Bibliographic record
Abstract
An extensive methodology for the numerical modeling of C4 interconnects in flip chip organic packages is presented, with particular emphasis on the variability introduced by the manufacturing process. A number of different analytical and experimental techniques are used to develop a complete mechanical model of the interconnect, in order to infer the characteristics of various packaging options with respect to the reliability of C4 interconnects. A fully parametric "macroscopic" finite element model of the entire module (laminate, underfill, chip, lid structure) is first constructed, and is used to define boundary conditions for "microscopic" models of the interconnects. A flexible software system that allows the complete parameterization of the module (in terms of its topology, scales, and material properties) is described. The geometry of the interconnect is calculated parametrically from first principles using a model of the solder joint in fluid phase, taking into account various properties of the interconnect such as the solder volume, the pad diameters, the relative position of the pads, etc. Data validating this fluid model on BGA and on C4 solder balls are also presented. Finally, the variability inherent to manufacturing flip chip packages is emulated by sampling some of the model parameters from random distributions (examples of such parameters include laminate warpage and solder joint volume, and their influence on global package properties, such as the underfilled gap between laminate and chip). Illustrative examples of applying this methodology for problem solving in a manufacturing environment are also presented.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".