Polyurethane Conformal Coatings Filled with Hard Nanoparticles for Tin Whisker Mitigation
Bibliographic record
Abstract
ABSTRACT Lead – free electronics using tin-based solders and pure tin are susceptible to tin whisker growth that can result in electrical failure. In an effort to prevent the whisker short circuits, we have developed polyurethane (PU) – based conformal coatings filled with the nanoparticles (nanosilica, nanoalumina). In particular, surface functionalization of those nanoparticles were explored to effectively bind them to the PU structure, as well as to prevent agglomeration. As the performance of the conformal coatings is strongly influenced by nano- and microstructural features, the structural and chemical variations due to the nanoparticle addition were examined by a wide range of characterization methods. The corresponding mechanical properties were also evaluated via ‘macroscopic’ tensile testing as well as ‘localized’ nanoindentation. Based upon mechanical properties and microstructure observations, this work identifies optimum concentration of the nanoparticles in PU. Some preliminary results on the effectiveness of nanoparticle-filled PU coatings for the tin whisker mitigation is also discussed in this paper.
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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".