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Record W4308471070 · doi:10.1109/ted.2022.3208218

Modeling and Analysis of SiC GTO Thyristor’s Dynamic Turn-On Transient

2022· article· en· W4308471070 on OpenAlexaff
Hangzhi Liu, Jun Wang, Shiwei Liang, Hengyu Yu, Gaoqiang Deng, Yuwei Wang, Z. John Shen

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2022
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsThyristorGate turn-off thyristorTransient (computer programming)MOS-controlled thyristorIntegrated gate-commutated thyristorSilicon carbideStatic induction thyristorTurn (biochemistry)Materials scienceElectronic engineeringElectrical engineeringComputer scienceEngineeringVoltagePhysicsTransistor

Abstract

fetched live from OpenAlex

The fast turn-on speed of silicon carbide (SiC) gate-turn-off (GTO) thyristor is preferred for pulse power applications. However, the turn-on delay phenomenon hinders its improvement. In this article, the dynamic turn-on transient process of SiC GTO thyristor is investigated and analyzed extensively by means of both numerical simulation and physical modeling. The physical mechanism behind its turn-on transient process is discussed in detail. A physical model based on the charge-control theory is proposed to identify the dominant factors influencing the dynamic turn-on transient. Then the theoretical analysis is quantitatively made on the parameter design of GTO’s unit cell, and methods to increase the turn-on switch speed are extensively discussed. This study provides not only in-depth physical insights into the device’s turn-on characteristics, but also designs guidelines for the advancement of SiC GTO thyristor.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.845

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 integrity0.0000.000
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 head0.227
Teacher spread0.217 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

Explore more

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