Implications of Helium and Neon Ion Beam Chemistry for Advanced Circuit Editing
Bibliographic record
Abstract
Abstract Gallium focused ion beams (Ga-FIB) have been used historically in the semiconductor industry for failure analysis, as well as circuit edit. However, in spite of the best of these efforts, as integrated circuit dimensions continue to shrink, Ga-FIB induced processes are being driven to their physical limits. The main purpose of this paper is to report the helium and neon ion beams' induced chemistry, including metal deposition, dielectric deposition, and chemically enhanced etching. Two simple examples are shown as proofs of concept demonstrating gas field ion source (GFIS) development for circuit edit applications. The paper summarizes the general utility of helium and neon ion beams for metal deposition, dielectric deposition, and sputtering and etching processes, and discusses some of the technical challenges associated with current GFIS technology. Using GFIS ion beams, it has been observed that the top and buried metal lines can be cut precisely and then reconnected.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".