ATLAS 2D and 3D Device Simulator - Silvaco · ßSi-pased optoelectronic devices in conjunction with...

ATLAS 2D and 3D Device Simulator

- 2 -ATLAS 2D & 3D Simulator

Overview

ß Basic principles of device simulation

ß ATLAS Framework and Modules

ß Input/Output and Core processing

ß ATLAS input deck structure

ß Mesh design

ß Pisces Physical Models

ß Numerics

ß Tuning device simulators

ß 3D simulations


Basic Principles: What is ATLAS?

ß ATLAS is a 2D and 3D Device Simulation Framework

ß ATLAS solves the fundamental physical equationsdescribing the dynamics of carriers in semiconductordevices for arbitrary device structures

ß ATLAS predicts terminal characteristics of semiconductordevices for steady state, transient, and small signal ACstimuli

ß ATLAS gives insight into the internal characteristics ofsemiconductor devices (e.g. carrier densities, fields,ionization/recombination rates, current densities etc.)


Basic Principles: Create a Structure for Simulation


Basic Principles: Create the Mesh


Basic Principles: Define the Doping Profiles


Group

1. Structure Specification

2. Material Models Specification

3. Numerical Models Specification

4. Solution Specification

5. Results Analysis

Statements

MESHREGIONELECTRODEDOPING

MATERIALMODELSCONTACTINTERFACE

METHOD

LOGSOLVELOADSAVE

EXTRACTTONYPLOT

Elements of ATLAS Input Deck


ATLAS Inputs and Outputs

ATLASDevice

Simulation

DevEditStructure and Mesh Editor

ATHENAProcess

Simulation

DeckBuildRun Time

Environment

ATLASDevice

SimulationTonyPlotVisualization

Tool

StructureFile

CommandFile

RuntimeOutput

SolutionFiles

LogFiles


ATLAS Framework Architecture


ATLAS Framework and Modules: S-Pisces

ß Drift-diffusion equation set

ß Full energy balance / hydrodynamic equations

ß Cartesian and cylindrical coordinate systems

ß DC, AC and Transient simulation domains

ß Extensive database of physical models

ß Impact ionization for device breakdown effects

ß Acceptor-like and Donor-like Trap dynamics

Able to accurately simulate the basic operation of MOS, bipolar, diode and powerdevices which contain silicon, silicon dioxide, polysilicon or metal regions.


ATLAS Framework and Modules: Giga

ß Significant local heating can occur which affects terminalcharacteristics for example:ß High current devices

ß Breakdown characteristics

ß SOI device simulation (Oxide is a good thermal insulator)

ß III-V devices (substrates are poor conductors)

ß Fully Coupled into Energy Balance Modelß 6 equation solver

ß Important to treat Energy balance and lattice heatingeffects together


ATLAS Framework and Modules: Quantum

ß 1D Schrodinger solver

ß Van Dort Correction Model

ß Hansch Correction Model

ß Quantum moments model


ATLAS Framework and Modules: MixedMode

ß Embeds up to 10 ATLAS devices within a standard spicenetlist and solves the complete systemß ESD simulation of human body model and machine model

specifications

ß SEU simulation of memory cells where the logical mode switchesafter an alpha particle strike

ß circuit analysis of devices with no accurate compact model forexample certain power devices

ß verification of newly developed compact models


ATLAS Framework and Modules: Luminous

ß General purpose 2D ray trace and photogeneration.Enables simulation of optoelectronic devices:ß Photodectors, photoconductors, solar cells, CCDs, LEDs, etc.

ß Si-pased optoelectronic devices in conjunction with S-Pisces

ß Optoelectronic devices based on advanced material systemsincluding heterostructures in conjunction with Blaze

ß Optical and self-heating effects (with Giga)

ß Optoelectronic device-circuit simulation (with MixedMode raytracing algorithms

ß Allows simulation of anti-reflective coatings


Mesh Design: Basic Guidelines

ß A good mesh is crucial to accurate simulation results.

ß Creating a good mesh is learned mainly from experience.

