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Record W1979792509 · doi:10.1115/ipack2007-33457

High Temperature Lead-Free Attach Reliability

2007· article· en· W1979792509 on OpenAlexfundno aff
Patrick McCluskey, Pedro O. Quintero

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsnot available
FundersUniversity of Alberta
KeywordsReliability (semiconductor)Lead (geology)ElectronicsElectronic packagingTemperature cyclingFabricationMaterials scienceAutomotive industrySolderingReliability engineeringComputer scienceEngineering physicsManufacturing engineeringEngineeringThermalElectrical engineeringMetallurgyComposite material

Abstract

fetched live from OpenAlex

The increasing demand for electronics capable of operating at temperatures above the traditional 125°C limit is driving major research efforts. Wide band gap semiconductors have been demonstrated to operate at temperatures up to 500°C, but packaging is still a major hurdle to product development. Recent regulations, such as RoHS and WEEE, increase the complexity of the packaging task as they prohibit the use of toxic materials in electronic products; lead being a major concern due to its widespread use in solder attach. In this investigation, a series of Pb-free die attach technologies have been identified as possible alternatives to Pb-based materials for high temperature applications. This paper describes the fabrication sequence used to create attachments with these materials and their resultant microstructure. The long term reliability is also determined by accelerated thermal cycling and physics-of-failure modeling.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.005
GPT teacher head0.212
Teacher spread0.206 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2007
Admission routes1
Has abstractyes

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