The radiation effects community needs clear, well-documented, neutron energy-dependent responses that can be used in assessing radiation-induced material damage to GaAs semiconductors and for correlating observed radiation-induced changes in the GaAs electronic properties with computed damage metrics. In support of the objective, this document provides: a) a clearly defined set of relevant neutron response functions for use in dosimetry applications; b) clear mathematical expressions for the defined response functions; and c) updated quantitative values for the energy- dependent response functions that reflect the best current nuclear data and modelling. This document recaps the legacy response functions. It then surveys the latest nuclear data and updates the recommended response function to support current GaAs damage studies. A detailed tabulation for six of the energy-dependent response functions is provided in an Appendix.
This report provides basic background data on the Manipulate-2020 code. This code is used for processing and "manipulation" of nuclear data in support of radiation metrology applications. The code is made available on the open GitHub repository and is available to the general nuclear data community.
Four D flip-flop (DFF) layouts were created from the same schematic in Sandia National Laboratories' CMOS7 silicon-on-insulator (SOI) process. Single-event upset (SEU) modeling and testing showed an improved response with the use of shallow (not fully bottomed) N-type metal-oxide-semiconductor field-effect transistors (NMOSFETs), extending the size of the drain implant and increasing the critical charge of the transmission gates in the circuit design and layout. This research also shows the importance of correctly modeling nodal capacitance, which is a major factor determining SEU critical charge. Accurate SEU models enable the understanding of the SEU vulnerabilities and how to make the design more robust.
A general formulation of silicon damage metrics and associated energy-dependent response functions relevant to the radiation effects community is provided. Using this formulation, a rigorous quantitative treatment of the energy-dependent uncertainty contributors is performed. This resulted in the generation of a covariance matrix for the displacement kerma, the Norgett-Robinson-Torrens-based damage energy, and the 1-MeV(Si)-equivalent damage function. When a careful methodology is used to apply a reference 1-MeV damage value, the systematic uncertainty in the fast fission region is seen to be removed, and the uncertainty for integral metrics in broad-based fission-based neutron fields is demonstrated to be significantly reduced.
A bipolar-transistor-based sensor technique has been used to compare silicon displacement damage from known and unknown neutron energy spectra generated in nuclear reactor and high-energy-density physics environments. The technique has been shown to yield 1-MeV(Si) equivalent neutron fluence measurements comparable to traditional neutron activation dosimetry. This paper significantly extends previous results by evaluating three types of bipolar devices utilized as displacement damage sensors at a nuclear research reactor and at a Pelletron particle accelerator. Ionizing dose effects are compensated for via comparisons with 10-keV X-ray and/or cobalt-60 gamma ray irradiations. Nonionizing energy loss calculations adequately approximate the correlations between particle and device responses and provide evidence for the use of one particle type to screen the sensitivity of the other.
A rigorous treatment of the uncertainty in the underlying nuclear data on silicon displacement damage metrics is presented. The uncertainty in the cross sections and recoil atom spectra are propagated into the energy-dependent uncertainty contribution in the silicon displacement kerma and damage energy using a Total Monte Carlo treatment. An energy-dependent covariance matrix is used to characterize the resulting uncertainty. A strong correlation between different reaction channels is observed in the high energy neutron contributions to the displacement damage metrics which supports the necessity of using a Monte Carlo based method to address the nonlinear nature of the uncertainty propagation.
The effect of uncertainty in the energy partition function on the silicon displacement damage metric is presented. Through the use of a Total Monte Carlo approach, the effect of uncertainty in the underlying electronic and nuclear ion interaction potentials, which are used to define the damage partition function, is propagated into an uncertainty in the silicon damage metric. This uncertainty is expressed as an energy-dependent covariance matrix which permits this uncertainty component to be combined with other uncertainty components, e.g. uncertainty due to the knowledge of the nuclear interaction data or to the treatment of the damage in the threshold displacement region. This approach provides a rigorous treatment of uncertainty due to the damage metric which can then be propagated in uncertainty estimates for various applications, e.g. when examining damage equivalence between different neutron sources. A strong energy-dependent correlation is found in this uncertainty component.