ß Some basic guidelines are to refine in key areas:ß Around junctions and depletion regions

ß Inversion regions

ß Areas of high electric field

ß Areas of current flow

ß Base region of BJTs

ß E-B junction is very critical

ß DevEdit is an ideal tool for creating and modifying the meshonly where the user wishes it


Mesh Design: Basic Guidelines (con’t)

ß A suitable grid for process simulation may not be suitablefor device simulation

ß In general, minimize the number of mesh pointsß Solution time »k*(mesh points)1.5 –> 2.5

ß BUT... too few mesh points can take LONGER since eachsolution takes longer to converge. You cannot beatexperience here

ß Use DevEdit to remove unnecessary mesh points and toconcentrate the mesh where it’s needed

ß 10Å mesh in inversion regions. Concentrate mesh atjunctions


Mesh Design: Effect on MOSFET Drain Current

ß Graph showing effect ofincreasing drain currentwith grid spacing

ß This shows therequirement for a griddensity for the inversionregion of 10Å typically


Mesh Design: Effect on Current Gain of a BJT








Contact Definition

ß CONTACT statement is used to :ß set workfunctions for example N+/P+ POLY gate (MOSFETs)

ß Surface recombination velocity (BJT emitter)

ß contact slaving and voltage control (BJT dual base contacts)

ß Schottky contacts (MESFETs, pHEMTs, Diodes, etc)

ß floating contacts (EEPROMs)

ß switch to current boundary conditions (latchup)

ß lumped contact R, L and C

ß distributed contact resistance


S-Pisces Physical Models: Which Model?

ß All simulation programs use a hierarchy of modelsfrom simple to complex models. These are key to accuratesimulations

ß More complex models are generally:ß More complete description of the actual physics

ß Have physically based parameters

ß More predictive


S-Pisces Physical Models: Which Model?

ß Why not just choose the most complex model each time?ß CPU time vs. accuracy gain whilst considering the goal

of the simulation

ß Simpler model gives the same answer in many cases

ß More tuning parameters


Device Simulation Models

ß Mobility Models

ß Recombination Models

ß Generation Models

ß Carrier Statistics

ß Energy Balance

ß Lattice Heating

Model choice tends to be technology specific as well as application specific.Recommendations will be given.


Mobility Models: Which one?

ß Models describing separate physical effects can becombined togetherß Concentration dependence (CONMOB)ß Concentration and temperature dependence (ANALYTIC,

ARORA)ß uses local temperature in Giga

ß Carrier concentration dependence (CCSMOB)ß Parallel electric field dependence (FLDMOB)ß velocity saturationß separate negative differential mobility model for GaAs

(EVSATMOD=1)

ß Transverse electric field dependence (TASCH, WATT,SHIRAHATA)ß surface mobility

ß Integrated models (CVT, YAMAGUCHI, KLA.x)


Recombination Model Hierarchy

ß Shockley-Read-Hall two carrier recombinationß used in almost all simulationsß based on fixed lifetimes (SRH)ß concentration dependent lifetimes (CONSRH and KLASRH)ß trap assisted tunneling (TRAP.TUNNEL)

ß Auger three carrier recombination (AUGER and KLAAUG )ß significant when carrier concentrations high

ß Optical recombination (OPTR)ß for direct band-gap materialsß dominant recombination in GaAs

ß Surface Recombinationß at semiconductor/insulator interfaces (S.N, S.P)ß at metal/semiconductor interfaces (SURF.REC)

ß Trapsß discrete bulk traps (TRAP statement)ß interface traps (INTTRAP statement)ß continuous trap density for non-crystalline materials (DEFECT statement)


Generation Model Hierarchy

ß Impact Ionizationß required for any sort of breakdown voltage simulation

ß Selberrherr’s Model (IMPACT SELB)

ß Grant’s Model (IMPACT)

ß Crowell-Sze Model (IMPACT CROWELL)

ß Concannon (IMPACT N.CONCAN P.CONCAN)

ß Valdinoci Model (IMPACT VALDINOCI)

ß Toyabe Model (IMPACT TOYABE)

ß Band to Band Tunnelingß standard model with E (BBT.STD)

ß Klaassen’s model with E (BBT.KL)

ß narrow bandgap model (KAGUN KAGUP)


Generation Model Hierarchy (con’t)

ß Fowler-Nordheim Tunneling (FNORD)ß tunneling through insulators

ß used in EEPROM erasing

ß Hot Carrier Injection (HEI, HHI)ß energetic carrier transport through thin insulators

ß used in EEPROM programming

ß Thermionic Emission (EMISS.xx)ß used to model transport across potential barriers at

heterojunctions


Carrier Statistics Models

ß Boltzmann statisticsß default

ß Fermi-Dirac statistics (FERMI)ß high concentration effects

ß Incomplete Ionization (INCOMP)ß for dopant freezeout

ß required for low temperature simulations

ß extra model for heavy dopants in silicon (IONIZ)

