fast blaze
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FastBlaze
Ultra-Fast MESFET and HEMT Device Simulator
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FASTBlaze Ultra-Fast MESFET and HEMT Device Simulator
Introduction to MERCURY TCAD Framework
The MERCURY framework is an application-specific TCAD toolset designed for FET simulation
Three Main Foundations of MERCURYFast Simulations (typically less than 1 minute)Accurate Physical Models
Accessible to all engineers
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MERCURY Modules
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Inputparser
Comprehensive
material and transportparameter database
Mocasim
C-Interpreter
Core Simulation FastBlaze
HarmonicBalance
FastNoise Post Processing
FastMixedMode
Automated meshgenerator
Automatic solutionsection
Wide selection ofphysical models
DC IV extraction Small-Signal RF
extraction
impedance-field
calculationcoupled with localnoise servicecalculation
Multi-frequency
large signal RFsimulator
Circuit embedded
device simulation(large signal)
Two port extraction Equivalent circuit
extraction Noise parameterextraction
FastGiga
Lattice heatflow equation
Future
Future
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FastBlaze Applications (cont.)
Analyses possible:
ID-VDS for various VGSID-VGS for various VDSTransconductancePunchthrough
Gate capacitanceTime domain waveformsRF two-port parameter extraction (eg. s-parameters)RF parameters as function of frequency and bias
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How Fast is FastBlaze?
All timings on a Sun ULTRA10 workstation
All simulations were on a 0.5 um gate length recessed MESFET or pHEMT. The DC Id-Vd simulations weretaken over the range -2.0V
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MERCURY Method
Two phases to MERCURY solution:
Charge control simulation vertically under the gate, recess and capregions
Transport simulation across the channel solving Poisson, currentcontinuity, and energy balance equations
REFERENCESR. Drury & C.M. Snowden, "A quasi-two-dimensional HEMT model for microwave CAD applications", IEEE
Transactions on Electron Devices, Vol. ED-42, No. 6, pp.1026-1032, 1995
C.M. Snowden & R.R. Pantoja, "GaAs MESFET Physical Models for Process-Orientated Design", IEEETransactions on Electron Devices, Vol. ED-40, No. 7, pp.1401-1409, 1992
B. Carnez, A. Cappy, et al. "Noise Modeling in Submicrometer-Gate FET's", IEEE Transactions on Electron
Devices, Vol. ED-28, No.7, pp.784-789, 1981
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MERCURY Method
Solution method is fast because:
Charge control data stored and accessed directly as a lookup tableCurrent driven allowing integration method for carrier transportScales linearly with number of mesh points (N)
conventional schemes scale as NHighly efficient Newton solverAutomated IV bias control to minimize the number of solution points
required
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MERCURY Method
The consequences of the MERCURY approach are:
No need to tradeoff accuracy for speed. Rapid simulation allows useof the most sophisticated models
Meshing and bias stepping can be automatedInitial guesses and convergence control are taken care of inherentlyTwo-dimensional effects can be modeled such as punchthrough
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MERCURY Method: Experimentation
Parameters which can be varied without recalculating the chargecontrolgate lengthrecess or contact lithographytransport models and parametersextrinsic and intrinsic parasiticsgate workfunction
Parameters which can be varied but do require a new chargecontrol simulation
epitaxial layer materials or thicknessesdoping and trap densitiesrecess depthtrap occupation models
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FastBlaze Key Features
Two different classes of key features:
Advanced Physical Modelstransport tuned using Monte Carlo Simulation
User Oriented Featuresgrid generationbias steppingdirect simulation at any bias pointGUI for structure definition
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Automated Grid Generation
Adaptive mesh refinementuses field solution obtainedfrom very fine mesh (10A)adaptive step size control
based on Taylor expansion
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Mesh layout around the gate, automaticallygenerated within MERCURY. Typical meshsize at drain edge of gate 2.8 x 0.6nm.
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Automated Current Driven Bias Stepping
An automated DC-IV generator only samples biaspoints where needed. This provides a highly efficient
method to characterize DC performance.
