Smart Packaging - Microscopic Temperature and Moisture Sensors Embedded in a Flip-Chip Package
Bibliographic record
Abstract
The interest in very-large-scale integration technology combined with market pressure to reduce materials and process costs introduce new packaging yield and reliability challenges. The use of organic substrates in flip-chip packages, rather than ceramics, led to thermal and moisture related issues. The organic laminate coefficient of thermal expansion substantially differs from the chip one, potentially leading to interfacial delamination and interconnect rupture. Moreover, organic substrates are permeable to water, potentially leading to electrochemical migration, corrosion of alloys, delamination and short-circuits. Thus temperature and moisture variation can have baneful consequences on flip-chip packages. Here, the internal module temperature and moisture quantities of a flip-chip package are measured using microscopic embedded carbon nanotube-based sensors. Those sensors are fabricated near interconnects and are positioned to provide spatial and real-time mapping of moisture and temperature in the package, for a better interconnect reliability study or package aging monitoring.
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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) | 0.000 | 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) | 0.001 | 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".