Effects of Moisture and Hydrogen Exposure on Radiation-Induced MOS Device Degradation and Its Implications for Long-Term Aging
Bibliographic record
Abstract
Transistors and ICs built in several different captive and commercial facilities were exposed to moisture, irradiated, and annealed. The moisture exposures were performed using highly accelerated stress test (HAST) at 130degC and 85% relative humidity. Irradiation of n-channel transistors exposed to HAST followed by a long-term anneal resulted in some increase in interface-trap and oxide-trapped charge buildup. However, exposing p-channel transistors to HAST preirradiation resulted in extremely large and unexpected voltage shifts immediately following irradiation. They were observed for devices with either doped oxide or nitride final chip passivation. Because of this, nitride passivation may not be sufficient to prevent H2O from causing enhanced radiation-induced degradation over long time periods in some devices (e.g., commercial devices with nitride final chip passivation packaged in plastic packages). The smaller voltage shifts for the n-channel transistors may be related to the formation of phosphosilicate glass (PSG) overlying the sources and drains of the n-channel transistors impeding the diffusion of moisture to the gate oxides. It is shown that, the large radiation-induced voltage shifts for the p-channel transistors can lead to enhanced IC parametric degradation and functional failure at lower radiation levels. Large increases in radiation-induced field oxide leakage current were also observed for transistors exposed to HAST preirradiation. Transistors were also annealed (prior to irradiation) and irradiated in H2. Approximately the same level of radiation-induced degradation was observed for n- and p-channel transistors suggesting that the diffusion kinetics for H2diffusion are considerably different than for H2O diffusion. These results raise the concern that exposure of devices to moisture or hydrogen can lead to long-term radiation-induced aging effects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".