Effective Flux Removal Under Stringent Environmental Limitations
Bibliographic record
Abstract
ABSTRACT To cope with latest VOC regulations the authors validated a viable process window for a new cleaning product technology. The face of precision cleaning in the electronics industry has changed significantly over the last 20 years. With the ban of Fluorinated Chloro-carbons, the 1989 Montreal protocol opened the way for the use of alternative to non-ozone depleting and more environmentally sound solutions. Initially, direct solvent-based replacements were successfully introduced in the 1990s; although efficient cleaning solutions, they too were soon considered harmful to the environment. With the latter, some of the problems included the high volatile organic content as well as the costly cleaning equipment needed to efficiently use them. In an effort to minimize the VOC content, water-based products were soon introduced, ranging from saponifier/surfactant based products, to MPC ® based technologies. They vary in operating temperatures, application concentrations used for cleaning, effectiveness, as well as achieved bath life time. Depending on the contamination to be removed, the application concentration for currently available products range from 5 and 30 %. MPC ® based product technologies on the other hand provide lower operating temperatures, lower concentrations and the longest bath life time. For saponifier-based products weekly bath changes are typically the norm. During the last 5 years, some states went further and passed legislation to limit the amount of VOC to 50g/L soon to be followed by the further regulations(i.e. 25g/L in California; Figure 1).
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".