Application of the RADSAFE Concept

Transcription

1 Application of the RADSAFE Concept Vanderbilt University R.A. Reed, R.A. Weller, R.D. Schrimpf, L.W. Massengill, M.H. Mendenhall, K. M. Warren, D.R. Ball, C.L. Howe, J.A. Pellish, E. Montez, A. Kalavagunta, A. Tipton, M. Alles, B. Sierawski, M. McCurdy, and A. Witulski, NASA/GSFC K.A. LaBel, M. Xapsos, J. Lauenstein PR&T Jim Pickel EMPC Tom Jordan Sponsors: NEPP, DTRA, AFOSR, and others

2 Figure 2.4 Single Event Effects (SEE) Two Ionization Cases: Incident particle generates electron-hole (e-h) pairs SEE modeling challenges we are currently addressing with RADSAFE: Detailed device and circuit response Direct Technology Computer Aided Design (TCAD) + spice Secondary particles adds to generated e-h pairs Commercial tools unable to predict indirect ionization case On-orbit rate prediction Indirect Approximation methods P.J McNulty, Notes from 1990 IEEE Nuclear and Space Radiation Effects Conference Short Course Failure of models when applied to emerging technology

3 TCAD Simulation of Radiation Event

4 Classical On-Orbit Direct Ionization SEE Rate LET Spectra Cross S ection Over LET IRPP and Critical Charge ED CRITICAL ENERGY DEPOSITION (ED) SEE On-Orbit Rate = CREME96 Or similar computer code! SV Omnidirectional LET Flux

5 IR Focal Plane Arrays SiGe Heterojunction Bipolar Transistor Silicon On Insulator RH CMOS

6 30 Mev, 0 Degrees Total IR Focal Plane Arrays model 1000 hits data scaled to 1000 hits model 1000 hits 1000 Test Technology: SiGe E+03 1.E+04 1.E+05 1.E-05 1.E-06 Frequency 2 Device Cross Section (cm ) Frequency SiGe Heterojunction Bipolar Transistor Const LET 1.E E Mev, 67 Degrees Total data scaled to 1000 hits Solid Line is Expected Data Trend From Classical Model Actual Data Disagrees 1.E+02 1.E+03 1.E-07 With Classical Model Hit Size (e) 1.E+04 Hit Size (e ) 1.E Effective LET (MeV-cm Silicon On Insulator 2 Device Cross -Section (cm ) /mg) DUT #5 Lot#1 DUT #3 Lot#1 Existing Model Would Predict Solid Line E CMOS 1.E Classical Model Does Not Predict Low LET Upsets E Proton Angle of Incidence (Degrees) Const

7 The RADSAFE Concept

8 Geometry and Material Description Radiation Environment Models Energy Deposition (ED) RADSAFE is an Integrated Modeling Concept Convert ED to initial conditions for electronic response First-order approximation models Detailed response models Device and Circuit Response

9 Geometry and Material Description Radiation Environment Models Energy Deposition (ED) RADSAFE is an Integrated Modeling Concept Convert ED to initial conditions for electronic response First-order approximation models Detailed response models Device and Circuit Response

10 Geometry and Material Description Radiation Environment Models Energy Deposition (ED) RADSAFE is an Integrated Modeling Concept Convert ED to initial conditions for electronic response First-order approximation models Detailed response models Device and Circuit Response

11 Geometry and Material Description RADSAFE is an Integrated Modeling Concept Radiation Environment Models Energy Deposition (ED) Convert ED to initial conditions for electronic response Model Development and Implementation Depends on: Technology Radiation Environment Particular Radiation Effect Desired Output First-order approximation models Device and Circuit Response Detailed response models

12 The RADSAFE System: Current Focus MRED - Monte Carlo Radiative Energy Deposition tool Developed at Vanderbilt University Based on Geant4 Run time selectable physics list Python interface Highly Flexible output

13 Single Event Simulation Structure: Si diode, a 5 µm cube. Events: GeV/nucleon 12 C. Pre-selection: >1.5 MeV in a 1 µm cube, 0.5 µm below the junction. 267 candidate events.

