1 / 17

Fundamental Aspects of Radiation Event Generation for Electronics and Engineering Research

Fundamental Aspects of Radiation Event Generation for Electronics and Engineering Research. Robert A. Weller Institute for Space and Defense Electronics School of Engineering Vanderbilt University. Overview. Introduction Research Program Background Technical Objectives Approach

kamali
Download Presentation

Fundamental Aspects of Radiation Event Generation for Electronics and Engineering Research

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Fundamental Aspects of Radiation Event Generation for Electronics and Engineering Research Robert A. Weller Institute for Space and Defense Electronics School of Engineering Vanderbilt University

  2. Overview • Introduction • Research Program Background • Technical Objectives • Approach • Expected Research Results • Technology Transfer

  3. Introduction • The Question: • If you model all the physical processes by which radiation interacts with materials, and by which electric charge moves in solids, as accurately as current knowledge permits, can you predict radiation effects in semiconductor devices from first principles? • If not, then why not? • The essential issue - Complexity!

  4. Background • Existing methods for predicting the rate of single event upsets in semiconductor devices have begun to fail because their of their basic assumptions. • New computational methods developed at Vanderbilt have exposed gaps in basic science that limit our ability to make accurate predictions of single event effects. • Two important areas needing basic work are: • The generation of final states of ionizing particles following nuclear reactions. • The microstructure of energy deposition and charge generation by ions, including the spatial and energy distributions of carriers. • The detailed motion of charge in matrices of sub 100 nm structures is also important but is not the primary focus of this work.

  5. Multi-layered Stack SEU Rate for a Modern SRAM • Comparing a calculation with data from a real SRAM flown by NASA • Observed Average SEU Rate: • 1x10-9 Events/Bit/Day • Vendor predicted rate using CREME96: • 2x10-12 Events/Bit/Day • Classical Method nearly a factor 500 lower than the observed rate • VU-ISDE rate: • All relevant physics with Geant4 • 1.3x10-10 to 1.3x10-9 Errors/Bit/Day • Wide error bar from Geant4 ion-ion physics uncertainty

  6. NMOS PMOS NMOS The Impact of Complexity 12-T DICE Latch Kevin Warren, VU ISDE

  7. A Focus on the Nuclear Physics

  8. Si-Nitride 0.4 µm SiO2 1.0 µm TiN 0.1 µm Al 0.84 µm TiN 0.1 µm SiO2 0.60 µm TiN 0.1 µm Al 0.45 µm SiO2 or W 0.6 µm TiN 0.1 µm Al 0.45 µm TiN 0.1 µm SiO2 0.6 µm Si 0.25 µm 50 µm Charge Generation 0 Nuclear Reactions

  9. Charge Motion 1018 e-/cm3 1014 e-/cm3

  10. Technical Objectives • Establish the available data, theory and computation for ion-ion nuclear reactions • Build virtual experiments that test these models for best fit to semiconductor data • Identify the best available nuclear reaction codes • Interface and/or adapt the best codes for MRED • Improve the nuclear-physics/charge-transport interface as necessary for < 100 nm structures • Establish a roadmap for any necessary nuclear reaction research

  11. Croc image: http://crocodilian.com/crocfaq/ Approach - Strategy • Identify the best available physics. • Code the physics (whenever possible) in timeless algorithms. • Use supercomputer-based high-fidelity simulations to extract the physics that arises from complexity. • Establish validity by comparison with experimental data. • Let computer evolution deal with any power shortfall (if possible).

  12. Approach - Implementation • Identify available nuclear reaction models. • Adapt models to mred/Geant4 if necessary. • Develop structures to simulate nuclear physics and radiation effects experiments. • Conduct simulated experiments for comparison with experimental data. • Identify the best available models for practical applications. • Identify essentially-related issues outside the scope of this effort.

  13. Manage Complexity with Computing

  14. Predicting Experiments

  15. Python SWIG MRED C++ Geant4 The Structure of MRED • Python: The common system language. • MRED: A Python module called mredPy. • Target: VU Linux cluster. • Python writes submission scripts, controls job execution, and merges results.

  16. Expected Results • Identify optimum nuclear modes for MRED. • Validate nuclear models against semiconductor data. • Identify issues related to the interface between charge generation and transport in sub-100 nm structures. • Deeper understanding of the intricacies of charge generation. • Reduced uncertainty in SEU prediction.

  17. Technology Transfer • ISDE Engineering • Collaborative R&D, e.g. NRL/Vanderbilt • NASA MSFC/Vanderbilt CREME-MC Site • Major semiconductor supplier relationships • NASA Center collaborative R&D • Through students

More Related