ß Band Gap Narrowing (BGN)ß important in heavily doped regions

ß critical for bipolar simulations


Lattice Heating and Energy Balance Simulations

ß Lattice Heating activated by MODELS LAT.TEMP

ß Energy Balance activated by MODELS HCTE.EL HCTE.HO

ß Additional numerical techniques available

ß See Six Equation Solver Training for more details


Recommended Physical Model Selections

ß Recommended physical models for MOS type FETs:ß MODELS SRH CVT BGN

ß Recommended physical models for BJTs, thyristors, etc:ß MODELS KLASRH KLAAUG KLA BGN

ß Also include impact ionization to model breakdown:ß IMPACT SELB

ß In general do not switch on a model unless it is reallyneeded


Numerical Methods for Isothermal Drift Diffusion

ß All numerics settings chosen on METHOD statementß All structure/parameter specification must be before this

statementß All solution specification must be after it

ß Fully Coupled Method solves for potential and carrierscoupled (METHOD NEWTON)ß recommended for all cases even including SOI simulations

ß De-Coupled method solves potential and carrierssequentially (METHOD GUMMEL)ß faster for low current cases

ß Combined method (METHOD GUMMEL NEWTON)ß runs initial decoupled iterations and switches to coupledß GUM.INIT parameter controls the number of initial decoupled

iterationsß most robust (but slowest) method


ATLAS Syntax Guide

ß Recommended numerical settingsß METHOD NEWTON MAXTRAP=10 CLIMIT=1E-4


The Curvetracer: An Overview

ß Algorithm to enable ATLAS to trace out complex IV curves

ß Avoids user intervention in switching from voltage to currentboundary conditions

ß Ideal method for simulating snapback

ß Improves simulation of breakdown


The Curvetracer: Features

ß Dynamic Load Line Approach from “An Automatic BiasingScheme for Tracing Arbitrarily Shaped IV Curves”,Goosens et al., IEEE Trans CAD 1994, Vol 13, pp. 310-317

ß Automatic boundary condition selection

ß Automatic selection of voltage/current step size

ß A single SOLVE statement can be used to trace entirecurves

ß Only in DC mode. Transient and MixedMode already havesimilar capability


The Curvetracer: A Load Line Approach


The Curvetracer: Typical Applications

ß CMOS Latch-up

ß Snapback Effects

ß Breakdown Voltages

ß Second Breakdown


The Curvetracer: Syntax Guide

ß A single command is used to trace an IV curve SOLVECURVETRACE

ß The TRACE statement sets up the parameters for the curvetrace

ß When viewing results in TonyPlot the INT.BIAS rather BIASshould be used as the voltage axis of the IV curve


The Curvetracer: TRACE Parameters

ß CONTR.NAME is the name of the electrode to be ramped

ß STEP.INIT defines the initial voltage step on the ramped electrode

ß NEXT.RATIO specifies the factor used to increase the voltage step inareas on the IV curve away from turning points

ß MINCUR may be used to set a small current value above whichthe dynamic load line algorithm is used. Below thisSTEP.INT and NEXT.RATIO are used. Highlyrecommended

ß END.VAL is used to stop tracing if the voltage or current oframped electrode equals or exceeds END.VAL

ß VOLT_CONT denotes that END.VAL is a voltage

ß CURR_CONT denotes that END.VAL is a current


ATLAS Syntax Guide: Data Output

ß Two dimensional structure files use the syntax:ß OUTPUT EFIELD

ß SAVE OUTF=2D.STR

ß SOLVE OUTF=<filename>.str

ß All terminal characteristics are saved in logfiles:ß LOG OUTF=<filename>.str

ß To stop sending data to a logfile either QUIT or insertanother LOG statement or use LOG OFF statement


ATLAS Syntax Guide

ß Numerics:ß METHOD NEWTON CARRIERS=2 Use syntax for most cases

ß Use CARRIERS=0 for initial guesses

ß Use METHOD GUMMEL NEWTON for devices with floatingregions (e.g. SOI) This uses Gummel iterations to supply initialguess for Newton solver. It is more robust, but slower thanregular Newton.

