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Comparative Simulation Study of Dynamic Behavior of the Body-Diode for 4H-SiC JFET and MOSFET

2016· article· en· W2402621725 on OpenAlexaff
Rudolf Elpelt, Bernd Zippelius, Daniel Domes

Bibliographic record

VenueMaterials science forum · 2016
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsJFETMaterials scienceSilicon carbideMOSFETDiodeOptoelectronicsPIN diodeStep recovery diodeSwitching timeFlyback diodeSchottky diodeElectrical engineeringVoltageTransistorField-effect transistorEngineeringFlyback transformer

Abstract

fetched live from OpenAlex

In switching applications with half-bridge like configurations the load current is commutated to the so-called reverse or body-diode of a switching device once each switching cycle. The bipolar charge generated in the switch in principle leads to a reverse recovery current and to additional losses. Though it is well known, that in silicon carbide these reverse recovery losses are very low compared to e.g. silicon devices, it turns out that depending on device structure and switching conditions the reverse recovery charge for the JFET may become larger than can be explainable by the stored bipolar charge. In this paper therefore we focus on a simulation study comparing the body-diode operation of common lateral channel silicon carbide JFET and MOSFET devices in a so-called double pulse measurement. It is shown, that the MOSFET body-diode operation still remains uncritical under very fast switching conditions, while the JFET body-diode exhibits a pronounced recovery current peak originating from a partial channel turn-on, and thus higher losses.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.212

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 head0.024
GPT teacher head0.294
Teacher spread0.270 · 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 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

Citations2
Published2016
Admission routes1
Has abstractyes

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