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Integration with VWF Framework
Code developed in-house to commercial standards
Seamless integration with DeckBuild and TonyPlotGeneral purpose optimization with optimizerRSM and advanced DOE using the VWF Automation Tools
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Ultra-Fast MESFET and HEMT Device Simulator
A customized, FastBlaze specific, GUI enables rapid device definition.This includes the geometrical, model and solution description providing
a straightforward setup of the simulation.
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Advanced Physical Models
Boltzmann, Fermi and Quantum Statistics
Energy Balance always usedAdvanced transport models
Monte Carlo derived velocity and energy and momentum relaxationtimes
Gate conduction Models (thermionic emission)
Extrinsic parasitic simulation Interface and bulk traps Integrated with C-interpreter for user defined models
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Quantum Mechanical Simulation
Self-consistently solves the Schrodinger and Poisson equations inthe charge control
Solves arbitrary number of bound statesUses highly efficient eigen solver routine to maintain high speedShows wavefront broadening into adjacent layers
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Conduction Band Energy and Eigenspectrum
The conduction band edge for a delta-doped GaAs/AlGaAs/InGaAs/GaAspHEMT is illustrated together with the first eleven bound-state energy
levels calculated using the quantum models.
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Mocasim: Monte Carlo Simulator
A three valley ensemble Monte Carlo simulator
Calculates bulk electron transport parameters for arbitrary threevalley semiconductors
velocityenergy relaxation timemomentum relaxation time
Derives four-dimensional material parameter setapplied fielddoping densitymole fraction(s)lattice temperature
Used to derive transport parameters for device simulators such asFastBlaze
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Mocasim: Features
Includes nine scattering mechanisms:Polar optical phonon absorption and emissionAcoustic phonon scatteringEquivalent valley phonon absorption and emissionNon-equivalent valley phonon absorption and emissionImpurity scatteringSelf-scattering
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Monte Carlo Transport Parameters
The electron velocity for GaAs at 300K is shown as a function of net impurity densityand electric field. The Monte Carlo derived velocity is complemented by both energy
and momentum relaxation times for a wide range of material systems.
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Material Dependent Transport Parameters
Velocity-field characteristics for various III-V materials.
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Transport Parameter Comparison
Comparison of HEMT Id-Vd using correct multi-layer transport models.The AlGaAs transport parameters are derived from Mocasim.
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Hydrogenic Dopant Ionization Comparison
Effect of incomplete ionization on dopant and carrier densities. Bothtraps and dopant impurities have several occupation statistic models.
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InGaAs pHEMT Structure
2D representation of pHEMT structure created in the MERCURY GUI.Definition of epitaxy, doping and recess topography is menu-driven.
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Auto-Generated Mesh for pHEMT
Mesh is automatically generated and focused in the pHEMT channel.
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DC Characteristics
DC characteristics of the pHEMT displayedwith uniform bias steps for clarity.
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Small Signal S-Parameters for a pHEMT
The time-dependent simulation used for RF evaluation is able to transform directlyto a variety of two-port descriptions. Here the small signal s-parameters for a
pHEMT including external contact parasitics are displayed up to 25GHz.
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Recessed MESFET Conduction-Band Energy
Full 2D distributions are provided to allow direct visualization of thecalculated physical parameters. This figure shows the conduction band
edge for a recessed MESFET structure biased at VDS= 2V.
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Transconductance Variation with Recess Depth
FastBlaze allows rapid prototyping of device structures in terms oftopographical, epitaxial and doping variations. This figure illustrates
the effect of increasing recess depth on transconductance.
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Conclusion
FastBlaze provides:Ultra high speed simulation MESFETs and HEMTsUses accurate physical modelsMonte Carlo derived parameters for modeling carrier transportPowerful user interface integrated with VWF tools
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MERCURY Speed Comparison
MERCURY and ATLAS were both used to simulate a planar 0.5 gate length GaAsMESFET on a SUN ULTRA 10 workstation. The total simulation time for an Id-Vdfamily of curves at Vg=0, -0.5V and -1.0V .
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MERCURY ATLAS Comparison
ATLAS MERCURY
Mesh Points 1200 7550 (auto generated)
CPU Time (s) 1400 49