On-Silicon Characterization of CDM-Like Stress in Long Interconnects Using vf-TLP in Nanometric ICs
Bibliographic record
Abstract
This work presents a comprehensive silicon-based validation methodology for Charged Device Model Electrostatic Discharge (CDM-ESD) protection strategies in a 28 nm thin-oxide CMOS process. The approach evaluates multiple protection topologies such as duo/trio diodes, and grounded-gate nMOS (ggNMOS), using very-fast Transmission Line Pulse (vf-TLP) testing. Failure analysis (FA) via Scanning Electron Microscopy (SEM) is used to correlate electrical degradation with physical damage post-stress. In-depth analysis is performed from three key perspectives: the influence of averaging window selection on I–V curve fidelity, extraction and interpretation of decoupling capacitance and energy dissipation efficiency under CDM-like stress. Results highlight both the strengths and limitations of each protection method under fast transients, offering insight into optimal ESD design for long interconnect paths. Practical enhancements to the vf-TLP setup are also discussed. This study identifies layout-induced failure mechanisms too. The proposed framework enhances CDM robustness validation and informs future ESD strategies in scaled nodes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".