A New Non-PRM Bumping Process by Electroplating on Si Die for Three Dimensional Packaging
Bibliographic record
Abstract
A new bumping process on a Si die by electroplating without a photo-resist-mold (PRM) was assessed for the three dimensional (3D) stacking of Si dice. In this process, solder bumps were deposited selectively onto the surface of a Cu plugged-through silicon-via (TSV) in a Si die. Since lithography related processes to make a PRM for solder bumping were omitted, it can reduce the production time and cost for bumping. The substrate was a Si wafer, and TSVs were produced by deep-ion-reactive-etching (DRIE). As an insulation layer, SiO2 was formed by high-density-plasma-chemical-vapor-deposition (HDPCVD) or wet oxidation method. A Ti adhesion and an Au seed layers were deposited by sputtering. Cu was plugged into the vias by pulsed direct-current (DC) electroplating. The backside of the Si wafer was ground by chemical-mechanical-polishing (CMP). Sn bumps were electroplated on the Cu plugged vias by a current supplied through a Cu-overplated layer (COL) on the vias surface. As experimental results, wet oxidation provided a uniform SiO2 thickness through the via depth, whereas the SiO2 thickness by HDPCVD decreased with the via depth. The Ti and Au thicknesses also decreased along the via depth. In electroplating for Cu plugging, defect-free Cu plug was achieved by pulsed DC for 18 h, where one cycle composed of a 5 s cathodic term with −12.2 mA·cm−2 and a 25 s anodic term with 2.3 mA·cm−2. Sn bumping using COL without PRM was accomplished successfully at a current density of −30 mA·cm−2 for 15 min. The diameter and height of the Sn bumps ranged from 48.5 to 52 μm and 22 to 25 μm, respectively. The bumps had a rivet head shape without a columnar part and showed facets on the bump surface. The COL was removed by CMP without damage to the bumps.
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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) | 0.001 | 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 | 0.001 |
| 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".