Effect of PVP on the low temperature bonding process using polyol prepared Ag nanoparticle paste for electronic packaging application
Bibliographic record
Abstract
There has been an increasing interest in developing low temperature interconnection process using metal nanoparticles. In this study the Ag nanoparticles (NPs) for this low temperature bonding process applications were prepared based on the polyol method using polyvinylpyrrolidone (PVP) as the protecting agent. The effect of PVP on the Ag nanoparticle size, nanoparticle solution viscosity and the bondability of the Ag nanoparticle paste were studied. The silver nanoparticle with diameter of 90 nm, 40 nm and 20 nm were synthesized by adjusting PVP concentration. The bonding processes using different kind of Ag nanoparticle paste were conducted. The joint with shear strength of 50 MPa were formed using Ag nanoparticle (NP) paste prepared with appropriate PVP concentration.
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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 | 0.000 |
| 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 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".