Applications of Monte Carlo Radiation Transport Simulations Techniques for Predicting Single Event Effects in Microelectronics Robert A. Reed Vanderbilt University robert.reed@vanderbilt.edu Vanderbilt Team: Robert Weller, Marcus Mendenhall, Brian Sierawski, Kevin Warren, Ronald Schrimpf, Mike King, Mike Clemens, Elizabeth Auden, Sabra, Mohammad, Aritra DasGupta, Nathaniel Dodds NASA/MSFC Collaborators: Jim Adams, John Watts, Abdulnasser Barghouty SLAC Collaborators: Makoto Asai, Koi Tatsumi, Dennis H. Wright Vanderbilt Sponsors: NASA Electronics Parts and Packaging Program NASA Autonomous Systems and Avionics Project DTRA Basic Research Program DTRA Radiation Hardened Microelectronics Program

Outline Introduction Brief history of SEE Rate Predictions Predictions SEEs Using Monte Carlo Radiation Transport Techniques (VU) Transporting radiation environments (MSFC) CRÈME website (MSFC and VU) Characteristics of the radiation event and the

Transients from Single Particle Event Charge Generation ± ~ ps Energy Deposition Charge Collection ± ps to s Transient Current Pulse Ei Eo fs to ps Time Time Soft Error Examples: Single Event Transient: A current pulse occurring at a circuit node due to single energetic particle event Single Event Upset: A change in a circuit’s logic state induced by a single energetic particle event

Analytical On-Orbit SEE Performance Predictions Space Environment Ground Testing ANALYTICAL RATE PREDICTION MODELS: Rectangular Parallelepiped (RPP) model Bendel Model (both are circa 1980) https://creme96.nrl.navy.mil/ On-Orbit SEE Rate

Scaling Trends in Electronics Single-Event Upset and Single-Event Transient Hardness Have Worsened with Scaling SEE have recently become a substantial Achilles heel for the reliability of even earth-based advanced CMOS technologies. As the amount of charge that represents stored information has dropped lower and lower, so the sensitivity of CMOS devices to single-particle charge collection transients has increased. In fact, single-event upsets (SEUs) are the single largest contributor to device soft failure (i.e., recoverable) rates in many of today’s CMOS technologies. In addition, as operating speeds have soared, increased sensitivity of circuits to single-event transients (SETs, which are short-lived single-event induced current/voltage transients that do not directly cause upsets but that may propagate through logic circuitry) has followed. In fact, SETs in digital circuits may set fundamental limits on the operating speed of radiation-hardened integrated circuits. SEE are therefore a significant concern not only for electronics operating in space environments, but also for high-altitude and even terrestrial systems that must operate very reliably. Scaling Trend Many newer ICs also exhibit complex failure modes such as single-event functional interrupts (SEFIs) that may require device reconfiguration or reset for recovery. P. E. Dodd, et al., RADECS 2009 Short Course, Brugge, Belgium

New SEE Challenges Complicated charge-collection volumes Ion tracks larger than device sizes Overlayers affect device response One event may affect multiple cells

Breakdown of Analytical Models Proton effects in SOI based memories Early experimental work on optocouplers & optical links show need for new tool R.A. Reed, et. al, IEEE Trans. Nuc. Sci., vol. 49, no. 6, Dec. 2002, pp. 3038 – 3044. RADHARD CMOS SRAM R.A. Reed, et. al IEEE Trans. Nuc. Sci., vol. 48, no. 6, Dec. 2001, pp. 2202 – 2209. Heavy Ion Effects 90 nm DICE latch K.M. Warren, et. al IEEE Trans. Nuc. Sci., vol. 48, no. 6, Dec. 2005, pp. 2125 – 2131. K. M. Warren, et. al, IEEE Trans. Nuc. Sci., vol. 54, no. 6, pp. 2419 - 2425, 2007. Heavy Ion Effects in SiGe HBTs R.A. Reed, et. al IEEE Trans. Nuc. Sci., vol. 50, no. 6, Dec. 2003, pp. 2184 – 2190

A New Paradigm: Classical models no longer capture all physical processes that drive the response of modern technology to ionizing radiation Solution: It is possible to predict single event effects from first principles given sufficient knowledge of device structure and the interaction of radiation with matter

