Failures of MOSFETs in terrestrial power electronics due to single event burnout
Bibliographic record
Abstract
Failures of semiconductor devices caused by cosmic radiation exposure is well known in space and avionics applications. However it is not well known that similar issues exist, to a lesser extent, for terrestrial applications. We have conducted research into the phenomenon of single event burnout (SEB) of high voltage power electronics semiconductor devices, specifically MOSFETs that are ubiquitously used in modern switchmode power electronics. The research revealed that SEB and related effects, caused by high-energy neutrons generated by the impact of cosmic radiation on our upper atmosphere, are a real possibility at ground level. An introduction and overview of the SEB effect, a review of existing literature indicating the flux and energy distribution of neutrons that reach the earth's surface and an overview of the structure of MOSFET devices indicating why they could be susceptible to the SEB effect is given. Experiments were conducted which demonstrated that random failures of high voltage MOSFET devices, when they are biased in the off state, do occur at a much higher rate than should otherwise be expected. A summary of experiments that were carried out at the TRIUMF cyclotron laboratory on both individual MOSFETs and on electronic equipment containing MOSFETs is presented. These experiments provide strong evidence that failures of MOSFETs and circuits using MOSFETs can be caused by neutrons with energy distributions similar to that experienced on the earth's surface.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".