Laser-Induced Trench Design, Optimisation and Validation for Restricting Capillary Underfill Spread in Advanced Packaging Configurations
Bibliographic record
Abstract
Spreading of flip-chip capillary underfill material into regions of other components can complicate their assembly and/or integrity. We propose a novel, cost-effective means to control this spread through the use of thin, linear trenches of controlled depth on solder mask surfaces. To optimally exploit this method, an in-depth study is conducted to understand the underlying mechanism. Using high resolution 3D optical profilometry, trench profile is first correlated to key laser process parameters. Trench profiles are then evaluated by means of a custom designed underfill loading test vehicle in order to determine their relative effectiveness. Characterization of both the trench and restricted underfill profiles demonstrate correlation to the Gibbs' inequality relationship for surface tension. A trench profile is identified for chip assembly that balances high underfill restricting capacity with acceptable width and depth to suit the specificity of a substrate solder mask. The restriction of underfill spreading is then investigated in the critical dispense region of a Package on Package (PoP) application comprising stringent spacing criteria between a flip chip device and proximal BGA connections. Using trenches proposed by the laser parameter study and placed as close as 0.7 mm from chip edge, successful dispense processing and subsequent underfill flow bounding are demonstrated. Finally, underfill spread and fillet formation in the presence of trenches on the non-dispense (exit) sides of a chip assembly is investigated to determine the limits of trench proximity to chip edge. Control of underfill spread is demonstrated at trench lines as close as 0.2 mm from the chip edge on the exit sides. Using comparable samples with unrestricted underfill flow, a reduction of 0.4 mm in underfill spread on each exit side is observed. Considering the possible contact angle of the underfill at the trench edge, one can model how close the trench lines should be placed to achieve a fillet height satisfying the design specifications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".