A Novel Method for Bonding of Ionic Wafers
Bibliographic record
Abstract
A novel method for bonding sapphire, LiNbO/sub 3/, quartz and glass wafers with silicon using the modified surface activated bonding (SAB) method is described. In this method, the mating surfaces were cleaned and nano-adhesion Fe layers were deposited using a low energy argon ion beam simultaneously. The optical images show that the entire area of 4-inch wafers of LiNbO/sub 3//Si was bonded. Such images for other samples show particle induced voids across the interface. The average tensile strength for all of the mating pairs was much higher than 10 MPa. Prolonged irradiation reduces polarization in LiNbO/sub 3/, sapphire, quartz and Al-silicate glasses. Fe and Ar ions induced charge deposition may have resulted in electric field, which was responsible for the depolarization. The lattice mismatch induced local strain was found in LiNbO/sub 3//Si. No such strain was observed in the Al-silicate glass/Si interface probably because of annealing at 573 K for 8 h. The Al-silicate glass/Si interface showed a layer of 2-nm thick. An amorphous layer of 5-nm thick was observed with a layer across the LiNbO/sub 3//Si interface. The EELS spectra confirmed the presence of nano-adhesion Fe layers across the interface. These Fe layers associated with the electric filed induced by ion beam irradiation for prolonged period of time, particularly in Si/LiNbO/sub 3/, might be responsible for the high bonding strength between Si/ionic wafers at low temperature.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".