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Record W4404788525 · doi:10.1109/jestpe.2024.3507821

WBG Power Semiconductor Module Packaging Insulation Characteristics Under Electrothermal Stress

2024· article· en· W4404788525 on OpenAlexaff
Wei Liu, Jun Jiang, Junzhe Zhang, Renli Fu, Chaohai Zhang

Bibliographic record

VenueIEEE Journal of Emerging and Selected Topics in Power Electronics · 2024
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsInternational Development Research Centre
FundersAeronautical Science Foundation of ChinaJiangsu Science and Technology DepartmentNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsMaterials scienceStress (linguistics)SemiconductorPower semiconductor deviceSemiconductor devicePower (physics)Power moduleElectronic packagingElectrical engineeringOptoelectronicsComposite materialEngineeringVoltagePhysicsThermodynamics

Abstract

fetched live from OpenAlex

As core components of increasing power density, the new generation wide bandgap (WBG) power semiconductor modules are advancing toward higher voltage levels. However, the reliability of packaging insulation serves as a significant constraint, notably concerning the insulation degradation induced by high temperatures working conditions within confined spaces. In this article, a simplified power module test model featuring a directed bonding copper (DBC) and silicone gel was established. Through partial discharge (PD) tests across temperatures spanning 25 °C–175 °C and different etching distances for substrate layout, the insulation degradation mechanism of power modules at varying temperatures is comprehensively explored. The results indicate an obvious reduction in the PD inception voltage (PDIV) with rising temperature, exhibiting an uptrend over 75 °C. Simultaneously, the discharge amplitude initially increases and subsequently decreases with rising temperature. The thermal expansion of tiny air-gap defects within the silicone gel emerges as a significant factor influencing the module’s insulation characteristics. Ultimately, by establishing a proportional air-gap defect model, the electric field and space charge distribution were studied under electrothermal coupling, validating the effectiveness of the insulation defect mechanism.

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 categoriesMeta-epidemiology (narrow)
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 score0.405
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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