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Investigations on Surge Current Capability of SiC Schottky Diodes by Implementation of New Pad Metallizations

2010· article· en· W2040533107 on OpenAlexaff
J. Hilsenbeck, Michael Treu, Roland Rupp, Kathrin Rüschenschmidt, Ronny Kern, Matthias Holz

Bibliographic record

VenueMaterials science forum · 2010
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsMaterials scienceSchottky diodeSurgeDiodeOptoelectronicsCurrent (fluid)VaristorElectrical engineeringVoltageEngineering

Abstract

fetched live from OpenAlex

In this paper we describe how a merged pn Schottky diode (MPS diode) is capable to drive surge current levels far beyond the normal current of the diode and how to improve the device in order to achieve even higher surge current levels. For a sine half wave of 10 µs an 8A MPS diode (size: 2.52mm2) with conventional Al pad metallization shows surge current levels of greater than 500A, using Cu it can be increased to ~900A. For 10ms pulse length a different behaviour was observed, here diodes with Al pad metallization show a higher surge current level (80A) compared to Cu pad metallization (~ 40A). The root cause for this negative result at longer pulse time is based in a chemical interaction between Cu and the Schottky metal (Ti). Additionally, an outlook is given how Cu can contribute to improved surge current capability also at longer pulse lengths.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.290
Teacher spread0.269 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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