# Presentation: 849366

## RHBD 12T/2m FF Analysis and Soft ErrorRate Prediction 

- Kevin Warren/Brian Sierawski
- The Institute for Space and Defense Electronics

## Hardened Latch Heavy Ion Data

- Clearly the data do not lend themselves to the standard CRÈME RPP model fitting
- The weibull fit shown to the right produces a range of error rates in CRÈME depending on the SV depth
- 0.5m-9.6E-10 /bit-day
- 1.0m-4.3E-10 /bit-day
- 2.0m-1.27E-10 /bit-day
- 3.0m-5.59E-11 /bit-day
- Effective cross section and LET have no real meaning in this circumstance.

- The points at each effective LET
- represent different roll angles.

## Simulation and Analysis TechniqueIdentifying the Mechanism of UpsetFinding a Way to Predict a Soft Error Rate

## Background and Simulation Flow

- Vanderbilt uses RADSAFE – a suite of software tools to analyze single event phenomena
- At the core is MRED – a physics based (GEANT4 libraries) Monte-Carlo simulation tool
- Sophisticated environmental sampling algorithms and energy tracking capability.
- _Begin with the circuit analysis_

**Sample **
**Particle (Z,A,E),**
**Directional Vector**
**(particle beam or **
**environment**

**Transport Through**
**Solid Model**

**Check to see how**
**much energy is**
**deposited in the **
**appropriate regions**

**Compare to critical**
**Charge requirements**

**Count upset if enough**
**charge is collected **

- Simplified MRED Flow

## Spice Analysis – Identifying Sensitive Node Pairs

- Determine what nodes are sensitive in the circuit
- Determine how much charge must be collected on node combinations to cause SEU

## Spice Analysis

- Multiple combinations of charge/discharge exist that could upset the cell.
- Drain N0/Drain N2
- Drain N0/Drain P1
- Drain N0/Drain P3
- Drain N2/Source P1
- Drain N2/Source P3
- Drain P1/Drain P3
- In alternate logic state, similar combinations are possible.
- Evaluate these possibilities in Spice

## Spice Level Upset Analysis

**Steps to determining Q****crit**** thresholds**
- Sink or source current on node(s) to investigate
- Using double exponential, establish minimum drive current to drive nodes to opposite rail voltage
- Select reasonable time constants for rise, hold, and decay (compare to TCAD results). Currently, tc are in 10’s of picoseconds.
- Increase or decrease time constants or decrease current magnitude to find minimum conditions for SEU.
- Record total charge

- Note that P1 and P3 drain nodes can be pulled high via parasitic bipolar conduction.
- B.D. Olson, D. R. Ball, K.M. Warren, L.W. Massengill, N.F. Haddad, S.E. Doyle, D. McMorrow, “Simultaneous Single Event Charge Sharing and Parasitic Bipolar Conduction in a Highly-Scaled SRAM Design,” IEEE Trans. Nuc. Sci., Vol 52, no. 6, December 2005. P/ 2132.

## Spice Level Upset Analysis

**The critical charge for any node pair is now modeled as a continuum of possible solutions rather than the “corner model” approach previously used (**R. Velazco, et al., “SEU-Hardened Storage Cell Validation Using a Pulsed Laser,” IEEE Trans. Nucl. Sci., Vol 43, No 6, 1996.  p 2843)
**For each sensitive transistor pair Q****1**** and Q****2****, solutions of the form Q(coll)****1****Q(coll)****2**** = constant were monitored (lower right)**
**Cutoffs for the minimum collected charge were enforced to eliminate cases in which extremely large amounts of collected charge on Q1 or Q2 could produce false upsets**
**The constant was the average value of the product of each transistor pair’s critical charges, determined from SPICE analysis**

- From Velazco, et al.

