model parameters," 2016 MIXDES - 23rd International Conference Mixed Design of Integrated Circuits and Systems, Lodz, 2016, pp. 68-73.

Abstract - A GNU Octave - based application for device-level compact model evaluation and parameter extraction has been developed. The applications main features are as follows: experimental I–V data importing, generating input data for different circuit simulation programs, running the simulation program to calculate I–V characteristics of the specified models, calculating model misfit and its sensitivity to selected parameter variation, and the comparison of experimental and simulated characteristics. Measured I–V data stored by different measurement systems are accepted. Circuit simulations may be done with Ngspice, Qucs and LTSpiceIV © . Selected aspects of the application are presented and discussed.

Mar 30, 2020

conference paper reached 700 reads

M. Bucher, A. Bazigos and W. Grabinski, "Determining MOSFET Parameters in Moderate Inversion," 2007 IEEE Design and Diagnostics of Electronic Circuits and Systems, Krakow, 2007, pp. 1-4.

Abstract: Deep submicron CMOS technology scaling leads to reduced strong inversion voltage range due to non-scalability of threshold voltage, while supply voltage is reduced. Moderate inversion operation therefore becomes increasingly important. In this paper, a new method of determining MOSFET parameters in moderate inversion is presented. Model parameters are determined using a constant current bias technique, where the biasing current is estimated from the transconductance-to-current ratio. This technique is largely insensitive to mobility effects and series resistance. Statistical data measured on 40 dies a 0.25 um standard CMOS technology are used for the illustration of this method.

Feb 8, 2018

BSIM3v3 to EKV2.6 Model Parameter Extraction

BSIM3v3 to EKV2.6 Model Parameter Extraction and Optimisation
using LM Algorithm on 0.18um Technology node
Kirmender Singh and Piyush Jain
Int. Journal of Electronics and Telecommunications 2018 Vol.64 No.1 pp.5-11

Abstract: The industry standard BSIM3v3 and BSIM4.0 have been replaced by BSIM6.0 compact MOSFET model for deep submicron technology node. The BSIM6.0 is next generation, defacto industry standard model for bulk MOSFET. This model is charge based which is continuous from weak to strong inversion of operation. The core of analytical and physical BSIM6 model[3] is charge, with drain current equation expressed in form of source (qs) and drain charge (qd). This model has all its governing equations continuous and can be used to develop design methodology using IC based approach. But its method of computing qs and qd is complicated which is different from Vittoz traditional charge calculation method. The continuous interpolation equation of drain current as adopted by EKV2.6 although is empirical but its compact expression is preferred by analog designer to get intuitive design guidance. BSIM6 is a combined effort by BSIM and EKV modeling groups based on charge based continuous equations. Although EKV2.6 model is not valid for deep submicron process as it only includes submicron short channel effects like velocity saturation (VS), vertical field mobility reduction (VFMR), Drain induced barrier lowering (DIBL), channel length modulation (CLM) etc. But it still offers some benefits to have first cut design methodology because of its much simplified analytical equations. The inversion coefficient (IC) has found extensive acceptance in designer community as it offers enhanced design elegance in EKV then more complicated BSIM model. This paper discuses first step in analog design process by extracted core EKV2.6 intrinsic model parameters from industry standard BSIM3v3 model on 0.18µ technology node. The 0.18µ technology is chosen as it is still more common technology node in analog circuit design. The model parameters are extracted for different bins and optimisation is done using nonlinear optimisation LM algorithm. The optimised EKV2.6 parameters are validated with currentvoltage(I-V), intrinsic voltage gain (Avi) and Early voltage circuit parameter (VA) with BSIM3v3 model [read more...]

Flow-chart of BSIM to EKV conversion steps
(source:
D. Stefanovic and M. Kayal “Structured Analog CMOS Design" Springer Publications, 2008)

Oct 17, 2017

[paper] Accurate diode behavioral model with reverse recovery

Stanislav Banáša,b, Jan Divínab, Josef Dobešb, Václav Paňkoa
aON Semiconductor, SCG Czech Design Center, Department of Design System Technology, 1. maje 2594, 756 61 Roznov pod Radhostem, Czech Republic
bCzech Technical University in Prague, Faculty of Electrical Engineering, Department of Radioelectronics, Technicka 2, 166 27 Prague 6, Czech Republic
Volume 139, January 2018, Pages 31–38

Highlights:

  • The complex robust time and area scalable Verilog-A model of diode containing reverse recovery effect has been developed.
  • Due to implemented reverse recovery effect the model is useful especially for high-speed or high-voltage power devices.
  • The model can be used as stand-alone 2-terminal diode or as a parasitic p-n junction of more complex lumped macro-model.
  • Two methods of model parameter extraction or model validation have been demonstrated.

ABSTRACT: This paper deals with the comprehensive behavioral model of p-n junction diode containing reverse recovery effect, applicable to all standard SPICE simulators supporting Verilog-A language. The model has been successfully used in several production designs, which require its full complexity, robustness and set of tuning parameters comparable with standard compact SPICE diode model. The model is like standard compact model scalable with area and temperature and can be used as a stand-alone diode or as a part of more complex device macro-model, e.g. LDMOS, JFET, bipolar transistor. The paper briefly presents the state of the art followed by the chapter describing the model development and achieved solutions. During precise model verification some of them were found non-robust or poorly converging and replaced by more robust solutions, demonstrated in the paper. The measurement results of different technologies and different devices compared with a simulation using the new behavioral model are presented as the model validation. The comparison of model validation in time and frequency domains demonstrates that the implemented reverse recovery effect with correctly extracted parameters improves the model simulation results not only in switching from ON to OFF state, which is often published, but also its impedance/admittance frequency dependency in GHz range. Finally the model parameter extraction and the comparison with SPICE compact models containing reverse recovery effect is presented [read more...]

FIG: Solving the recursive calculation of reverse recovery charge

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.

Feb 24, 2016

Keysight: Full SPICE Characterization Flow

Keysight Technologies offers half a daya seminar at IEMN, Villeneuve d’Ascq. This free seminar is an opportunity to discover "Full SPICE Characterization Flow". The content is open, based on practical industrial and academic examples to illustrate the features of Keysight CAD/EDA software tools:
  • Introduction (20 min)
  • Part 1 - Measurements Automatization (30 min)
  • Part 2 - Spice Model Extraction  (60 min)
  • Part 3 - Quality Assurance Model (20 mins)
  • Q/A Session (20 min)
Place: Grand Amphithéâtre de l’IEMN, Laboratoire Centrale, Avenue Henri Poincaré F-59491 Villeneuve d’Ascq (F)
Date 17 March 2016

[Register online]

Nov 10, 2014

i-MOS version 201410 release

  New release of the interactive Modeling and On-line Simulation Platform (i-MOS), version 201410 has been released. In this release we have launched some new features:
  • Developing an ‘Equalizer’ module in the ‘Model’ page for easy model parameter tuning
  • Accommodating multiple parameters in this module for users’ most convenience
  • Improving the ‘Custom data’ function for manual parameter extractions
  • Updating the TFET model e-TIM (previous e-TuT) to support multiple materials
  • Including an am-bipolar current module in the e-TIM
The new  release is ready here i-MOS.