ß Contents of method statement statement vary with solution typeß GUMMEL DAMPED

ß Newton AUTONR

ß Always TRAP


Sources of Error in Device Simulation

ß Inaccurate doping profiles

ß Insufficient physics

ß Unknown or inaccurate material parameters

ß Inaccurate model parameters

ß Reliance on empirically fitted models

ß Mesh induced errors

ß External effects


Solving Doping Profile Errors

ß This is the largest source of error for ‘small geometrydevices’ß Apply correction to doping if using SRP results

ß Use a process simulator

ß Account for CD biasing in mask edge locations

ß For further information see “Calibrating Process Simulators”


Solving Material Parameter Errors

ß Silicon parameters generally well-tuned already

ß For non-silicon materials, all parameters are subject totuning

ß Some parameters are substrate dependent and MUST betunedß e.g. minority carrier lifetime

ß Some parameters are process dependentß e.g. Qss


Solving Model Parameter Errors

ß Remember that most models are empirically fitted to aparticular set of data

ß Should be used only after other errors are handled

ß Most common parameters used are VSAT for saturationregion tuning and Impact Ionization parameters forbreakdown


Solving Mesh Errors

ß Avoid obtuse triangles in the current path or high field areas

ß Avoid discontinuities in mesh density

ß Ensure adequate mesh density in high field areas


External Effects

ß You are trying to compare measured data so you mustunderstand your measurement system. The simulation is ofa ‘perfect intrinsic device structure.”ß External resistancesß Long tracks in street structures, substrate contacts

ß Temperature. Simulator uses 300K. Do you?

ß Test systems use transients. Can be important for some deviceeffects

ß Variations in measured data. Best to tune to a curve of datarather that a single point.

ß Ensure extraction technique is the sameß e.g at least 4 ways to get MOS Vt


How to Tune Device Simulators

ß Problemß too many parameters to change

ß Run many simulationsß slow and tedious

ß Use Optimizerß easier, but may not converge in difficult cases

ß User VWFß using parameterized input decks


How to Tune Device Simulators (con't.)

ß Tacticß Eliminate or account for external effects

ß Measure what you can first to eliminate variables in the tuning

ß Thoroughly check all process related information

ß Use ‘unknown’ material parameters first

ß Use ‘major’ model parameters such as VSAT


Lattice Heating Simulations

ß Wachutka’s model of lattice heating accounts forß Joule heating

ß Heating/cooling from generation and recombination

ß Peltier and Thomson heating

ß Lattice heating is required for many reasonsß High power devices

ß ESD protection devices

ß SOI device operation

ß III-V material systems

ß Bipolar carrier injection processes

ß Accurate impact ionization

ß External heat sources


Tuning Lattice Heating Simulations

ß There are four additional calibration requirements whensimulating lattice heat flow1. Temperature dependent physical models

2. Temperature dependent thermal conductivities

3. Temperature dependent heat capacities

4. Thermal boundary conditions

ß Tacticß choose correct models 1

ß control material heating by 2

ß transient heat flow control with 3

ß apply external heat sources/sinks 4


Energy Balance Simulations

ß Energy balance simulations are required for todaystechnologies:ß Deep sub-micron CMOS transistors

ß Advanced high mobility materials

ß Accurate substrate current modeling

ß Velocity overshoot effects

ß Gate leakage currents

ß Transconductance modeling

ß Nonlocal transport phenomena

Reference: Simulation Standard article, Volume 6, Number 4, April 1995.


Tuning Energy Balance Equations

ß The relaxation times of the energy balance equations arethe critical parameter but are difficult to measure.1. Energy relaxation times

2. Energy dependent mobilites

3. temperature dependence of relaxation times

4. Energy dependent impact ionization

ß Tacticß apply previous drift-diffusion calibration strategies

ß modify 1 to control velocity overshoot

ß 2 is then coupled to 1

ß 3 is uncharacterized but implemented for research purposes

ß specify energy relaxation length for 4


Examples of Calibration Parameters

ß Threshold VoltageGate workfunction (WORKF) CONTACTSurface states (QF) INTERFACE

ß Subthreshold SlopesSurface states (QF) INTERFACEInterface defect traps INTTRAPDiscrete Bulk defect traps TRAPDistributed bandgap defect traps DEFECTS

ß ThetaPhysical models (MOS) MODELSMobility equations coefficients (DELTAN.CVT) MOBILITY

ß Bipolar GainPhysical models (BIPOLAR) MODELSMobility equations coefficients (MUN, MUP) MOBILITYRecombination coefficients (TAUN0) MATERIALExtrinsic resistances (RESISTANCE) CONTACTSurface recombination (SURF.REC) CONTACT


Examples of Calibration Parameters (con't.)

