A Novel Induced Offset Voltage Sensor for Separable Wear-Out Mechanism Characterization in a 12nm FinFET Process
Bibliographic record
Abstract
Increasingly detailed predictive modelling and monitoring of semiconductor wear-out benefits greatly from on-chip measurement of transistor degradation under different voltage stress regimes. To this end, we present a novel sensor architecture leveraging direct current (DC) readout for product designs where precise timing sources are unavailable. Our design avoids wear-out in ancillary transistors and compensates for process, voltage, and temperature variations to ensure measurements track induced shifts in threshold voltage under a configurable stress regime in isolation. The proposed architecture is described in detail and a review of existing DC sensors for monitoring semiconductor degradation is included to enable comparative analysis of our design. Sensor functionality is validated via implementation in a 12nm FinFET process. Accelerated wear-out testing is conducted via a custom automated test system. Experimental results demonstrate that the design is capable of separately monitoring transistor degradation under different stress regimes and highlight observed wear-out behaviours in nanometre-scale transistors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".