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Record W2800065502 · doi:10.1139/tcsme-2017-0013

Electrothermal coupling analysis and experimental verification for wirebond devices

2018· article· en· W2800065502 on OpenAlexvenueno aff
Chin-Li Kao, Tei-Chen Chen

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMolding (decorative)Quad Flat No-leads packageWire bondingMaterials scienceElectronic packagingThermal conductivityThermalMechanical engineeringThermal analysisCoupling (piping)Composite materialElectrical engineeringChipEngineeringLayer (electronics)

Abstract

fetched live from OpenAlex

The thermal performance of a powered wirebond device with package level and board level test specimens was investigated by both analytical and experiment methods. The effects of thickness and thermal conductivity of the molding compound and heat spreader attached to the top surface of the molding compound on the performance of the Au wire and silicon die were modeled and evaluated by three-dimensional electrothermal coupling analysis. An advanced quad flat no-lead (QFN) sample was selected to experimentally measure the maximum allowable current in Au wire for packages either with or without molding compound. Two failure modes, namely the fusing of the wire and the decomposition temperature of the molding compound, were established in analysis. A board level test specimen with a thermal test die was also employed to measure the real time package thermal performance. The major achievement of this work is in the complete combination of modeling, experiment, and optimization for thermal performance evaluation purpose of a powered wirebond device. Results of this physical analysis can provide a reliable and useful guide to estimate the maximum allowable currents in Au wires for a wirebond device under practical application conditions.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.730
Threshold uncertainty score0.402

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 head0.009
GPT teacher head0.215
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2018
Admission routes1
Has abstractyes

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Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicElectronic Packaging and Soldering TechnologiesFrench-language works237,207