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Chip Warpage Damage Model for ACA Film Type Electronic Packages

2005· article· en· W2064861594 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKey engineering materials · 2005
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsMaterials scienceDelamination (geology)ChipFlip chipInterconnectionComposite materialAdhesiveReliability (semiconductor)Electronic engineeringElectrical engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

The use of anisotropically conductive adhesives (ACA) for the direct interconnection of flipped silicon chips to printed circuits (flip chip packaging), offers numerous advantages such as reduced thickness, improved environmental compatibility, lowered assembly process temperature, increased metallization options, cut downed cost, and decreased equipment needs. Despite numerous benefits, ACA film type packages bare several reliability problems. The most critical issue among them is their electrical performance deterioration upon consecutive thermal cycles attributed to gradual delamination growth through chip and adhesive film interface induced by CTE mismatch driven shear and peel stresses. In this study, warpage of the chip is monitored by real time moiré interferometer during –50oC to +125oC temperature range. Moreover, reduction in chip warpage due to increase in delamination length is obtained as in function of thermal fatigue cycles. Finally, a new model to predict damage level of ACA package and remained life is proposed and developed.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.211
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it