Fundamental investigation of lid interactions with TIM1 and adhesive materials for advanced flip chip packaging
Bibliographic record
Abstract
As flip chip packaging evolves, there are increasing demands on the overall package design in order to maintain reliability while the devices themselves are increasing in performance. A key aspect for advanced flip chip applications that require a heat sink, is to ensure the integrity of the interface between the silicon chip and the heat sink (often a referred to as a lid or heat spreader). The challenging trends for these types of packages include: increased silicon surface areas, changes in substrate type(s), thinner overall package z-heights, and other thermo-mechanical demands which can all result in new, or re-introducing previously-solved, mechanisms that disrupt the thermal interface which is critically important for sufficient heat dissipation. In this research, the relationship between the lid and the materials at this interface is investigated. There are two types of lid/material interactions studied: the lid-to-TIM1 interface and the interface at the perimeter where, for large devices, an auxiliary band of adhesive/sealant is used to improve package reliability. Among the various techniques identified to assess the interactions at this interface, the adhesion performance is considered a primary method. A modified die shear adhesive method was optimized specifically for this application and determined to be the most suitable among several competing adhesion characterization methods. This investigation also includes characterization of the adhesion performance for numerous types of materials using standard microelectronics industry reliability conditions. It was found that following the failure modes, in particular, (as opposed to only the adhesive force data) at select intervals during this battery of stress testing can improve understanding of the interfacial behavior. Additionally, correlation studies were conducted to compare adhesion results with the other techniques typically used at the flip chip package-level, such as manufacturing line parametric tests (e.g. acoustic microscopy) or in the failure analysis lab (dye penetration, cross-sectioning, etc). Finally, an analytical chemistry assessment of the lid surface functionalities was also performed in order to correlate potential chemical interactions with this material set. Subsequently, the feasibility of improving the compatibility between the lid surfaces and the materials was evaluated. A variety of cleaning methods and other techniques were utilized to identify which methods seem to provide some performance benefits without significantly compromising other aspects of the overall package robustness.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".