ß I - V CurvesPhysical models (MOBILITY, BGN) MODELSMobility equations coefficients (VSAT) MOBILITY

ß Leakage CurrentsPhysical models (TUNNELING) MODELSRecombination coefficients (TAUN0) MATERIALTrap density ( see subthreshold slope)

ß BreakdownCurrent level (Vt, Theta, Gain, etc)Impact ionization coefficients (SELB, AN1, BN1) IMPACT

ß EPROM Write/ EraseFloating contacts (FLOATING) CONTACTPhysical models (PROGRAM, ERASE) MODELSTunneling equation coefficients (IG. ELINR) MODELSCoupling capacitances CONTACT


Examples of Calibration Parameters (con’t)

ß Lattice HeatingPhysical models (LAT.TEMP) MODELSThermal conductivities (TC.A, TC.B, TC.C) MATERIALHeat capacities coefficients (HC.A, HC.B, HC.C) MATERIALThermal boundary conditions THERMCONTACT

ß Energy BalancePhysical model (HCTE) MODELSRelaxation times (TAUREL.EL) MATERIALImpact ionization coefficients (LREL.EL) IMPACT

3D Device Simulation with ATLAS


3D Device Simulation Modules in ATLAS

ß Device3D - Drift diffusion simulator with standard 2D modelsavailable

ß Blaze3D - III-V and II-VI simulator

ß Giga3D - Self-consistent lattice heat flow solution

ß MixedMode3D - Missed Spice and Device 3D simulation

ß Quantum3D - Quantum correction theory in 3D

ß TFT3D - Amorphous Poly Device simulation

ß Thermal3D - Heat dissipation only simulator


Device 3D - 3D Silicon Device Simulator

ß Solves Poisson’s and electron/hole continuity equations

ß Prismatic based mesh structures

ß dc, ac and transient analysis modes

ß Choice of numerical solvers

ß Comprehensive physical modelsß mobility

ß recombination

ß generation

ß carrier statistics

ß R, L and C lumped elements

ß C-interpreter functionality


3D Device Simulation

ß Giga 3Dß Giga 3D contains most the functionality of the 2D Giga but works

with the 3D products

ß This allows modeling of heatflow and self heating effects in 3Ddevices

ß The only functionality not supported in this version of Giga 3Dthat is supported in 2D is the BLOCK method


Lattice Heating in 3D Using Giga3D

ß Isosurfaces oftemperature in a powerdiode with currentcrowding into the anode



ß MixedMode3Dß This improvement allows simulation of 3D devices embedded in

lumped element circuits

ß MixedMode3D contains all the functionality of 2D MixedModesimulator


MixedMode3D

ß Circuit schematic for a GTOthyristor

ß The GTO element is simulatedusing 3D device simulation


MixedMode3D

ß Currents in the GTOthyristor during turn-off through externalcircuit


SEU in Memory Cell Using MixedMode3D

ß Voltage drop on mode ofSRAM cell during singleevent upset

ß Circuit boundaryconditions are requiredto model the cellbehavior

ß 3D device simulation isrequired to model theSEU



ß Blaze 3Dß This version accounts for spatial variations in bandgap due to

variations in material composition in 3D This version supportsall the same models as are supported in 2D Blaze with theexception of thermionic emission at heterojunctions and energytransport

ß This version also does not support compositional variation in thez direction


HBT in Blaze3D

ß 3D super self alignedSiGe HBT structurecreated and meshedusing DevEdit3D

ß Emitter and basecontacts arepolysilicon

ß A section of oxideisolation is removedfrom the view toreveal the confinedSiGe base region withdenser mesh


HBT in Blaze3D

ß (a) cut plane through 3DHBT structure at onset ofavalanche breakdown.Note the concentration ofimpact ionization in thecenter of the n-SiGecollector extension region.

ß (b) HBT collectorbreakdown characteristic.(c) cut line through2D section showing graphof impact ionization ratewith depth under polyemitter stripe.


HEMT in Blaze3D

ß 2D cut plane taken from aBlaze3D solution for the 3DHEMT during a negativegate bias transient

ß The section is along themajor axis of the resistiveT-gate and shows thepotential gradient along itslength

ß The channel conduction(particularly the parasiticconduction in the AlGaAs)is consistent with the gatepotential profile



ß TFT 3Dß This model allows modeling of poly and amorphous

semiconductor devices such as TFTs in 3D

ß This model has all the functionality of the 2D TFT simulator


TFT 3D

ß 3D device simulationof high performanceTFT device



ß Quantum3Dß This allows modeling of the effects of quantum confinement using

the quantum moment approach

ß This model has all the functionality of the 2D Quantum model


SEU in Device 3D

ß More controlparameters forradial distributionand transientintensity of SEUpulses have beenadded


SEU in MixedMode3D

ß Effect of an alpha particlestrike on an invertercircuit simulated withMixedMode 3D

ß The memory bits areseen to switch during theevent

ß Data corruption such asthis could cause criticalfailure of the circuit

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