Some Fundamental Issues in the Use of Zn-Containing Lead-Free Solders for Electronic Packaging
Bibliographic record
Abstract
A synergistic approach is applied to address the major concerns about the use of Zn-containing lead-free solders for electronic packaging. Using computational thermodynamics as a predictive tool, the phase stability of the Ag-Al-Cu-In-Sn-Zn system is examined to design a Zn-containing lead-free solder with melting characteristics similar to near-eutectic Pb-Sn solder. Theoretically, it is found that a Sn-0.3 mass%Al-4.2 mass%In-7.8 mass%Zn solder has a melting point (liquidus temperature) of 185°C and a solidification range of 10°C. It is demonstrated that environmentally benign fluxes containing tin-organometallics significantly improve the wetting behavior compared to rosin fluxes used for lead-tin solders. For the Sn-Zn eutectic solder on a Cu substrate at 260°C, it is found that the contact angle is reduced from 150° to about 25° when tin-organometallic fluxes are used instead of rosin flux. Severe accelerated tests (85% relative humidity at 85°C) for up to six weeks show that the mechanical properties of Sn-Zn eutectic solder interconnects are not affected adversely by the environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".