An Application of Semiparametric Bayesian Isotonic Regression to the Study of Radiation Effects in Space- borne Microelectronics

This work is concerned with the vulnerability of spaceborne microelectronics to single event upset, a change of state caused by high-energy charged particles in the solar wind or the cosmic ray environment striking a sensitive node. To measure the susceptibility of a semiconductor device to single event upsets, testing is conducted by exposing it to highenergy heavy ions or protons produced in a particle accelerator. The number of upsets is characterized by the interaction cross-section, an increasing function of linear energy transfer (LET). The prediction of the on-orbit upset rate is made by combining the device geometry and cross-section vs. LET curve with a model for the orbit-specific radiation environment. We develop a semiparametric isotonic regression method for the upset count responses, based on a Dirichlet process prior for the cross-section curve. The proposed methodology allows the data to drive the shape of the cross-section vs. LET relationship, resulting in more robust predictive inference for the on-orbit upset rate than conventional models based on Weibull or lognormal parametric forms for the cross-section curve. We illustrate the modelling approach with data from two particle accelerator experiments.