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K.M. Warren,
R.A. Weller,
B.D. Sierawski,
R.A. Reed,
M.H. Mendenhall,
R.D. Schrimpf,
L.W. Massengill,
M.E. Porter, J.D. Wilkinson,
K.A. LaBel,
J.H. Adams
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ABSTRACT: The RADSAFE simulation framework is described and applied to model SEU in a 0.25 mum CMOS 4 Mbit SRAM. For this circuit, the RADSAFE approach produces trends similar to those expected from classical rectangular parallelepiped models, but more closely represents the physical mechanisms responsible for SEU in the SRAM circuit.
IEEE Transactions on Nuclear Science 09/2007; · 1.45 Impact Factor
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ABSTRACT: A combination of commercial simulation tools and custom applications utilizing Geant4 physics libraries is used to analyze thermal neutron induced soft error rates in a commercial bulk CMOS SRAM. Detailed descriptions of the sensitive regions based upon technology in computer-aided design calibration are used in conjunction with a physics-based Monte Carlo simulator to predict neutron soft error cross sections that are in good agreement with experimental results
IEEE Electron Device Letters 03/2007; · 2.85 Impact Factor
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ABSTRACT: Experimental thermal neutron and alpha soft error test results of a 4 Mbit SRAM fabricated on a 0.25 mum process are evaluated using Vanderbilt University's RADSAFE toolkit. The capabilities of the radiation transport code are demonstrated by accurately reproducing experimental results and predicting operational soft error rates for the memory.
Integrated Circuit Design and Technology, 2007. ICICDT '07. IEEE International Conference on;
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ABSTRACT: In this work, heavy ion and energetic proton single event upset (SEU) cross sections are measured for a 4 Mbit CMOS, static random access memory (SRAM). Heavy ion upset cross sections were used to define a dosimetry model suitable for use in a Monte-Carlo, physics-based transport code, which is shown to be predictive for experimentally measured proton single event upset (SEU) cross sections. The simulator was used to quantify the difference between neutron and proton SEU cross sections and to evaluate the fidelity of currently established rate prediction methods. Simulations indicate that established test methods under-predict the FIT rate between 26- 35% for this technology.
Reliability Physics Symposium, 2008. IRPS 2008. IEEE International;