14 Ion Tracks for Event e - /cm e - /cm 3

15 Radiation event: Meshing Event 267 Slice at y = 1.0 µm Slice at x = 0 µm

16 Example #1: SEUs in SRAMS 10 µm

17 RADSAFE on SEE in SRAMs TCAD Cell Structure: SRAM Cell Single Charge Deposition in TCAD: Ne+W Event SEE simulation Mixed mode SRAM Cell Upset Geant4 Geometry and 523 MeV Neon Event MRED Energy Deposition for 10 8 Events

18 Geometry and Material Description Radiation Environment Models Energy Deposition (ED) RADSAFE is an Integrated Modeling Concept Convert ED to initial conditions for electronic response First-order approximation models Detailed response models Device and Circuit Response

19 The Cross Section Curve Histogram of events for each ion as an integral cross section for a given deposited charge (pc) Q crit of 1.21 pc determined for TCAD simulations Impact of ion-ion scattering on SEE test methods and on-orbit rate prediction approaches? 1.21 pc Cell Level Q crit Predicted Cross Sections 1.E-07 1.E-07 Integral Cross Section (cm 2 ) 1.E-08 1.E-09 1.E-10 1.E-11 1.E-12 1.E-13 1.E-14 1.E-15 Cross Section (cm 2 /bit) 1.E-08 1.E-09 1.E-10 1.E-11 1.E-12 1.E-13 1.E-14 1.E-15 Simulation Experiment Deposited Charge (pc) LET (MeV*cm 2 /mg)

20 Example #2 Single Event Transients (SETs) in IR FPAs Figure 2.4 Two Ionization Cases: Incident particle generates electron-hole (e-h) pairs Direct Secondary particles adds to generated e-h pairs Indirect Single pixel of an IR FPA P.J McNulty, Notes from 1990 IEEE Nuclear and Space Radiation Effects Conference Short Course

21 Geometry and Material Description Radiation Environment Models Energy Deposition (ED) RADSAFE is an Integrated Modeling Concept Convert ED to initial conditions for electronic response First-order approximation models Detailed response models Device and Circuit Response

22 Radiation Effects Challenges for Space Based IR Sensing Exposure to galactic cosmic rays and solar particle events NASA missions require very low noise and very long integration time 10 electrons or less Hundreds to thousands of seconds Single event transients increase output level of individual pixels Transients are latched in until reset at end of integration Large events can be filtered Small events compromise scene data acquisition Charge spreading to multiple pixel

23 Proton-Induced Transient Testing of IR Focal Plane Arrays NASA testing of IR FPA Proton testing at 30 MeV

24 Charge Spreading Mechanisms surrounding material diffusion region HgCdTe active layers depletion region In column Si ROIC active Layer

25 Charge Spreading Mechanisms surrounding material 1 diffusion region depletion region HgCdTe active layers In column Si ROIC active Layer Direct Ionization

26 Charge Spreading Mechanisms surrounding material 1 diffusion region HgCdTe active layers 2 depletion region In column Si ROIC active Layer Diffusion of Carriers

27 Charge Spreading Mechanisms surrounding material 1 diffusion region 4 HgCdTe active layers 3 2 depletion region In column Si ROIC active Layer Indirect Ionization

28 Energy Deposition Modeling via MRED 30 MeV protons 3.0E MeV Proton Energy Deposits in HgCdTe Detector Volume 2.5E E+04 # Events 1.5E E E E E E E E E E E+05 Energy Deposited (ev)

29 Quasi Carrier Transport Model (NASA s REACT) Drift and diffusion charge collection models applied depending on particle location Charge carrier history ends when either collected or recombined Charge distributed to pixels across array in accordance with drift and diffusion Diffusion Region HgCdTe High Electric Field In column Si ROIC active Layer

30 RADSAFE Predictions and Experimental Data 1000 model 1000 hits data scaled to 1000 hits Const LET 100 Frequency E+02 1.E+03 1.E+04 1.E+05 Hit Size (e)

31 Vision for Complex Response Modeling IR FPAs 1.E+00 Flux (#/cm2 MeV) 1.E-01 1.E-02 1.E-03 GCR Min 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 Energy (MeV)

32 Conclusions RADSAFE concept relies on a revolutionary, modular computational system for predicting the radiation response of electronic devices, circuits, and systems from detailed device structure, circuit topology, and characteristics of the radiation environment. RADSAFE goals: to be informed by the best available physics, implemented by robust algorithms, enabled by supercomputer technology, and calibrated by data. RADSAFE will be used to uncover basic mechanisms for radiation induced effects. Enable development of approximation models and test methods for radiation effects in emerging technologies Technological Challenges: Development of framework for integrating simulation tools Refinement/development of physically-based models for key phenomena (e.g., interaction of heavy ions with very heavy nuclei) Verification and validation of tool suite through targeted experiments Efficient implementation of tools for massively parallel high performance computing systems