TSV Extracted Equivalent Circuit Model and an On-Chip Test Solution
Bibliographic record
Abstract
Through silicon via (TSV) is the enabling technology for 3-D integrated circuit (IC) realization. To develop manufacturing tests for 3-D ICs, TSV has to be accurately modeled. Analytical methods are commonly used to develop circuit models for TSVs. These models are often difficult to develop and require some assumptions to simplify the problem. This paper presents a new method utilizing computer-aided design tools to extract circuit models for prebond and postbond TSVs. It is shown how the effects of common TSV parametric and catastrophic faults such as pinholes, voids, and open circuits affect TSV circuit models through 3-D full-wave simulations. It is also shown that the substrate conductivity has a considerable effect on the TSV fault characterization. The extracted models indicate that even a relatively large void does not alter the TSV characteristic parameters and thus voids remain largely undetected with conventional test solutions. An on-chip circuit, utilizing a delay-locked loop is presented as a test solution to detect TSV parametric faults.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".