- Hypothetical solution space
- Using Q(coll)1*Q(coll)2=Constant

## Simulation Flow

-  ****Circuit response understood
-  _Calorimetry (Sensitive Volumes)_
- X Particle Transport
- X Calibration
- X Environment and Rate

**Sample **
**Particle (Z,A,E),**
**Directional Vector**
**(particle beam or **
**environment**

**Transport Through**
**Solid Model**

**Check to see how**
**much energy is**
**deposited in the **
**appropriate regions**

**********Compare to critical**
**Charge requirements**

**Count upset if enough**
**charge is collected **

## Calculated Collected Charge – Sensitive Volumes

- The amount of charge generated in silicon is related to the energy deposited [aka calorimetry -> 22.5 MeV/pC]
- The challenge lies in determining how much of the generated charge makes it to the collecting node.
- RPP (CREME96) model assumes a region in which 100% of the generated charge results in collected charge.
- RPP model is not intended to model effects of coincidence or sharing of charge between nodes (although it could conceivably be used to reproduce experimental data but it’s non-physical).
- In MRED, multiple RPP structures are generally used to model charge collection for a single transistor. The RPP structure need not have a weight of 1 (100% efficiency).
- Identifying, locating, and quantifying the parameters of the sensitive volumes is the key aspect of this analysis.

## Calorimetry – Multiple SV Concept

- Within the solid model energy is tracked on a per transistor basis: “Sensitive Volumes”
- Usually 3 or more volumes encompass the transistor area
- Example:
- V1: Drain/Active silicon region
- V2: Sub-STI, proximal to drain
- V3: Sub-STI, distal to drain
- Energy deposition is equated to charge by
- Summing the contributions of E(V1)....E(Vn)
- Converting to charge (22.5MeV/pc)

- V3

- V2

- V1

- Transistor
- Top View

- V1

- Poly

- Contact

- Active

## Sensitive Volumes

- Regions far away from the sensitive node contact may have a very small alpha, for example, but contribute largely to the cross section.
- Traditionally we have modeled alpha as a constant for each volume, i, in each transistor j, but in this case it was chosen to be a function of E. The efficiency of any charge collection process DOES NOT follow linearly with deposited energy. This is physically reasonable, but adds to calibration difficulties as well.

## Sensitive Volumes 

- This function is quite powerful in fitting data over a large range of LET
- Allows one to partially decouple high and low LET cross sections for better fitting to exp. data
- Each volume has a max and min value for alpha, but only one Eo was used.

## Practical Considerations

- There are two basic types of parameters in this model: Geometrical and Charge Collection
- Geometrical
- Sensitive volume areas – ultimately represent cross sections.
- Located around the sensitive node (drain/source diffusions)
- Generally bounded by layout or process features (well taps, well boundaries, etc...)
- Areas scaled to represent measured cross sections
- Sensitive volume depths
- Initial guesses based upon process parameters – n,p well depths, epi depth, etc.. But varied to produce best fit to data.

## Sensitive Volumes

- MRED uses multiple sensitive volumes to represent charge collection for a given transistor.
- For any transistor, j, the final collected charge is a weighted sum of the micro-volumes

- NMOS

- PMOS

- NMOS

- Red squares are
- sensitive volumes

- *Multiple bits containing
- multiple arrays of volumes

## Sensitive Volumes - Final Note

- Every transistor in every bit (shown below) has a set of sensitive volumes associated with it.
- Note that only certain sets of transistors are sensitive, and this depends on the logic state of the circuit, which is set by the user (checkerboard for these simulations)
- During simulation, the defined logic state of the bit is checked and only those transistors that contribute to SEU are evaluated.

- 4x4 bit array

## Simulation Flow

-  ****Circuit response understood
-  ****Calorimetry (Sensitive Volumes)
-  _Particle Transport_
- X Calibration
- X Environment and Rate

**Sample **
**Particle (Z,A,E),**
**Directional Vector**
**(particle beam or **
**environment**

**Transport Through**
**Solid Model**

******Check to see how**
**much energy is**
**deposited in the **
**appropriate regions**

**********Compare to critical**
**Charge requirements**

**Count upset if enough**
**charge is collected **

## Solid Model Construction - Transport

- Solid models are based upon extrusions of the gdsii layer information provided by the vendor.
- Each layer is assigned a material composition (elements, stoichiometry, and density)
- Need only layout files and cross sections to complete.
- Level of detail is vital to accurately model
- Energy loss in over layers (electronic stopping, elastic, and inelastic collisions)
- Production of secondary particles that may affect cross section

## Solid Model Creation –90nm 12T

- Base Model

- Replicated
- (25 bits)
- Programmable

## Simulation Flow

-  ****Circuit response understood
-  ****Calorimetry (Sensitive Volumes)
**** Particle Transport
-  _Calibration_
- X Environment and Rate

**Sample **
**Particle (Z,A,E),**
**Directional Vector**
**(particle **_**beam**_** or **
**environment**

****** ****Transport Through**
**Solid Model**

******Check to see how**
**much energy is**
**deposited in the **
**appropriate regions**

**********Compare to critical**
**Charge requirements**

**Count upset if enough**
**charge is collected **

## Calibration to Heavy Ion Test Data

- Heavy Ion data were provided for 10 MeV/u Xe, Ar, and Kr.
- Parts were rotated and tilted in the beam
- Tilt angles were roughly between 0 and 75 degrees and roll angles were over a range of about 180 degrees.

