Direct glass-to-glass bonding obtained <i>via</i> simplified ammonia-based low-temperature procedure resists high shear stress and powerful CW fiber laser irradiation
Bibliographic record
Abstract
Direct glass-to-glass bonding is important for high-technology components in optics, microfluidics, and micro-electromechanical systems applications. We studied direct bonding of 1 mm thick soda-lime float glass substrates. The process is based on the classic RCA-1 cleaning procedure from the semiconductor industry modified with an ammonium hydroxide rinse, followed by a thermal treatment under unidirectional pressure without the need for a dedicated drying step. RCA-1 uses a solution of ammonium hydroxide and hydrogen peroxide to clean contaminants off the surface of silicon and enable subsequent bonding. Bond quality was evaluated using destructive shear testing. Strong bonds (≈7.81 MPa on average) were achieved using unidirectional pressure of approximately 0.88 MPa and bonding temperatures between 160 °C and 300 °C applied for 30 min. Surface roughness and chemistry was characterized before and after cleaning. The optical robustness of the bonds was tested and shown to be capable of surviving high powered continuous wave (CW) fiber laser irradiation of at least 375 W focused for 2 s without delamination. Melting of the substrate was observed at higher powers and longer exposure times.
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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) | 0.001 | 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) | 0.002 | 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".