Monte Carlo Method Using High Performance Computing National Electrostatics Corporation http://www.icknowledge.com/trends/p4(2).jpg Predicted Responses After E. G. Stassinopoulos and J. P. Raymond, Proc. of the IEEE 76, 1423 (1988)

Key Technology: MRED Python First generation Python/Geant4 application MRED: Monte Carlo Radiative Energy Deposition First generation Python/Geant4 application Contains the best available physics from various sources: Geant4 PENELOPE2008 CEM03 LAQGSM PHITS Geant4 MRED C++ SWIG Python

MRED+PENELOPE2008: Electrons in Silicon Silicon Cube 10 × 10 × 10 nm3 Penelope2008 extension State-of-the-art electron, positron and gamma transport code Gold-standard for low energy ionizing electromagnetic interactions with atoms and solids. Simulate 250 eV electrons 100 particle raster

Trends in Advanced Technology Nodes Decreasing feature sizes are leading to an overall reduction in critical charge IBM 65 nm SOI critical charge around 0.14 fC – 0.24 fC (1500 electrons) [1] Recent publication from IBM details a 22 nm SOI technology node [2] SRAM cell area of 0.1 μm2 Estimated critical charge of 0.08 fC, approximately 1.8 keV (500 electrons) 0.1 μm2 SRAM after [2]. Decreasing feature size has resulted in overall reduction of Qc in SOI circuits – cite example. Highlight IBM 22 nm technology – SRAM areal density of .1 um^2. By estimating the gate capacitance we were able to approximate the critical charge for this technology node – 0.08 fC – 1.8 keV. [1] Rodbell, K.P., et al, "Low-Energy Proton-Induced Single-Event-Upsets in 65 nm Node, Silicon-on-Insulator, Latches and Memory Cells," IEEE  Trans.  Nucl.  Sci. Dec. 2007. [2] Haran, B.S. et al, "22 nm technology compatible fully functional 0.1 μm2 6T-SRAM cell,” IEDM Dec. 2008. TEM of 22 nm devices after [2]. King, TNS 2010

Electron Events in 50 × 50 ×50 nm3 Si Cube Incident δ-ray Scattering events Energy Deposited = 2.1 keV E.D. = 2.6 keV Both Events Deposit Sufficient Energy to Upset 22 nm SRAM ! King, TNS 2010

280 MeV Fe Strike 28 GeV Fe Strike δ-rays δ-rays SVs SVs Sensitive Volumes Graphical representation of the preveious slide. 28 GeV Fe has a very irratic track structure – due to highly energetic delta-rays – 280 MeV Fe has a track structure more tightly focused around the ion track. King, TNS 2010

Proton Test Structures 300 μm × 780 μm area

Data Analysis Charge collected and histogrammed 3. Data analyzed as a function of charge. 2. Reverse Integrated

Effect of Tungsten overlayers Tungsten (W) is seen to increase charge collection cross section for high collected charge. No difference in charge collection cross section for charge below ~0.5 pC. Presence of W can cause SEE in devices that would otherwise not see proton-induced SEE.

Monte Carlo Simulations Monte Carlo Radiative Energy Deposition tool (MRED) Geant4-based simulation tool Provides option of selecting nuclear physics model Geant4 Bertini Cascade Cascade-Exciton Model (CEM) Validate physics model, then investigate proton-induced charge deposition mechanism

Proton-Silicon Reactions Geant4 Bertini Cascade has a branching ratio orders of magnitude lower than other models for proton-induced fission in W, and thus drastically under-predicts the energy deposition CEM hadronic physics model in MRED integrated with Geant4 transport and energy deposition models agrees well with experiment

Hadronic Physics Model Comparison

Low-Energy Proton Upsets Previous work reported data collected by Vanderbilt and NASA Goddard on TI 65 nm bulk CMOS process [Sierawski, TNS 2009] Consistent with evidence of proton direct ionization contributing to single event upsets (SEUs) reported for IBM 65 nm SOI process [Rodbell, TNS 2007][Heidel, TNS 2008] 3-4 orders of magnitude increase in cross section below 2 MeV Cross sections consistent with nuclear Reaction events for Ep > 10 MeV Sierawski, TNS 2009

