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Device Simulation for SingleEvent Effects

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It all pales in comparison to.... Objectives. Provide device simulation environment for rad-hard applications ... P = Process / D = Device 90% code shared ... – PowerPoint PPT presentation

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Title: Device Simulation for SingleEvent Effects


1
Device Simulation for Single-Event Effects
  • Mark E. Law
  • Dan Cummings, Nicole Rowsey
  • SWAMP Center

2
2006 Basketball Champs
3
2006 Football Champs
4
2007 Basketball Champs
5
It all pales in comparison to.
6
Objectives
  • Provide device simulation environment for
    rad-hard applications
  • Address Rad-Hard specific issues
  • Physics - strain
  • Numerics - automatic operation
  • Coupled Device / Defect Simulations

7
Outline
  • Background - FLOODS Code
  • Numeric Issues and Enhancements
  • Physical Issues and Enhancements
  • Conclusions

8
FLOOPS / FLOODS
  • Multi-dimensional, Object-oriented codes
  • P Process / D Device 90 code shared
  • Scripting capability for PDEs - Alagator
  • Commercialized - ISE / Synopsis
  • Sentaurus - Process is based on FLOOPS
  • Licensed at over 300 sites world-wide
  • Short Course at Vandy Jan. 11-12

9
What is Alagator?
  • Scripting language for PDEs
  • Models are accessible, easily modified
  • Equations are split
  • Node pieces (recombination, time derivative)
  • Element pieces (current, fields)
  • Pieces are vectorized
  • 128 pieces in tight BLAS loops for performance
  • Operations are broken down in scripting
  • Precomputation and Caching automatic
  • Overall CPU linear in of pieces

10
What is Alagator?
  • Example use of operators for diffusion equation
  • Ficks Second Law of Diffusion
  • ddt(Boron) - 9.0e-16 grad(Boron)
  • ?C(x,t) / ?t D ?2C(x,t) / ?x2
  • All physics is defined on the command line
  • Rapidly evolve models for new devices / materials
    / physics

11
Outline
  • Background - FLOODS Code
  • Numeric Issues and Enhancements
  • Physical Issues and Enhancements
  • Conclusions

12
Object Oriented
  • Derived Specific Geometry Elements
  • Common properties so code is independent

Element Class
Volume
Face
Edge
Node
Face
2 -Edge
3 -Edge
Tri
Quad
13
Anisotropic Grid - Mixed Elements
  • For many reasons, quads are better shapes for
    device simulation
  • Rectangular region created at the command line
  • Refinement creates mixed elements and terminated
    lines
  • Assembly runs on generalized elements

14
ElementInfo Derived Classes
  • NodeInfo Base Class - for nodes
  • EdgeFluxInfo - Edge Flux Terms
  • ReflectInfo - Boundary conditions, contacts
  • InterfaceInfo - Interface layers and Material
    boundaries
  • ElementInfo - Base Element Assembly Class
  • Derived Classes - Allow more element types
  • EleEdgeInfo (1D)
  • EleTriInfo, EleQuadInfo (2D)
  • EleTetInfo (3D) (will add EleBrickInfo)

15
Elastic Assembly - Element Assembly
  • Data Comes from ElementInfo Class
  • All are vectors - 128 long
  • Code Fragment of Assembly
  • for(i 0 i lt BDim i)
  • for(j 0 j lt BDim j)
  • sij 0.0
  • for(l 0 l lt Ddim l)
  • for(k 0 k lt Ddim k)
  • //multiply BT, D, B
  • tmp.Mult(ev.BM(k, i),ev.BM(l, j),
    Dkl)
  • sij tmp
  • sij ev.Size()

16
Outline
  • Background - FLOODS Code
  • Numeric Issues and Enhancements
  • Physical Issues and Enhancements
  • Conclusions

17
Philips Unified Mobility Model
  • Unifies the description of majority and minority
    carrier bulk mobilities
  • temperature dependence
  • electronhole scattering
  • screening of ionized impurities by carriers
  • clustering of impurities

18
Bandgap Narrowing
pn diode band diagram
Unified apparent bandgap narrowing
ND
NA
is a function of doping level
19
Normal Field Computation
  • Dot, magnitude, cross operators
  • Compute gradient of scalar terms, vector
    operations
  • dot(DevPsi, x)
  • Determines magnitude of the gradient of the first
    argument
  • In the direction of the second
  • dot(DevPsi, x) - vertical (channel) field
  • dot(DevPsi,qfn) / Magnitude(qfn)
  • Produce field in the current flow direction
  • dot(DevPsi, x) - vertical field for mobility
    reduction
  • Leads to strain tensor operations

SiO2
Current
Field
20
Mobility Degradation at Interfaces
perpendicular field
Surface Roughness
Acoustic Phonon
21
Anisotropic Mobility Enhancement
  • PMOS (Lgate65 nm)
  • Mobility enhanced by a factor of 2.5 in the
    lateral direction uniformly
  • DC Drain curves with the gate at -1.0V for a
    65nm and 250 nm gate length, with and without a
    strain enhanced mobility in the lateral
    direction.

22
Anisotropic Mobility Transient
  • PMOS (Lgate65 nm)
  • Mobility enhanced by a factor of 2.5 in the
    lateral direction uniformly
  • To observe strain differences, assumed no
    recombination
  • Charge was deposited along a vertical line
    through the drain junction
  • Charge cloud was assumed to be Gaussian in the
    lateral direction and uniform vertically
  • Issue total charge collected is not the same
    for both cases

23
Shockley-Read-Hall Recombination
Diodes with different carrier lifetimes
(increasing forward bias)
Nt trap density can be set as a function of
distance
24
Example - Modern USJ Formation
  • State of the Art USJ Technology
  • Si Preamorphization
  • Carbon Implant at End of Range
  • Significant increase in junction leakage (but
    still small compared to S-D leakage)
  • Large local recombination centers at C

Felch, et al., INSIGHT 2007
25
Example - Modern USJ Formation
  • Centered SRH increase at C sites
  • Order of magnitude increase in junction leakage
    (measured was larger)
  • 65nm MOS transistor (larger technology node than
    this is aimed at)
  • Single event response w/ and w/o carbon

26
Summary
  • Generalized Element Assembly, Refinement
  • Need to work on bricks, unrefinement
  • Added Physical Operators
  • Directional terms included
  • Add Strain
  • Built Standard MOS models for distribution
  • Lombardi, Phillips, Bandgap, Recombination
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