Integration of Probing Capability into Plasma FIB for In-Situ Delayering, Defect Inspection, and EBAC on BEOL Defects of Sub-20nm FinFET Devices
Bibliographic record
Abstract
Abstract Deprocessing and probing are two quintessential steps in the physical failure analysis (PFA) and competitive analysis of integrated circuits (ICs). Typically, these steps are accomplished using multiple tools, which include polishers, electron microscopes, and probers. To combat the aggressive back-end-of-line (BEOL) scaling which has significantly decreased the controllability of manual polishing, gas-assisted Xe plasma FIB has been employed to achieve large area uniform delayering. Combined with an in-situ probing capability within the plasma FIB, the iterative process of juggling between tools is streamlined into a seamless process. In this paper, the successful integration of Prober Shuttle and plasma FIB to isolate and visualize real defects on sub-20 nm microprocessor chips are presented.
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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".