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1200V SiC JFET in Cascode Light Configuration: Comparison versus Si and SiC Based Switches

2011· article· en· W2040881473 on OpenAlexaff
Fanny Björk, Michael Treu, J. Hilsenbeck, Matteo-Alessandro Kutschak, Daniel Domes, Roland Rupp

Bibliographic record

VenueMaterials science forum · 2011
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsJFETMaterials scienceCascodeInsulated-gate bipolar transistorReliability (semiconductor)MOSFETSilicon carbideOptoelectronicsDiodePhotovoltaic systemVoltageElectrical engineeringOhmic contactElectronic engineeringTransistorField-effect transistorEngineeringLayer (electronics)Power (physics)CMOSNanotechnology

Abstract

fetched live from OpenAlex

A 1200 V SiC JFET has been demonstrated to achieve ultra-low switching losses ten times lower than for industrial grade 1200V Si IGBT. The low switching losses are also shown to compete with the fastest 600V class MOSFET in the market, yielding 1.1% higher PFC stage efficiency for 340 kHz switching frequency, when same device on-resistances were measured. The proposed normally-on JFET also differentiates over the IGBT by its purely Ohmic output characteristics without any voltage threshold, and by a monolithically integrated body diode with practically zero reverse recovery. In this paper we outline as well how the other pre-requisites for a 1200 V SiC switch in applications such as photovoltaic systems and UPS can be fulfilled by the proposed JFET solution: long-term reliability, product cost optimization by low specific on-resistance combined with reasonable process window expectations. Finally, a normally-off like safe operation behavior is ensured by a dedicated driving scheme utilizing a low-voltage Si MOSFET as protection device at system start-up and for system failure 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.647

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 head0.041
GPT teacher head0.250
Teacher spread0.208 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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