- 180o

- 90o

- 0o

- Roll angle assumption

## 10 MeV/u Xenon at 75 and 65 Degree Tilt

- 75o Tilt

- 65o Tilt

## 10 MeV/u Xenon at 55 and 40 Degree Tilt

- 55o Tilt

- 40o Tilt

## 10 MeV/u Krypton  at 75 and 65 Degree Tilt

- 75o Tilt

- 65o Tilt

## 10 MeV/u Krypton  at 55 and 40 Degree Tilt

- 55o Tilt

- 40o Tilt

## 10 MeV/u Argon  at 75 and 65 Degree Tilt

- 75o Tilt

- 65o Tilt

## 10 MeV/u Argon  at 55 Degree Tilt

- 55o Tilt

## Calibration

- Data and simulation agreement are excellent at mid- to high LET values
- At low LET (Argon) there are more discrepancies but the trends are similar.
- At low LET, there is a noticeable difference between experiment and data in the cross section between 20/40 degrees and 140/160 degrees. Could be an artifact of the rectangular volumes or the experimental setup.
- Don’t expect the slight difference in cross sections at small tilt and low LET values to significantly affect results

## Simulation Flow

-  ****Circuit response understood
-  ****Calorimetry (Sensitive Volumes)
**** Particle Transport
**** Calibration
-  _Environment and Rate_

**Sample **
**Particle (Z,A,E),**
**Directional Vector**
**(particle beam or **
_**environment**_

****** ****Transport Through**
**Solid Model**

******Check to see how**
**much energy is**
**deposited in the **
**appropriate regions**

**********Compare to critical**
**Charge requirements**

**Count upset if enough**
**charge is collected **

## Soft Error Rate Prediction

- SEU rate predictions are handled by sampling from environments generated by CREME96.
- For this prediction, flux from CREME96 GEO/Interplanetary model during solar minimum following transport through 100 mils of aluminum was used.
- Note that this is not a “worst case” scenario.

- GEO/Interplanetary
- 100 mil Al Shielding
- 1<Z<92
- 0.1 MeV/u cutoff

## Soft Error Rate Prediction

- The relative contribution of species from Z=1 to Z=60 to the soft error rate is shown below.
- Note that the highest peak occurs at Z=26 (Iron) and accounts for approximately 50% of the total SER.
- The summed contribution of all species results in a final device error rate of _2.3 +/- 0.8 x 10__-9_ errors/bit-day

## Soft Error Rate Prediction (Sanity Check)

- It is possible to do a direct error rate methodology comparison between CREME96 and MRED, but only for the case of a simple RPP-type structure.
- In this instance, each set of sensitive volumes for a given FF bit were replaced by a single RPP of 1x1x0.5 m dimension and a critical charge of 50 fC. All other simulation parameters, solid model, and routines were the same as the latch SER prediction.
- This was intended to evaluate the spectrum sampling, solid model transport, book-keeping and post-processing algorithms in MRED against CREME96.

- Low Z error discrepancies are due to nuclear reactions which are not modeled in CRÈME
- MRED software is in complete agreement with CRÈME for this simple RPP case.

## Conclusions

- The current model is empirically driven but parameters and mechanisms are physically justifiable.
- TCAD results currently support the SEU mechanism hypothesis used to perform MRED analysis (“charge sharing” for N/P pairs, not just N-N pairs)
- _90% or more of the errors occur at shallow tilt angles_ (75-105 degrees)
- Model does NOT predict a divergent cross section at 90o, but rather saturates at about 2-3x10-9 cm2/bit
- Despite small admittance angle and area (e.g. cross section), if a particle does traverse the length of the device it is almost guaranteed to induce an upset down to low LET
- Hard to determine how low of an LET is physically reasonable since it is not practical to get experimental cross sections at 90 degrees
- We generally assume an order of magnitude systematic error in all rate predictions