A Study of Low-Cost Sequential Electroplating Bumping Process and its Metallurgical Behavior
Bibliographic record
Abstract
Studies were conducted to validate from a metallurgical point of view whether a lower cost sequential plating approach to SnAg and SnAgCu (SAC) solder bumping is a suitable alternative to the conventional alloy plating process. A range of Ag content corresponding to typical bump applications was explored with respect to Ag diffusion and intermetallic compound (IMC) formation. Variables that can affect such IMC formation were further explored as a function of underbump metallization (UBM) structure and cooling rate during bump solidification. By comparing the results to those previously reported on SnAg-based alloys, it is demonstrated that the proposed sequential plating process produces very similar microstructures and Ag3Sn IMC morphologies, due to the rapid diffusion and distribution of Ag through the liquid Sn. Known means to mitigate the less desirable large Ag3Sn platelets, that is by changing the top UBM layer from Cu to Ni or by employing an ultrarapid cooling rate, are shown to be equally effective for sequential plating. These observations, in conjunction with the simplicity and flexibility of plating multiple single metals, propose adoption of the sequential plating process as a cost-effective and robust Pb-free bumping solution for fine pitch flip-chip packaging.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".