Characteristics of Sn–Cu Solder Bump Formed by Electroplating for Flip Chip
Bibliographic record
Abstract
Sn–Cu near eutectic solder bump was fabricated by electroplating for flip-chip, and its electroplating and bump characteristics were studied. A Si-wafer was used as a substrate and the under bump metallization (UBM) comprised 400 nm of Al, 300 nm of Cu, 400 nm of Ni, and 20 nm of Au sequentially from bottom to the top of the metallization. The electrolyte for plating Sn–Cu solder consisted of$hbox Sn^+2$(concentration of 30 g/L) and$hbox Cu^+2$(0.3 g/L) solutions with methasulfonic acid and deionized water. The experimental results showed that the plating ratio of the Sn–Cu increased from 0.25 to 2.7$mu/hbox min$with increasing current density from 1 to 8$hbox A/dm^2$. In this range of current density, the plated Sn–Cu maintained its composition nearly constant level as Sn-(0.9$sim$1.4)wt% Cu. The solder bump of typical mushroom shape with 120-$muhbox m$stem diameter and 75-$muhbox m$height was formed by plating at 5$hbox A/dm^2$for 2 h. The mushroom bump changed its shape to the hemispherical type of 140-$muhbox m$diameter by air reflow on a hot plate at 260$^circhbox C$. The homogeneity of element distribution in the solder bump was examined, and Sn content in the mushroom bump appears to be uneven changed to more uniform after the air reflow. The highest shear bond strength of the Sn–Cu hemispherical bump showed 113 gf by reflowing at 260$^circhbox C$for 10 s.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".