Microstructure Size Measurement Based on C-scan Image of Scanning Acoustic Microscopy
Bibliographic record
Abstract
The scanning acoustic microscopy system has a poor lateral resolution in the scan of microdefects within micro-devices. To solve the problem, this paper identifies the main influencing factors of the lateral size measuring accuracy of scanning acoustic microscopy, namely, Cscan image resolution and the lateral size measuring resolution. Then, the two kinds of resolutions were subjected to detailed analysis. After that, several micro-scale silicon wafers were prepared, and subjected to defect detection and size measurement by a high-frequency scanning acoustic microscopy system with a 300MHz high-frequency focused transducer. The measuring results show that the C-scan of the scanning acoustic microscopy system successfully recognized linear defects of 10m and circular defect with a diameter of 16m, and achieved a size measuring error no greater than 5.05 %; in addition, the measuring error is negatively correlated with the size of the wafer. Thus, the scanning acoustic microscopy system can measure small dimensions in an accurate manner.
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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) | 0.001 | 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 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".