Heavy-Ion SEU Cross Sections Heavy-ion tests at TAMU revealed LET threshold less than 0.5 MeV-cm2/mg confirming proton sensitivity Low-LET cross sections were used to calibrate an MRED multiple sensitive volume model High-energy ions provide consistent energy deposition through a well-known stopping power thus characterizing the charge collection σion SBU MBU Sierawski, TNS 2009

σproton Proton Predictions Proton SEU cross sections were predicted for Ep < 32.5 MeV Transport codes model the stochastic energy deposition and the sensitive volume model captures the process of charge collection Simulations include all relevant physical mechanisms of energy loss with no adjustable parameters σproton Sierawski, TNS 2009

Terrestrial Environment Neutrons: 13 cm2hr-1 for E > 10 MeV Muons: 60 cm2hr-1 for P > 0.35 GeV/c Cosmic rays create showers (“zoo”) of secondary particles in the atmosphere Neutrons, while numerous, rarely interact with material leading to single event upsets Muons are the most abundance particle at sea level Stopping power similar to protons Sierawski, TNS 2010

Preliminary Simulations MRED Monte Carlo simulations indicated potential for upset from muon direct ionization Technology scaling (assuming same sensitive volume dimensions) will increase susceptibility to terrestrial protons, muons Spectra will be moderated by concrete, buildings, etc. 45nm 65nm Technology scaling

Single Event Upsets Trend in upsets is indicative of direct ionization Peak occurs when beam is tuned to stop in device active region At higher energies, stopping power is too low for upset At lower energies particles range out Kinetic energy distributions were determined by simulation and related to the abscissa for SEU probability Two other SRAMs from a different vendor showed similar response First experimental evidence of single event upsets from muon ionization! Sierawski, TNS 2010

Applications of MRED Space Applications: Integration of various physics models from various sources for comparison to experimental data Identify strengths and weaknesses of model Monte Carlo Based SEU Rate Predictions of NASA, DTRA, BAE, Boeing Simple cuboid sensitive volume model Multiple geometry sensitive volume model Spice-in the loop Transients in silicon focal plane arrays electron environments behind spacecraft shielding Low LET (< 1 MeV-cm2/mg) effects Multiple bit upset in highly scale (90nm and 65 nm) CMOS technology Simulation of SEU Cross-Sections Using MRED Under Conditions of Limited Device Information Prediction of SEGR in power MOSFETs Dose enhancement effects CREME-MC website Terrestrial applications of MRED Assessing Neutron Induced Multi-bit upset Muon single event upsets Alpha particles from packaging

Galactic Cosmic Ray Flux and Dose Using GEANT4/HZETRN 95 John Watts University of Alabama Huntsville/CSPAR John.w.watts@nasa.gov (256)961-7696 February 5, 2010

Galactic Cosmic Ray Dose and Flux Transporting the Full Galactic Cosmic Ray Flux (protons through uranium and energies for 10 MeV to 105 MeV) is computationally expensive for complex geometries. The 3-D space craft geometry is in GDML format extract from files created by ST-Viewer which can read CAD STEP files. We are investigating developing a replacement for ST-Viewer using the open source library, JSDAI, which provides an API for processing STEP files. To make the problem tractable GEANT4 is used to generate and output a set of vectors sampling all directions about a point in a 3-D geometry with material description and distance through each volume encountered using geantinos. Java script reads a single vector of multiple materials and transport the input galactic cosmic ray spectrum along the vector and output a file of the fluxes and dose at the end of the vector.

CRÈME Capabilities Vanderbilt / MSFC developing a website that will provide certain functionalities to the user community CREME86 CREME96 CRÈME-MC (limited Monte Carlo) Monte Carlo Provides: Multilayer structures and materials Multiple sensitive volumes Effects of track size and nuclear interactions Accelerated ground test simulation On-orbit predictions Evaluates models for space radiation environments Natural spectra Transported spectra

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Proton-W Reactions Proton-W secondary particles sorted by LET value Secondaries with LET > 25 originate from proton-induced fission Isotropic emission Max LET: 42 MeVcm2/mg High LET particles have a range from 4 μm to 22 μm Proton-induced fission rare for low energy protons